Breaking down the OEWG’s legacy: Hits, misses, and unfinished business

What is the OEWG?

The open-ended working groups (OEWGs) are a type of format present in the UN that is typically considered the most open, as the name suggests. It means that all UN member and observer states, intergovernmental organisations, and non-governmental organisations with the UN Economic and Social Council (ECOSOC) consultative status may attend public meetings of the working group. Yet, decisions are made by the UN member states.  There are various OEWGs at the UN. Here, we are addressing the one dealing with cybersecurity.

What does the OEWG on cybersecurity do? In plain language, it tries to find more common ground on what is allowed and what is not in cyberspace, and how to ensure adherence to these rules. In the UN language, the Cyber OEWG was mandated to ‘continue to develop the rules, norms, and principles of responsible behaviour of states, discuss ways for their implementation, and to study the possibility of establishing regular institutional dialogue with broad participation under the auspices of the UN.’

How was the OEWG organised? The OEWG was organised around an organisational session that discussed procedures and modus operandi, and substantive ones dealing with the matter, as well as intersessional meetings and town halls supplementing the discussions. The OEWG held 10 substantive sessions during its 5-year mandate, with the 11th and final session just around the corner in July 2025, where the group will adopt its Final report.


The OEWG through expert eyes: Achievements, shortfalls, and future goals

As the OEWG 2019–2025 process nears its conclusion, we spoke with cybersecurity experts to reflect on its impact and look ahead. Their insights address four key questions: (1) the OEWG’s most substantive contributions and shortcomings in global ICT security; (2) priorities for future dialogues on responsible state behavior in cyberspace; (3) the feasibility of consensus on a permanent multilateral mechanism; and (4) the potential relevance of such a mechanism in today’s divisive geopolitical climate. Their perspectives shed light on what the OEWG has achieved—and the challenges still facing international cyber governance.

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Katherine Getao, Senior Research Fellow, DiploFoundation

The OEWG, as intended by its designers during the 2017 UNGGE process, has enabled broad, inclusive, voluntary participation in global cybersecurity policy discussions. Countries from all continents have chosen to participate and have gained a better understanding of state actions necessary to protect global peace and security in and through ICTs. The OEWG has enabled global agenda-setting, e.g. through the widespread adoption of a framework of action commitment to establish points of contact, it has stimulated and galvanised regional ICT and cybersecurity processes such as joint capacity-building, development of protocols, etc., examples being (in Africa) activities at the AU headquarters as well as RECs, notably ECOWAS. The OEWG also enables countries that are new to the domain to learn and build useful networks.

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That said, the global picture for ICT security is still very uncertain and risky. ICT security involves what I term the “Robin Hood” effect, where the ingenuity and intelligence enabled by ICT can have equalising effects in conflicts between technologically advanced and weaker states. Whether the multilateral policy discussions and broad agreements have in any way tempered conflicts about or involving ICTs remains to be seen. My other observation about the OEWG is that by broadening the stakeholders, the agenda and content of the discussions and documents have grown and lack some of the coherence enjoyed by the UNGGE outcomes.

Regarding the agenda, I think the broad sections: emerging threats, norms, CBMs, international law, capacity building, way forward – are still relevant, but global current evènts are demonstrating that new issues will inevitably arise under these headings. My concern is more about process than agenda. Given the rapidly changing global environment, the agenda should remain fluid. I would suggest three  process additions:

  • Have an academic track, both to ensure that emerging issues and technologies are discussed as early as possible and to orient the emerging generation towards the norms, policies and laws. This could involve selected academic researchers, centres of excellence, online courses etc.
  • Insert the issue into ongoing ICT processes, maybe by having a ‘school’ or other type of side event to help participants correlate the issues they are already discussing with emerging global ICT peace and security policy, given that it is a cross-cutting issue.
  • Responsible states emerge from responsible leaders. The OEWG is now mature enough to seek national and regional champions of responsible state behaviour in cyberspace. Inserting this issue into the postures and statements of global opinion leaders would hopefully influence the behaviour of states.

States probably could reach consensus on the structure and function of a future permanent mechanism because, apart from the concerns about resourcing, building an institution is often an attractive, visible ‘quick win.’ In my view, however, I would not support the establishment of a purely policy-making institution in such a fluid, complex and practical field. Suitable institutions might be developed or supported in suitable implementation areas.

I think it is too early to develop a permanent mechanism. A 5-year (for example) revolving process approval would give some stability while remaining flexible and needs-based

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Nemanja Malisevic, Senior Director of Digital Diplomacy, Microsoft

The Open-Ended Working Group’s most substantive contribution is its role in encouraging states to articulate national and regional positions on the application of international law in cyberspace. Over 30 countries, along with the African Union and EU, submitted formal positions. This growing body of documented perspectives has helped clarify how states interpret existing legal frameworks in cyberspace—an important step toward building a shared understanding of responsible state behavior online. Despite these positive developments, all things considered, the OEWG has not delivered many tangible outcomes that materially improve global cybersecurity. Key issues such as the cyber mercenary market, coordinated vulnerability disclosure, and the protection of public critical infrastructure remain largely unaddressed. The process has struggled to move beyond dialogue into actionable strategies.

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The consensus-based nature of the OEWG allows a small number of states to block progress. Without genuine cooperation and constructive engagement from all participants, the process risks stagnation. Additionally, the current stakeholder modalities have proven inadequate. For cybersecurity discussions to be effective, they must include a diverse range of voices—technical experts, civil society, and system operators. Unfortunately, the OEWG has not provided a truly inclusive platform for these stakeholders to contribute meaningfully.

To advance responsible state behavior in cyberspace, future efforts may need to move beyond the limitations of the types of processes that we have traditionally seen in this space.  Governments should explore mechanisms that allow for real and tangible progress. Models like the Ottawa Declaration on cluster munitions and the Montreux Document on military contractors—though not directly applicable—offer interesting food for thought in this regard. A future approach should prioritize actionable strategies and more inclusive participation to address urgent cybersecurity challenges.

Whether states can reach consensus on a permanent mechanism for dialogue depends entirely on political will. The current geopolitical climate makes this a challenging prospect, but not an impossible one.  Ideally, such a mechanism would be state-led and permanent, operating on a single-track basis while incorporating meaningful multistakeholder participation. It should be designed not just for dialogue, but for action—equipped with the tools and authority to implement strategies that enhance global cybersecurity in practical, measurable ways.

The relevance and influence of a future permanent mechanism will hinge on its design, ambition and implementation. If it replicates the limitations of the current OEWG—particularly its susceptibility to deadlock and exclusion of key stakeholders—then it is unlikely to achieve meaningful progress. However, if it is action-oriented, inclusive, and strategically focused, it could become a powerful tool for fostering a more secure and stable cyberspace.

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Christina Rupp, Senior Policy Researcher Cybersecurity Policy and Resilience, Interface

The Open-ended Working Group 2021-2025 has made a lasting contribution to global discussions on ICT security by broadening participation and providing a platform for smaller delegations and underrepresented states to engage substantively in international discourse on cybersecurity policy. This more inclusive dialogue on responsible behavior in cyberspace has strengthened cross-regional coalition-building, fostered understanding across diverse perspectives, and – as repeatedly emphasized by the Group’s Chair – thus served as a confidence-building measure (CBM) in itself.

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The adoption of three Annual Progress Reports (APRs) by consensus in 2022, 2023, and 2024 amidst a challenging political climate represents a notable achievement in sustaining multilateral dialogue on cybersecurity. These reports also reflect concrete, if modest, progress, including, inter alia, the establishment of a Points of Contact (PoC) directory, agreement on eight global cyber CBMs, and consensus on a comprehensive section addressing existing and potential threats to international peace and security stemming from the use of ICTs. However, translating dialogue into implementation has remained a challenge over the course of the OEWG’s deliberations. Persistent divisions – for example, over prioritizing the implementation of existing commitments versus the elaboration of new norms and referencing discussions on International Humanitarian Law – have limited the Group’s ability to move from consensus language to specific outcomes.

Looking ahead, discussions on cybersecurity in the context of the United Nations First Committee should shift toward operationalizing the existing framework for responsible state behavior. This framework – comprising, inter alia, 11 norms for responsible state behavior, existing international law including the UN Charter, eight global cyber-confidence building measures including the PoC directory, as well as 10 cyber capacity-building principles – offers sufficient tools to do so. What is needed now is to give enhanced meaning to their sometimes abstract language and align them with practical, on-the-ground realities. Bringing in expert briefers and adopting more interactive formats could invigorate discussions and support bridging gaps between technical, legal, political, and diplomatic communities.

Whether states can reach final consensus on the design of a future permanent mechanism on cybersecurity under UN auspices next month remains an open question, particularly given the fragile compromises and last-minute diplomacy that have characterized the final stages of APR negotiations over the past two years. Annex C of the 2024 APR outlines a solid basis of elements of future permanent mechanism, but key issues – particularly concerning dedicated thematic groups and stakeholder modalities – remain unresolved. A successful outcome in July will require both a high level of political will and a willingness to compromise from all states in order to agree on a clear roadmap that avoids duplication and overlaps, fosters deeper dialogue, and enables meaningful stakeholder contributions to support evidence-based policymaking on cybersecurity at the UN level.

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Eugene EG Tan,
Associate Research Fellow
Centre of Excellence for National Security
S. Rajaratnam School of International Studies (RSIS), Nanyang Technological University, Singapore (NTU)

Most of the OEWG 2021-25 has been conducted under a geopolitical storm, making any agreement to advance the framework on responsible state behaviour in the use of ICTs a hard-won consensus. But even if it seems like an evaluation that the glass is half full, there has been progress. The OEWG has at least three annual progress reports to show for the discussions that has gone on in the group, which is no mean feat considering the geopolitical situation. Any attempt to rollback state commitments made in the previous OEWG and UNGGE has also been met with a vigorous pushback by the majority of states, keeping much of the acquis intact. This is especially important in a time where international law has come under the cosh due to the actions of some states.

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There has however been a substantial change in how discussions at the group has progressed. The longer mandate given to the OEWG has enabled the group to place more emphasis on the implementation of the framework (and reporting back to the framework), rather than being bogged down with the ideological differences that has long stalked the process. I think this action-oriented approach is useful to all stakeholders in the process – states, academics, civil society, and industries – because it enables feedback on which of the norms, capacity building, and confidence building measures have proven effective, and what has been less so. And this should continue into the future permanent mechanism.

How the future permanent mechanism will look like is unclear and would most certainly be a result of political agreement that is UN-acceptable to states and unfortunately minimises the role of non-state stakeholders. Non-state stakeholders will have to accept the modalities that the future mechanism agrees to. But this does not mean that the role of non-state stakeholders should stop or decrease, and it is incumbent on the states that see the value of non-state stakeholder participation to ensure non-state stakeholder voices remain heard and relevant to the discussions on responsible state behaviour. 

The numerous side events held on the sidelines of the OEWG are important in providing states and other stakeholders to deepen discussions and learn from the expertise of other states and stakeholders. This dialogue and knowledge sharing opportunity should be kept alive in the future mechanism in order to prevent the future mechanism from being siloed into a diplomatic endeavour. The future of the stability of cyberspace lies all in the hands of all stakeholders, and it would be richer if all stakeholders were involved in the process – we can only hope that the collective wisdom of all states will prevail at the final session in July.

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Yuliya Shlychkova, Vice President, Government Affairs and Public Policy, Kaspersky

In our view, the most significant achievement by the OEWG 2021-2025 was reaching an agreement to set up the Points of Contact Directory. This database serves as an important tool promoting practical international cooperation countering cybersecurity threats, allowing faster information exchange between competent bodies. When reflecting on the work of the OEWG 2021-2025, we would also like to highlight the informal intersessional consultative meetings with stakeholders organized by the Chair of OEWG H.E. Mr. Burhan Gafoor and thank him for his genuine interest in engaging in a direct conversation with a multi-stakeholder community.

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The UN Report of the Group of Governmental Experts on Advancing Responsible State Behaviour in Cyberspace in the Context of International Security (A/76/135), which was published in 2021, suggested numerous considerations for agenda prioritisation. Among them, issues covered by norms F, G (critical infrastructure protection) and I (supply chain security) could be regarded as particularly important nowadays, as one can observe a constantly growing number of cyberthreats against critical infrastructure as well as supply chains.

We hope that a consensus on the structure and function of a future permanent mechanism for dialogue on ICT-related issues will eventually be reached. We also hope that member states will work out concrete parameters of such mechanism.

During times of geopolitical turbulence, any mechanism, which enables direct dialogue, is of special importance. That is why we believe that a future permanent mechanism would be highly relevant. It would also inherit the reputation of the OEWG as one of the premier platforms for the global dialogue on ICT-related issues. Our view is that, in order to increase its efficiency, the OEWG successor should keep channels of communication with the private sector open, which has vast expertise in the ICT sphere and could make a meaningful contribution to the depth of any future discussion. Their format could vary – for example, it could be similar to aforementioned Chair’s informal intersessional consultative meetings with stakeholders. At the same time, specific measures could be taken in order to make such consultations more relevant and useful for the purposes of a future permanent mechanism – in particular, by dividing all interested non-government stakeholders in thematic groups based on their area of activity, and then inviting them to specific rounds of consultations which are relevant to their expertise.

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Martin Xie, Director of Brussels Cybersecurity Transparency Center, Huawei

The 2021-2025 UN Open-Ended Working Group (OEWG) has served as a pivotal forum for global cyber norms diplomacy, though its legacy remains decidedly mixed. Its most enduring contribution lies in institutionalizing a universal dialogue platform—successfully bringing all UN member states into the conversation while establishing essential trust-building mechanisms, most notably the global Points of Contact directory. This procedural progress has laid a valuable foundation for future international discussions. However, substantial advancements, particularly in developing new norms, often encountered obstacles due to geopolitical tensions, resulting in reaffirmations of existing norms rather than the creation of new commitments. Complex issues, including ransomware and emerging technology norms, remain largely unresolved.

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Moving forward, emphasis should shift from norm-setting to practical implementation and operational cooperation. As cyber threats rapidly evolve—including sophisticated AI-driven incidents, supply chain vulnerabilities, and persistent ransomware—the international community would benefit from actionable measures aimed at mitigating these risks. The technology industry’s practical experience can undoubtedly contribute to this effort. Enhanced public-private cooperation in threat assessment, vulnerability disclosure, and incident response can meaningfully improve global cyber resilience.

The consensus to establish a flexible, Programme of Action (PoA)-style follow-up mechanism post-2025 reflects a pragmatic step towards continuous diplomatic engagement. This mechanism aims to sustain dialogue and build constructively on previous OEWG efforts. Its effectiveness will largely depend on genuine multistakeholder participation, where technical insights are appropriately considered without political bias.

In an increasingly complex geopolitical environment, the mechanism’s most immediate value may be crisis management and maintaining open channels of communication. Its role will likely remain normative, focusing on fostering trust and predictability rather than enforcing norms strictly or attributing responsibility explicitly. For the technology industry, this landscape presents both ongoing compliance complexity and, more significantly, a strategic importance for constructive, collaborative participation in safeguarding the stability and security of our interconnected digital infrastructure.


Topic-by-topic: Diplo’s experts assess OEWG achievements and what comes next

In addition to external cybersecurity experts, we asked our own team—who have tracked the OEWG process since its inception—to share their analysis. They highlight key achievements over the past five years, identify gaps in the discussions, and offer predictions on where debates may lead during the final session and beyond.

Threats
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Over the past five years, the OEWG’s discussions on threats have really grown—not just in length, but in depth. As the threat landscape evolved, so did the conversations. What started as fairly general discussions have now become much more detailed and specific, with nearly a quarter of recent sessions focused on threats alone. That shift shows two things: first, how rapidly cyber risks like ransomware, state-sponsored attacks, and now even AI-driven threats are expanding; and second, that states are getting more comfortable talking openly about these issues.

One standout achievement is how much more states are leaning into cooperation. What’s interesting is that they’re not just naming threats anymore—they’re using just as much time to talk through how to tackle them together. That’s a big deal. We’ve seen more proposals for joint responses, support for capacity-building, and collective action than ever before. It’s a sign that this forum isn’t just about pointing out problems, but about working toward solutions.

There’s also been progress in how states describe and understand threats. In recent sessions, they flagged some new concerns—like the vulnerability of undersea cables and satellite communication networks. That’s a big leap in recognizing the physical infrastructure behind the internet and the risks we might not have talked about much before. States also raised alarms about cyber incidents targeting critical sectors like healthcare, aviation, and energy, and added AI to the mix, with specific concerns about the data used in machine learning and the misuse of AI to power more sophisticated attacks.

All of this points to a maturing conversation. We’re seeing a more layered understanding of threats, which makes space for more tailored, effective responses. And that’s exactly what global cooperation on cybersecurity should be aiming for: staying ahead of the curve, together.

What’s next?

As we head into the final session of the OEWG, expect threat discussions to stay front and centre—more detailed, more action-oriented, and more grounded in real-world risks. That momentum is set to carry into the UN’s future permanent mechanism, which will likely include a dedicated working group on threats. This won’t be just another talk shop. It’s being designed to take a cross-cutting, policy-driven approach—bringing in technical experts and other stakeholders to focus on concrete steps that boost resilience, protect critical infrastructure, and strengthen global stability in cyberspace.

The trend is clear: more specifics, more cooperation, more solutions. Future discussions will be about connecting policy and practice—turning shared concerns into collective action. So while the OEWG chapter might be closing, the real work on threat response is only just beginning.

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Andrijana Gavrilovic
Head of Policy and Diplomatic Reporting, Diplo

Rules, norms and principles
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The OEWG 2019-2025 established itself as the main space for open and inclusive talks about responsible state behaviour in cyberspace, despite a tough political environment marked by big power rivalries, ongoing conflicts, and deep divisions. One of the key achievements was reconfirming and reinforcing the existing normative framework. States didn’t just reaffirm the 11 voluntary, non-binding norms — they also moved the conversation forward on the Chair’s proposed voluntary Norms Implementation Checklist, This checklist breaks down each norm in more detail, pointing out specific actions countries can take both nationally and internationally. It’s now attached to the Zero Draft of the OEWG Final Report. 

This shift from just setting norms to focusing on how to actually put them into practice is an important step. While the OEWG helped make this shift happen, many countries have already started applying the norms on their own, which shows these principles are becoming more embedded in real-world policies compared to five years ago. Sharing experiences—especially around protecting critical infrastructure and supply chain security—is growing, showing a real push to turn these norms into action. Even though the checklist is still voluntary, most agree it’s a helpful tool for being more transparent, supporting self-checks, and boosting accountability among countries.

Another important role of the OEWG was as a place to openly discuss the future of the normative framework. The group provided a space for countries to talk about whether the current norms are enough or if new, possibly legally binding rules are needed to handle new cyber threats. Although they didn’t reach an agreement on this, the OEWG allowed different views to be shared in a fair and inclusive way, highlighting the need for ongoing dialogue and cooperation.

The OEWG also made progress in setting up a more permanent way to continue this work, while recognising the important role of regional organisations, civil society, and other non-governmental stakeholders. The Zero Draft highlights these contributions and stresses the value of consultations between meetings. Most importantly, it lays the groundwork for a permanent institutional mechanism, showing strong political will to keep international cooperation on cyber norms going beyond 2025.

What’s next?

Looking ahead, the Zero Draft notes that countries are still divided on whether new or legally binding norms are needed. While we don’t expect a final consensus at the closing session, there’s clear support for keeping the conversation going in a structured way. The Chair has suggested creating thematic working groups under a future permanent mechanism. This could be a practical way to move forward, focusing on putting norms into practice while also allowing room to revisit the rules debate in a more focused,  issue-specific context. These groups could be key to driving implementation at national, regional, and sector levels, while also making sure multiple stakeholders can stay involved.

However, in an era where military instruments increasingly shape the resolution of international disputes, to what extent can these peacetime-negotiated UN cyber norms remain relevant and applicable? How can voluntary norms—developed through consensus and intended to promote transparency, restraint, and responsible behaviour—be upheld when geopolitical tensions escalate into open conflict? And how might states, but also stakeholders, continue to apply and interpret these norms to distinguish responsible conduct from destabilising behaviour, even when trust and cooperation are under strain? These questions lie at the heart of ensuring that the normative framework remains a meaningful tool for promoting international stability and accountability—especially when the rules-based order itself is being tested. 

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Anastasiya Kazakova
Cyber Diplomacy Knowledge Fellow, Diplo

International law
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Between 2021 and 2025, the OEWG continued to explore how international law—especially the UN Charter—applies to how states use ICTs. These discussions got more detailed over time, both in substantive and intersessional meetings. One positive trend has been the growing number of national statements on how international law applies in cyberspace. Over 100 countries have now shared their views, along with inputs from other organisations, which helped enrich the debate (see paragraph 40(f) of the Zero Draft). These contributions gave countries a chance to share understandings of how international law applies to cyberspace and of the state responsibilities in the use of ICTs.

States largely agreed on some key legal principles. They reaffirmed that state sovereignty and related international norms and principles still apply when it comes to ICT-related activities. They also confirmed that core principles from the UN Charter—the principle of non-intervention, the prohibition on the threat or use of force, and the peaceful settlement of disputes, non-intervention—remain valid and relevant in cyberspace.

What’s next?

Looking ahead to the final session, we expect some countries to push for the inclusion of international human rights law (IHRL) and international humanitarian law (IHL) in the Final Report. Even though these two areas were discussed quite a bit during this OEWG cycle, they’re currently missing from the international law section of the Zero Draft. Including them would also help ensure they’re part of the list of issues to be explored in any future discussions under the new permanent mechanism.

That said, one major divide still hasn’t been resolved: should there be a new, legally binding agreement on how international law applies to ICTs? This question continues to split the group, and that’s unlikely to change anytime soon.The proposal to create a thematic group focused on international law within the future permanent mechanism comes with its own set of challenges. Some countries might try to use this group to start negotiating a binding legal instrument. Others will likely resist that idea, which could cause the group to stall. As with the other proposed thematic groups, it will also be important to sort out who gets to participate—technical experts, legal advisers, policy practitioners, and others. So far, it’s unclear how non-governmental stakeholders will be involved, and some states remain sceptical about their role. There’s also a risk that dividing the work into multiple thematic groups could fragment the conversation, leading to siloed discussions rather than a holistic approach. And for countries with fewer resources, it may be hard to keep up across multiple parallel discussions, potentially giving more influence to those with larger delegations and greater capacity.

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Pavlina Ittelson
Executive Director, Diplo US

Capacity building
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Cyber capacity-building has remained a cross-cutting pillar of the OEWG’s ICT-security agenda, sustaining momentum even as global tensions have made cooperation more difficult. Over the past five years, three key achievements stand out. 

First, the launch of the Global Roundtable on ICT Capacity-Building in New York in May 2024 marked a big step forward. It was the UN’s first-ever event focused solely on this topic, bringing together governments, industry, civil society, and academia to share experiences, highlight good practices, and discuss what’s still missing. The strong support for making this roundtable a regular fixture shows a real commitment to keeping everyone at the table and recognising the important role of non-state actors in strengthening capacity around the world. 

Second, countries have worked to set up practical tools to deliver on capacity-building. A key example is the Global ICT Security Cooperation and Capacity-Building Portal (GCSCP), which has received wide support as a neutral, government-led platform to coordinate capacity-building efforts. Alongside it, a needs-based capacity-building catalogue was also welcomed, provided both tools are connected with existing efforts to avoid duplication. Together, they’re meant to help match countries’ needs with available support.

Third, there’s been progress on the financing side. A voluntary UN trust fund was proposed to help finance projects and support participation from smaller delegations. It was broadly welcomed and is expected to complement other funding sources like the World Bank’s Cybersecurity Multi-Donor Trust Fund and ITU mechanisms.

What’s next? 

The OEWG’s final session needs to turn these ideas into something that works in practice. That includes agreeing on how often to hold the roundtables, how they’ll be run, and how they’ll connect to whatever permanent mechanism comes next. The goal is to make them more than just another meeting—to turn them into a space where real progress is made.

For the GCSCP and the capacity-building catalogue, a phased rollout is likely, starting with basic modules, a document repository, a Points of Contact directory, mapping of states’ needs, and a calendar of events. More sensitive features—like a norms-tracker proposed by Kuwait or an incident-reporting tool—are likely to be delayed, given concerns from some countries about data sharing and potential politicisation.

The trust fund will need clear criteria for who can access it, how it will be monitored, and how to avoid overlaps with existing efforts. There’s still uncertainty about whether it will attract enough consistent funding to meet the varied needs of developing countries.

Finally, there’s still no agreement on how the future permanent mechanism should handle capacity-building. Some countries want a dedicated working group, while others prefer to integrate it into all relevant discussions. The OEWG has built the basic framework—now the task is to finalise the details and make sure cyber capacity-building stays inclusive, focused on real needs, and able to adapt to future challenges.

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Salome Petit-Siemens
Master’s Student in International Security, Sciences Po

CBMS
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The launch of the Points of Contact (PoC) Directory in May 2024 stands, without a doubt, as the flagship achievement of the OEWG’s current mandate. Although the concept was first introduced in the 2021 OEWG report as one of the confidence-building measures (CBMs), the PoC Directory began to see real-world use by the end of the year 2024. Its operationalisation required active investment by the UN Secretariat, which organised the first system-wide ping test in June 2024 to verify the accuracy and responsiveness of entries. This was followed by a tabletop exercise planned for March 2025.

Another important milestone—closely tied to the PoC’s rollout—was the growing agreement on the need for a standardised communication template. At first, some states were hesitant, worried that it might make using the Directory too rigid or formal. But over time, the idea gradually gained traction. By April 2025, the Secretariat had circulated a draft template—an important step toward making communications between PoCs more consistent and efficient.

While not as visible, the globalisation of CBM practices has been arguably just as significant. Traditionally, CBM implementation was driven by regional organisations. However, 2024 witnessed a notable increase in cross-regional and multilateral initiatives, including global workshops, seminars, and training programmes. These efforts have contributed to a broader diffusion of CBM norms and practices beyond regional silos.

Yet, as we take stock of the OEWG’s progress over the past five years, one cannot ignore the gradual erosion of multistakeholder engagement in CBM discussions. As the OEWG approaches its final session, it is crucial not only to celebrate achievements but also to acknowledge areas where inclusivity and innovation have lagged behind.

The standardised template for PoC communication is likely to dominate discussions during the OEWG’s concluding session, especially given the Chair’s stated intention to include it in the final report.

The idea of integrating CBMs into the different thematic groups—something that’s part of the vision for a future permanent mechanism—was introduced in the last session. But most delegations seemed to prefer holding off on deep discussions until that mechanism is actually up and running. While spreading CBMs across different topics sounds good in theory, it also comes with risks. Moving these conversations out of their dedicated agenda item might risk politicising what has so far remained one of the OEWG’s most consensus-driven domains.

Ultimately, despite notable advancements, especially since 2024, the future of CBMs lies in their effective implementation, not necessarily future discussions at a global level. The next phase of development for the PoC Directory, in particular, hinges on actual use by states. Some key questions, first raised back in 2022, are still up in the air, including the precise scope of PoC functions. Only practice will provide answers to those questions.

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Jenne-Louise Roellinger
PhD student in International Relations, Sciences Po

Future mechanism
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One of the biggest achievements of the OEWG has been getting broad agreement that we need a regular, ongoing space to talk about international cybersecurity. Even with all the geopolitical tensions, countries have managed to keep talking about how a future mechanism could look. In fact, the OEWG has shown that dialogue—even between politically divided countries—is not just possible, but necessary, and increasingly seen as something that should be institutionalised.

Right now, there’s still no agreement on what this future mechanism should be. Some countries want to continue with the OEWG, while others are pushing for a Programme of Action (PoA). To find a middle ground, the Chair’s Zero Draft suggests setting up a permanent UN-backed body that would hold annual meetings and run several thematic working groups. It’s a compromise aimed at keeping everyone on board while ensuring the process keeps moving. This setup recognises the need for continuity, but its design must remain politically and procedurally neutral to secure broad support.

Still, it’s unclear whether this proposal addresses the concerns of non-governmental stakeholders, who were excluded from formal sessions, despite repeated calls for transparency and inclusion. Although intersessional consultations offered some space for engagement, many in the civil society, the private sector, and the technical community expressed concern that their expertise and operational relevance were not adequately reflected in the negotiation process. 

What’s next?

If countries can agree on a final report, and we shouldn’t rule that out—especially given recent signs of cooperation between Russia and the US at the UNGA—it will likely support the idea of a permanent institutional mechanism, though maybe without naming it outright. That would give the UNGA First Committee a chance to adopt a resolution during its 80th session later this year that formally launches the new framework. Such an outcome would mark a major step forward. We could see continued work starting in 2026 through annual meetings, thematic working groups, and inclusive consultations, as the Chair has proposed.

But if consensus doesn’t happen, the Chair might release a final report that lays out where countries agree and attaches statements from states on where they still disagree. At the moment, three main positions seem to be taking shape. One group of states backs the PoA model—basically a single-track, more inclusive process with full multistakeholder participation. Another group wants to stick with the OEWG as it is now, including the accreditation-based model for stakeholder participation agreed in 2022. A third group is pushing for a government-only, multilateral setup focused on five thematic pillars: threats, norms, international law, confidence-building, and capacity-building. These states also express strong reservations about continued stakeholder involvement in future UN cyber discussions.

These disagreements—about what the institutional setup should be, what issues to cover, and how stakeholders should be involved—highlight how politically tricky these negotiations are. And they’ll likely shape whatever comes next after the OEWG ends. If the divisions continue, we might see competing resolutions in the First Committee, which would mean a vote—and that increases the chance of fragmentation and less overall support for any future mechanism. Some delegations have already warned against this path, noting that splitting resources across multiple tracks could stretch everyone too thin. Yet in today’s fractured geopolitical landscape, the risk of a divided outcome in cyber diplomacy is not just possible—it’s increasingly likely.

 Face, Head, Person, Photography, Portrait, Happy, Smile, Accessories, Earring, Jewelry, Body Part, Neck, Adult, Female, Woman

Anastasiya Kazakova
Cyber Diplomacy Knowledge Fellow, Diplo


Stay tuned: Unpacking the OEWG’s impact with reports and events

Buckle up — we’re heading into the final phase of the OEWG! As the process wraps up, we’ll be tracking every development, publishing an in-depth report, and hosting events to reflect on the OEWG’s legacy, lessons learned, and what lies ahead. Whether you’re a long-time observer or just tuning in, there’s something for everyone.

Follow the final session live:
Our dedicated event page will feature AI-generated session reports, updated in near real-time to help you stay on top of the discussions as they unfold.

For seasoned negotiators:
We’ve also analysed the text of the Zero Draft and its Rev 1, which delegations will be negotiating during the final session — helping you navigate the proposals, sticking points, and emerging consensus.



Meme coins: Fast gains or crypto gambling?

Meme coins have exploded in the crypto market, attracting investors with promises of fast profits and viral hype. These digital tokens, often inspired by internet memes and pop culture, like Dogecoin, Pepe, Dogwifhat and most recently Trump coin, do not usually offer clear utility. Instead, their value mostly depends on social media buzz, influencer endorsements, and community enthusiasm. In 2025, meme coins remain a controversial yet dominant trend in crypto trading. 

Viral but vulnerable: the rise of meme coins 

Meme coins are typically created for humour, social engagement, or to ride viral internet trends, rather than to solve real-world problems. Despite this, they are widely known for their popularity and massive online appeal. Many investors are drawn to meme coins because of the potential for quick, large returns. 

For example, Trump-themed meme coins saw explosive growth in early 2024, with MAGA meme coin (TRUMP) briefly surpassing a $500 million market cap, despite offering no real utility and being driven largely by political hype and social media buzz. 

Analysis reports indicate that in 2024, between 40,000 and 50,000 new meme tokens were launched daily, with numbers soaring to 100,000 during viral surges. Solana tops the list of blockchains for meme coin activity, generating 17,000 to 20,000 new tokens each day. 

Chainplay’s ‘State of Memecoin 2024’ report found that over half (55.24%) of the meme coins analysed were classified as ‘malicious’. 

A chaotic blend of internet culture, greed, and adrenaline, meme coins turn crypto investing into a thrilling game where hype rules and fortunes flip in seconds.

The risks of rug pulls and scams in meme coin projects 

Beneath the humour and viral appeal, meme coins often hide serious structural risks. Many are launched by developers with little to no accountability, and most operate with centralised liquidity pools controlled by a small number of wallets. The setup allows creators or early holders to pull liquidity or dump large token amounts without warning, leading to devastating price crashes—commonly referred to as ‘rug pulls.’ 

On-chain data regularly reveals that a handful of wallets control the vast majority of supply in newly launched meme tokens, making market manipulation easy and trust almost impossible. These coins are rarely audited, lack transparency, and often have no clear roadmap or long-term utility, which leaves retail investors highly exposed. 

The combination of hype-driven demand and opaque tokenomics makes meme coins a fertile ground for fraud and manipulation, further eroding public confidence in the broader crypto ecosystem. 

A chaotic blend of internet culture, greed, and adrenaline, meme coins turn crypto investing into a thrilling game where hype rules and fortunes flip in seconds.

Gambling disguised as investing: The adrenaline rush of meme coins 

Meme coins tap into a mindset that closely resembles gambling more than traditional investing. The entire culture around them thrives on adrenaline-fueled speculation, where every price spike feels like hitting a jackpot and every drop triggers a high-stakes rollercoaster of emotions. Known as the ‘degen’ culture, traders chase quick wins fuelled by FOMO, hype, and the explosive reach of social media.

The thrill-seeking mentality turns meme coin trading into a game of chance. Investors often make impulsive decisions based on hype rather than fundamentals, hoping to catch a sudden pump before the inevitable crash. 

It is all about momentum. The volatile swings create an addictive cycle: the excitement of rapid gains pulls traders back in, despite the constant risk of losing everything.

While early insiders and large holders strategically time their moves to cash out big, most retail investors face losses, much like gamblers betting in a casino. The meme coin market, therefore, functions less like a stable investment arena and more like a high-risk gambling environment where luck and timing often outweigh knowledge and strategy. 

A chaotic blend of internet culture, greed, and adrenaline, meme coins turn crypto investing into a thrilling game where hype rules and fortunes flip in seconds.

Is profit from meme coins possible? Yes, but…

While some investors have made substantial profits from meme coins, success requires expert knowledge, thorough research, and timing. Analysing tokenomics, community growth, and on-chain data is essential before investing. Although they can be entertaining, investing in meme coins is a risky gamble. Luck remains a big key factor, so meme coins are never considered safe or long-term investments.

Meme coins vs Bitcoin: A tale of two mindsets 

Many people assume that all cryptocurrencies share the same mindset, but the truth is quite different. Interestingly, cryptocurrencies like Bitcoin and meme coins are based on contrasting philosophies and psychological drivers.

Bitcoin embodies a philosophy of trust through transparency, decentralisation, and long-term resilience. It appeals to those seeking stability, security, and a store of value rooted in technology and community consensus—a digital gold that invites patience and conviction. In essence, Bitcoin calls for building and holding with reason and foresight. 

Meme coins, on the other hand, thrive on the psychology of instant gratification, social identity, and collective enthusiasm. They tap into our desire for excitement, quick wins, and belonging to a viral movement. Their value is less about utility and more about shared emotion— the hope, the hype, and the adrenaline rush of catching the next big wave. Meme coins beckon with the thrill of the moment, the gamble, and the social spectacle. It makes meme coins a reflection of the speculative and impulsive side of human nature, where the line between investing and gambling blurs.

Understanding these psychological underpinnings helps explain why the two coexist in the crypto world, yet appeal to vastly different types of investors and mindsets. 

A chaotic blend of internet culture, greed, and adrenaline, meme coins turn crypto investing into a thrilling game where hype rules and fortunes flip in seconds.

How meme coins affect the reputation of the entire crypto market

The rise and fall of meme coins do not just impact individual traders—they also cast a long shadow over the credibility of the entire crypto industry. 

High-profile scams, rug pulls, and pump-and-dump schemes associated with meme tokens erode public confidence and validate sceptics’ concerns. Many retail traders enter the meme coin space with high hopes and are quickly disillusioned by manipulation and sudden losses. 

This leads to a sense of betrayal, triggering risk aversion and a generalised mistrust toward all crypto assets, even those with strong fundamentals like Bitcoin or Ethereum. Such disillusionment does not stay contained. It spills over into mainstream sentiment, deterring new investors and slowing institutional adoption. 

As more people associate crypto with gambling and scams rather than innovation and decentralisation, the market’s growth potential suffers. In this way, meme coins—though intended as jokes—could have serious consequences for the future of blockchain credibility. 

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Trading thrills or ticking time bomb?

Meme coins may offer flashes of fortune, but their deeper role in the crypto ecosystem raises a provocative question: are they reshaping finance or just distorting it? In a market where jokes move millions and speculation overrides substance, the real gamble may not just be financial—it could be philosophical. 

Are we embracing innovation, or playing a dangerous game with digital dice? In the end, meme coins are not just a bet on price—they are a reflection of what kind of future we want to build in crypto. Is it sustainable value, or just viral chaos? The roulette wheel is still spinning. 

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Cognitive offloading and the future of the mind in the AI age

AI reshapes work and learning

The rapid advancement of AI is bringing to light a range of emerging phenomena within contemporary human societies.

The integration of AI-driven tools into a broad spectrum of professional tasks has proven beneficial in many respects, particularly in terms of alleviating the cognitive and physical burdens traditionally placed on human labour.

By automating routine processes and enhancing decision-making capabilities, AI has the potential to significantly improve efficiency and productivity across various sectors.

In response to these accelerating technological changes, a growing number of nations are prioritising the integration of AI technologies into their education systems to ensure students are prepared for future societal and workforce transformations.

China advances AI education for youth

China has released two landmark policy documents aimed at integrating AI education systematically into the national curriculum for primary and secondary schools.

The initiative not only reflects the country’s long-term strategic vision for educational transformation but also seeks to position China at the forefront of global AI literacy and talent development.

chinese flag with the city of shanghai in the background and digital letters ai somewhere over the flag

The two guidelines, formally titled the Guidelines for AI General Education in Primary and Secondary Schools and the Guidelines for the Use of Generative AI in Primary and Secondary Schools, represent a scientific and systemic approach to cultivating AI competencies among school-aged children.

Their release marks a milestone in the development of a tiered, progressive AI education system, with carefully delineated age-appropriate objectives and ethical safeguards for both students and educators.

The USA expands AI learning in schools

In April, the US government outlined a structured national policy to integrate AI literacy into every stage of the education system.

By creating a dedicated federal task force, the administration intends to coordinate efforts across departments to promote early and equitable access to AI education.

Instead of isolating AI instruction within specialised fields, the initiative seeks to embed AI concepts across all learning pathways—from primary education to lifelong learning.

The plan includes the creation of a nationwide AI challenge to inspire innovation among students and educators, showcasing how AI can address real-world problems.

The policy also prioritises training teachers to understand and use AI tools, instead of relying solely on traditional teaching methods. It supports professional development so educators can incorporate AI into their lessons and reduce administrative burdens.

The strategy encourages public-private partnerships, using industry expertise and existing federal resources to make AI teaching materials widely accessible.

European Commission supports safe AI use

As AI becomes more common in classrooms around the globe, educators must understand not only how to use it effectively but also how to apply it ethically.

Rather than introducing AI tools without guidance or reflection, the European Commission has provided ethical guidelines to help teachers use AI and data responsibly in education.

european union regulates ai

Published in 2022 and developed with input from educators and AI experts, the EU guidelines are intended primarily for primary and secondary teachers who have little or no prior experience with AI.

Instead of focusing on technical complexity, the guidelines aim to raise awareness about how AI can support teaching and learning, highlight the risks involved, and promote ethical decision-making.

The guidelines explain how AI can be used in schools, encourage safe and informed use by both teachers and students, and help educators consider the ethical foundations of any digital tools they adopt.

Rather than relying on unexamined technology, they support thoughtful implementation by offering practical questions and advice for adapting AI to various educational goals.

AI tools may undermine human thinking

However, technological augmentation is not without drawbacks. Concerns have been raised regarding the potential for job displacement, increased dependency on digital systems, and the gradual erosion of certain human skills.

As such, while AI offers promising opportunities for enhancing the modern workplace, it simultaneously introduces complex challenges that must be critically examined and responsibly addressed.

One significant challenge that must be addressed in the context of increasing reliance on AI is the phenomenon known as cognitive offloading. But what exactly does this term entail?

What happens when we offload thinking?

Cognitive offloading refers to the practice of using physical actions or external tools to modify the information processing demands of a task, with the aim of reducing the cognitive load on an individual.

In essence, it involves transferring certain mental functions—such as memory, calculation, or decision-making—to outside resources like digital devices, written notes, or structured frameworks.

digital brain

While this strategy can enhance efficiency and performance, it also raises concerns about long-term cognitive development, dependency on technological aids, and the potential degradation of innate mental capacities.

How AI may be weakening critical thinking

A study, led by Dr Michael Gerlich, Head of the Centre for Strategic Corporate Foresight and Sustainability at SBS Swiss Business School, published in the journal Societies raises serious concerns about the cognitive consequences of AI augmentation in various aspects of life.

The study suggests that frequent use of AI tools may be weakening individuals’ capacity for critical thinking, a skill considered fundamental to independent reasoning, problem-solving, and informed decision-making.

More specifically, Dr Gerlich adopted a mixed-methods approach, combining quantitative survey data from 666 participants with qualitative interviews involving 50 individuals.

Participants were drawn from diverse age groups and educational backgrounds and were assessed on their frequency of AI tool use, their tendency to offload cognitive tasks, and their critical thinking performance.

The study employed both self-reported and performance-based measures of critical thinking, alongside statistical analyses and machine learning models, such as random forest regression, to identify key factors influencing cognitive performance.

Younger users, who rely more on AI, think less critically

The findings revealed a strong negative correlation between frequent AI use and critical thinking abilities. Individuals who reported heavy reliance on AI tools—whether for quick answers, summarised explanations, or algorithmic recommendations—scored lower on assessments of critical thinking.

The effect was particularly pronounced among younger users aged 17 to 25, who reported the highest levels of cognitive offloading and showed the weakest performance in critical thinking tasks.

In contrast, older participants (aged 46 and above) demonstrated stronger critical thinking skills and were less inclined to delegate mental effort to AI.

Higher education strengthens critical thinking

The data also indicated that educational attainment served as a protective factor: those with higher education levels consistently exhibited more robust critical thinking abilities, regardless of their AI usage levels.

These findings suggest that formal education may equip individuals with better tools for critically engaging with digital information rather than uncritically accepting AI-generated responses.

Now, we must understand that while the study does not establish direct causation, the strength of the correlations and the consistency across quantitative and qualitative data suggest that AI usage may indeed be contributing to a gradual decline in cognitive independence.

However, in his study, Gerlich also notes the possibility of reverse causality—individuals with weaker critical thinking skills may be more inclined to rely on AI tools in the first place.

Offloading also reduces information retention

While cognitive offloading can enhance immediate task performance, it often comes at the cost of reduced long-term memory retention, as other studies show.

The trade-off has been most prominently illustrated in experimental tasks such as the Pattern Copy Task, where participants tasked with reproducing a pattern typically choose to repeatedly refer to the original rather than commit it to memory.

Even when such behaviours introduce additional time or effort (e.g., physically moving between stations), the majority of participants opt to offload, suggesting a strong preference for minimising cognitive strain.

These findings underscore the human tendency to prioritise efficiency over internalisation, especially under conditions of high cognitive demand.

The tendency to offload raises crucial questions about the cognitive and educational consequences of extended reliance on external aids. On the one hand, offloading can free up mental resources, allowing individuals to focus on higher-order problem-solving or multitasking.

On the other hand, it may foster a kind of cognitive dependency, weakening internal memory traces and diminishing opportunities for deep engagement with information.

Within the framework, cognitive offloading is not a failure of memory or attention but a reconfiguration of cognitive architecture—a process that may be adaptive rather than detrimental.

However, the perspective remains controversial, especially in light of findings that frequent offloading can impair retention, transfer of learning, and critical thinking, as Gerlich’s study argues.

If students, for example, continually rely on digital devices to recall facts or solve problems, they may fail to develop the robust mental models necessary for flexible reasoning and conceptual understanding.

The mind may extend beyond the brain

The tension has also sparked debate among cognitive scientists and philosophers, particularly in light of the extended mind hypothesis.

Contrary to the traditional view that cognition is confined to the brain, the extended mind theory argues that cognitive processes often rely on, and are distributed across, tools, environments, and social structures.

digital brain spin

As digital technologies become increasingly embedded in daily life, this hypothesis raises profound questions about human identity, cognition, and agency.

At the core of the extended mind thesis lies a deceptively simple question: Where does the mind stop, and the rest of the world begin?

Drawing an analogy to prosthetics—external objects that functionally become part of the body—Clark and Chalmers argue that cognitive tools such as notebooks, smartphones, and sketchpads can become integrated components of our mental system.

These tools do not merely support cognition; they constitute it when used in a seamless, functionally integrated manner. This conceptual shift has redefined thinking not as a brain-bound process but as a dynamic interaction between mind, body, and world.

Balancing AI and human intelligence

In conclusion, cognitive offloading represents a powerful mechanism of modern cognition, one that allows individuals to adapt to complex environments by distributing mental load.

However, its long-term effects on memory, learning, and problem-solving remain a subject of active investigation. Rather than treating offloading as inherently beneficial or harmful, future research and practice should seek to balance its use, leveraging its strengths while mitigating its costs.

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Ultimately, we -as educators, policymakers, and technologists- have to shape the future of learning, work and confront a central tension: how to harness the benefits of AI without compromising the very faculties—critical thought, memory, and independent judgment—that define human intelligence.

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The rise of AI in Hollywood, gaming, and music

It feels like just yesterday that the internet was buzzing over the first renditions of OpenAI’s DALL·E tool, with millions competing to craft the funniest, weirdest prompts and sharing the results across social media. The sentiment was clear: the public was fascinated by the creative potential of this new technology.

But beneath the laughter and viral memes was a quieter, more uneasy question: what happens when AI not only generates quirky artwork, but begins to reshape our daily lives, both online and off? As it turns out, that process was already underway behind the scenes, and we were none the wiser.

AI in action: How the entertainment industry is using it today

Three years later, we have reached a point where AI’s influence seems to have passed the point of no return. The entertainment industry was among the first to embrace this technology, and starting with the 2025 Academy Awards, films that incorporate AI are now eligible for Oscar nominations.

That decision has been met with mixed reactions, to put it lightly. While some have praised the industry’s eagerness to explore new technological frontiers, others have claimed that AI greatly diminishes the human contribution to the art of filmmaking and therefore takes away the essence of the seventh art form.

The first wave of AI-enhanced storytelling

One recent example is the film The Brutalist, in which AI was used to refine Adrien Brody’s Hungarian dialogue to sound more authentic. Such a move that sparked both technical admiration and creative scepticism.

With AI now embedded in everything from voiceovers to entire digital actors, we are only beginning to confront what it truly means when creativity is no longer exclusively human.

Academy Awards 2025, Adrien Brody, The Brutalist, The Oscars, Best Actor
Adrien Brody’s Hungarian dialogue in ‘The Brutalist’ was subject to generative AI to make it sound more authentic. Screenshot / YouTube/ Oscars

Setting the stage: AI in the spotlight

The first major big-screen resurrection occurred in 1994’s The Crow, where Brandon Lee’s sudden passing mid-production forced the studio to rely on body doubles, digital effects, and existing footage to complete his scenes. However, it was not until 2016 that audiences witnessed the first fully digital revival.

In Rogue One: A Star Wars Story, Peter Cushing’s character was brought back to life using a combination of CGI, motion capture, and a facial stand-in. Although primarily reliant on traditional VFX, the project paved the way for future use of deepfakes and AI-assisted performance recreation across movies, TV shows, and video games.

Afterward, some speculated that studios tied to Peter Cushing’s legacy, such as Tyburn Film Productions, could pursue legal action against Disney for reviving his likeness without direct approval. While no lawsuit was filed, questions were raised about who owns a performer’s digital identity after death.

The digital Jedi: How AI helped recreate Luke Skywalker

Fate would have it that AI’s grand debut would take place in a galaxy far, far away, with the surprise appearance of Luke Skywalker in the Season 2 finale of The Mandalorian (spoiler alert). The moment thrilled fans and marked a turning point for the franchise, but it was more than just fan service.

Here’s the twist: Mark Hamill did not record any new voice lines. Instead, actor Max Lloyd-Jones performed the physical role, while Hamill’s de-aged voice was recreated with the help of Respeecher, a Ukrainian company specialising in AI-driven speech synthesis.

Impressed by their work, Disney turned to Respeecher once again, this time to recreate James Earl Jones’s iconic Darth Vader voice for the Obi-Wan Kenobi miniseries. Using archival recordings that Jones signed over for AI use, the system synthesised new dialogue that perfectly matched the intonation and timbre of his original trilogy performances.

Darth Vader, James Earl Jones, Star Wars, Obi-Wan Kenobi, Respeecher, AI voice synthesizer
Screenshot / YouTube / Star Wars

AI in moviemaking: Preserving legacy or crossing a line?

The use of AI to preserve and extend the voices of legendary actors has been met with a mix of admiration and unease. While many have praised the seamless execution and respect shown toward the legacy of both Hamill and Jones, others have raised concerns about consent, creative authenticity, and the long-term implications of allowing AI to perform in place of humans.

In both cases, the actors were directly involved or gave explicit approval, but these high-profile examples may be setting a precedent for a future where that level of control is not guaranteed.

A notable case that drew backlash was the planned use of a fully CGI-generated James Dean in the unreleased film Finding Jack, decades after his death. Critics and fellow actors have voiced strong opposition, arguing that bringing back a performer without their consent reduces them to a brand or asset, rather than honouring them as an artist.

AI in Hollywood: Actors made redundant?

What further heightened concerns among working actors was the launch of Promise, a new Hollywood studio built entirely around generative AI. Backed by wealthy investors, Promise is betting big on Muse, a GenAI tool designed to produce high-quality films and TV series at a fraction of the cost and time required for traditional Hollywood productions.

Filmmaking is a business, after all, and with production budgets ballooning year after year, AI-powered entertainment sounds like a dream come true for profit-driven studios.

Meta’s recent collaboration with Blumhouse Productions on Movie Gen only adds fuel to the fire, signalling that major players are eager to explore a future where storytelling may be driven as much by algorithms as by authentic artistry.

AI in gaming: Automation or artistic collapse?

Speaking of entertainment businesses, we cannot ignore the world’s most popular entertainment medium: gaming. While the pandemic triggered a massive boom in game development and player engagement, the momentum was short-lived.

As profits began to slump in the years that followed, the industry was hit by a wave of layoffs, prompting widespread internal restructuring and forcing publishers to rethink their business models entirely. In hopes of cost-cutting, AAA companies had their eye on AI as their one saving grace.

Nvidia developing AI chips, along with Ubisoft and EA investing in AI and machine learning, have sent clear signals to the industry: automation is no longer just a backend tool, it is a front-facing strategy.

With AI-assisted NPC behaviour and AI voice acting, game development is shifting toward faster, cheaper, and potentially less human-driven production. In response, game developers have become concerned about their future in the industry, and actors are less inclined to sign off their rights for future projects.

AI voice acting in video games

In an attempt to compete with wealthier studios, even indie developers have turned to GenAI to replicate the voices of celebrity voice actors. Tools like ElevenLabs and Altered Studio offer a seemingly straightforward way to get high-quality talent, but if only it were that simple.

Copyright laws and concerns over authenticity remain two of the strongest barriers to the widespread adoption of AI-generated voices. especially as many consumers still view the technology as a crutch rather than a creative tool for game developers.

The legal landscape around AI-generated voices remains murky. In many places, the rights to a person’s voice, or its synthetic clone, are poorly defined, creating loopholes developers can exploit.

AI voice cloning challenges legal boundaries in gaming

The legal ambiguity has fuelled a backlash from voice actors, who argue that their performances are being mimicked without consent or pay. SAG-AFTRA and others began pushing for tighter legal protections in 2023.

A notable flashpoint came in 2025, when Epic Games faced criticism for using an AI-generated Darth Vader voice in Fortnite. SAG-AFTRA filed a formal complaint, citing licensing concerns and a lack of actor involvement.

Not all uses have been controversial. CD Projekt Red recreated the voice of the late Miłogost Reczek in Cyberpunk 2077: Phantom Liberty, with his family’s blessing, thus setting a respectful precedent for the ethical use of AI.

How AI is changing music production and artist Identity

AI is rapidly reshaping music production, with a recent survey showing that nearly 25% of producers are already integrating AI tools into their creative workflows. This shift reflects a growing trend in how technology is influencing composition, mixing, and even vocal performance.

Artists like Imogen Heap are embracing the change with projects like Mogen, an AI version of herself that can create music and interact with fans, blurring the line between human creativity and digital innovation.

Major labels are also experimenting: Universal Music has recently used AI to reimagine Brenda Lee’s 1958 classic in Spanish, preserving the spirit of the original while expanding its cultural reach.

AI and the future of entertainment

As AI becomes more embedded in entertainment, the line between innovation and exploitation grows thinner. What once felt like science fiction is now reshaping the way stories are told, and who gets to tell them.

Whether AI becomes a tool for creative expansion or a threat to human artistry will depend on how the industry and audiences choose to engage with it in the years ahead. As in any business, consumers vote with their wallets, and only time will tell whether AI and authenticity can truly go hand-in-hand.

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The rise of tech giants in healthcare: How AI is reshaping life sciences

Silicon Valley targets health

The intersection of technology and healthcare is rapidly evolving, fuelled by advancements in ΑΙ and driven by major tech companies that are expanding their reach into the life sciences sector.

Once primarily known for consumer electronics or search engines, companies like Google, Amazon, Microsoft, Apple, and IBM are now playing an increasingly central role in transforming the medical field.

These companies, often referred to as ‘Big Tech’, are pushing the boundaries of what was once considered science fiction, using AI to innovate across multiple aspects of healthcare, including diagnostics, treatment, drug development, clinical trials, and patient care.

silicon valley tech companies

AI becomes doctors’ new tool

At the core of this revolution is AI. Over the past decade, AI has evolved from a theoretical tool to a practical and transformative force within healthcare.

Companies are developing advanced machine learning algorithms, cognitive computing models, and AI-powered systems capable of matching—and sometimes surpassing—human capabilities in diagnosing and treating diseases.

AI is also reshaping many aspects of healthcare, from early disease detection to personalised treatments and even drug discovery. This shift is creating a future where AI plays a significant role in diagnosing diseases, developing treatment plans, and improving patient outcomes at scale.

One of the most significant contributions of AI is in diagnostics. Google Health and its subsidiary DeepMind are prime examples of how AI can be used to outperform human experts in certain medical tasks.

For instance, DeepMind’s AI tools have demonstrated the ability to diagnose conditions like breast cancer and lung disease with remarkable accuracy, surpassing the abilities of human radiologists in some cases.

google deepmind AI progress Demis Hassabis

Similarly, Philips has filed patents for AI systems capable of detecting neurodegenerative diseases and tracking disease progression using heart activity and motion sensors.

From diagnosis to documentation

These breakthroughs represent only a small part of how AI is revolutionising diagnostics by improving accuracy, reducing time to diagnosis, and potentially saving lives.

In addition to AI’s diagnostic capabilities, its impact extends to medical documentation, an often-overlooked area that affects clinician efficiency.

Traditionally, doctors spend a significant amount of time on paperwork, reducing the time they can spend with patients.

However, AI companies like Augmedix, DeepScribe, and Nabla are addressing this problem by offering solutions that generate clinical notes directly from doctor-patient conversations.

AI doctor

These platforms integrate with electronic health record (EHR) systems and automate the note-taking process, which reduces administrative workload and frees up clinicians to focus on patient care.

Augmedix, for example, claims to save up to an hour per day for clinicians, while DeepScribe’s AI technology is reportedly more accurate than even GPT-4 for clinical documentation.

Nabla takes this further by offering AI-driven chatbots and decision support tools that enhance clinical workflows and reduce physician burnout.

Portable ultrasounds powered by AI

AI is also transforming medical imaging, a field traditionally dependent on expensive, bulky equipment that requires specialised training.

Innovators like Butterfly Network are developing portable, AI-powered ultrasound devices that can provide diagnostic capabilities at a fraction of the cost of traditional equipment. These devices offer greater accessibility, particularly in regions with limited access to medical imaging technology.

The ability to perform ultrasounds and MRIs in remote areas, using portable devices powered by AI, is democratising healthcare and enabling better diagnostic capabilities in underserved regions.

An advanced drug discovery

In the realm of drug discovery and treatment personalisation, AI is making significant strides. Companies like IBM Watson are at the forefront of using AI to personalise treatment plans by analysing vast amounts of patient data, including medical histories, genetic information, and lifestyle factors.

IBM Watson has been particularly instrumental in the field of oncology, where it assists physicians by recommending tailored cancer treatment protocols.

treatment costs.

A capability like this is made possible by the vast amounts of medical data Watson processes to identify the best treatment options for individual patients, ensuring that therapies are more effective by considering each patient’s unique characteristics.

Smart automation in healthcare

Furthermore, AI is streamlining administrative tasks within healthcare systems, which often burden healthcare providers with repetitive, time-consuming tasks like appointment scheduling, records management, and insurance verification.

By automating these tasks, AI allows healthcare providers to focus more on delivering high-quality care to patients.

Amazon Web Services (AWS), for example, is leveraging its cloud platform to develop machine learning tools that assist healthcare providers in making more effective clinical decisions while improving operational efficiency.

It includes using AI to enhance clinical decision-making, predict patient outcomes, and manage the growing volume of patient data that healthcare systems must process.

Startups and giants drive the healthcare race

Alongside the tech giants, AI-driven startups are also playing a pivotal role in healthcare innovation. Tempus, for example, is integrating genomic sequencing with AI to provide physicians with actionable insights that improve patient outcomes, particularly in cancer treatment.

The fusion of data from multiple sources is enhancing the precision and effectiveness of medical decisions. Zebra Medical Vision, another AI-driven company, is using AI to analyse medical imaging data and detect a wide range of conditions, from liver disease to breast cancer.

Zebra’s AI algorithms are designed to identify conditions often before symptoms even appear, which greatly improves the chances of successful treatment through early detection.

Tech giants are deeply embedded in the healthcare ecosystem, using their advanced capabilities in cloud computing, AI, and data analytics to reshape the industry.

partners handshake ai companies

Microsoft, for example, has made significant strides in AI for accessibility, focusing on creating healthcare solutions that empower individuals with disabilities. Their work is helping to make healthcare more inclusive and accessible for a broader population.

Amazon’s AWS cloud platform is another example of how Big Tech is leveraging its infrastructure to develop machine learning tools that support healthcare providers in delivering more effective care.

M&A meets medicine

In addition to developing their own AI tools, these tech giants have made several high-profile acquisitions to accelerate their healthcare strategies.

Google’s acquisition of Fitbit, Amazon’s purchase of PillPack and One Medical, and Microsoft’s $19.7 billion acquisition of Nuance are all clear examples of how Big Tech is seeking to integrate AI into every aspect of the healthcare value chain, from drug discovery to clinical delivery.

These acquisitions and partnerships also enable tech giants to tap into new areas of the healthcare market and provide more comprehensive, end-to-end solutions to healthcare providers and patients alike.

Smart devices empower health

Consumer health technologies have also surged in popularity, thanks to the broader trend of digital health and wellness tools. Fitness trackers, smartwatches, and mobile health apps allow users to monitor everything from heart rates to sleep quality.

Devices like the Apple Watch and Google’s Fitbit collect health data continuously, providing users with personalised insights into their well-being.

seoul 05 02 2022 male hand with two apple watches with pink and gray strap on white background

Instead of being isolated within individual devices, the data is increasingly being integrated into broader healthcare systems, enabling doctors and other healthcare providers to have a more complete view of a patient’s health.

This integration has also supported the growth of telehealth services, with millions of people now opting for virtual consultations powered by Big Tech infrastructure and AI-powered triage tools.

Chinese hospitals embrace generative AI

The rise of generative AI is also transforming healthcare, particularly in countries like China, where technology is advancing rapidly. Once considered a distant ambition, the use of generative AI in healthcare is now being implemented at scale.

The technology is being used to manage massive drug libraries, assist with complex diagnoses, and replicate expert reasoning processes, which helps doctors make more informed decisions.

At Beijing Hospital of Traditional Chinese Medicine, Ant Group’s medical model has impressed staff by offering diagnostic suggestions and replicating expert reasoning, streamlining consultations without replacing human doctors.

Our choice in a tech-driven world

As AI continues to evolve, tech giants are likely to continue disrupting the healthcare industry while also collaborating with traditional healthcare providers.

While some traditional life sciences companies may feel threatened by the rise of Big Tech in healthcare, those that embrace AI and form partnerships with tech companies will likely be better positioned for success.

The convergence of AI and healthcare is already reshaping the future of medicine, and traditional healthcare players must adapt or risk being left behind.

generate an image of an artificial intelligence head in front of a human head and digital codes in the background reproducing all the human heads inputs and psychological reactions

Despite the tremendous momentum, there are challenges that need to be addressed. Data privacy, regulatory concerns, and the growing dominance of Big Tech in healthcare remain significant hurdles.

If these challenges are addressed responsibly, however, the integration of AI into healthcare could modernise care delivery on a global scale.

Rather than replacing doctors, the goal is to empower them with better tools, insights, and outcomes. The future of healthcare is one where technology and human expertise work in tandem, enhancing the patient experience and improving overall health outcomes.

As human beings, we must understand that the integration of technology across multiple sectors is a double-edged sword. It can either benefit us and help build better future societies, or mark the beginning of our downfall— but in the end, the choice will always be ours.

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Bitcoin’s political puppeteers: From code to clout

Bitcoin was once seen as the cornerstone of a financial utopia — immune to political control, free from traditional banking systems, and governed solely by blockchain protocols. For a while, that dream felt real — and we lived it.

Today, things have changed. The whole crypto market has become increasingly sensitive to political influence, the actions of crypto whales, and rising global tensions.

While financial markets are expected to respond to global developments, Bitcoin’s price volatility has started to reflect something more concerning. Instead of being driven primarily by innovation or organic adoption, BTC price movements are increasingly shaped by media exposure and the strategic trades by influential figures.

In this shifting ecosystem, manipulation and concentrated influence are gradually undermining the core ideals of decentralisation and financial autonomy. Is this really the revolution we were promised? 

Trump’s family growing grip on the crypto market

Donald Trump has not always been a crypto fan. Once critical of Bitcoin, he is now positioning himself as a pro-crypto leader. It is a shift driven by opportunity — not just political, but financial. Trump understands that supporting digital assets could help the USA become a global crypto hub. But it also aligns perfectly with his reputation as a businessman first, politician second. 

The issue lies in the outsized influence his words now have in the crypto space. A single post on social media like X or Truth can send Bitcoin’s price up or down. Whether he is praising crypto or denying personal gain, the market reacts instantly. 

His sons, Donald Trump Jr. and Eric Trump are also active — often promoting the narrative that banks are obsolete and crypto is the future. They frequently make suggestive remarks about market trends. At times, they even imply where investors should put their money — all while staying within legal limits. Still, this pattern subtly steers market sentiment, raising concerns about coordinated influence and the deliberate shaping of market trends.

The launch of politically themed meme coins like $TRUMP and $MELANIA added fuel to the fire. These coins sparked massive rallies — and equally dramatic crashes. In fact, Bitcoin’s all-time high was followed by a sharp fall, partially triggered by the hype and eventual dump around these tokens.

Investigations now suggest insider activity. One wallet made $39 million in just 12 hours after buying $MELANIA before it was even announced. Meanwhile, $TRUMP coin insiders moved $4.6 million in USDC right before the major token unlock.

While technically legal, these actions raise serious ethical concerns. Also, 80% of its supply is controlled by insiders — including Donald Trump himself. It points to a clear pattern of influence, where strategic actions are being used to shape market movements and drive profits for a select few.

What we are seeing is the unprecedented impact of a single family. The combination of political clout and financial ambition is reshaping crypto sentiment, and Bitcoin is reflecting the shift as well. It is no longer subtle — and it is certainly troubling. Crypto is supposed to be free from central influence — yet right now, it bends under the weight of a single name.

Whales and the Michael Saylor effect 

Beyond politics, crypto whales are playing their part in manipulating Bitcoin’s movements. They can cause major price swings by buying or selling in bulk. 

One of the most influential is Michael Saylor, co-founder of Strategy. His company holds approximately 555,450 BTC and is still buying. Every time he announces a new purchase, Bitcoin prices spike. Traders monitor his every move — his tweets are treated like trading signals. 

But Saylor has bigger plans. He once said he could become a Bitcoin bank — a statement that sparked backlash. What is particularly striking is that a businessman who has supported Bitcoin’s decentralised nature from the beginning is now acting in ways that appear to contradict it. Bitcoin was designed to avoid central control — not to be dominated by one player, no matter how bullish. When too much BTC ends up concentrated in one place, the autonomous promise begins to crack. 

Market trust is shifting from code to individuals — and that is risky.

Global tensions as a Bitcoin barometer

Bitcoin does not just respond to tweets anymore. Global tensions have made it a geopolitical asset — a barometer of financial anxiety. 

Recent US tariffs, particularly on Chinese mining equipment, have raised mining costs. Tariffs also disrupted the supply chain for mining rigs, slowing down expansion and affecting hash rates.

At the same time, when the US exempted tech products like iPhones and laptops from tariffs, Bitcoin surged — reaching $86,000. It shows how trade policy and tech pressure are now directly linked to Bitcoin price action. 

Yet, there always seems to be a push-and-pull dynamic at play — not necessarily coordinated, but clearly driven by short-term momentum and opportunistic interests.

It is where irony lies — Bitcoin was built to be apolitical. But today, it is tightly tied to global politics. Its price now swings in response to elections, sanctions, and international conflicts — the very forces it was meant to bypass. What was once a decentralised alternative to traditional finance is becoming a mirror of the same systems it sought to disrupt. 

Bitcoin: from decentralised dream to politically-driven reality 

Bitcoin is no longer moved by natural market fundamentals alone. It dances to the tune of political tweets, whale decisions, and global conflicts. A decentralised dream now faces a centralised reality.

It all started when governments and financial institutions began taking an active interest in Bitcoin and the broader cryptocurrency market. While mainstream adoption was essential for legitimising digital assets, that level of attention came with strings attached — most notably, external influence.

What was once an alternative movement powered by decentralised ideals has gradually attracted the gaze of political leaders, regulators, and corporate giants. The tale of two sides of the sword: the promise of legitimacy, tempered by the risk of losing the system’s independence. 

In this environment, the absence of central control and the self-governing nature of the system are becoming increasingly symbolic. The market reacts not just to algorithms or adoption metrics, but also to the opinions and actions of a powerful few — raising concerns about market manipulation, unequal access, and the long-term health of crypto’s founding vision. Is that really a non-centralised structure?

Crypto was meant to free us from financial gatekeepers. But if Bitcoin can be shaken by one man’s post on a social network, we must ask: can it still considered free? 

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Technological inventions blurring the line between reality and fiction

The rapid progress of AI over the past few years has unsettled the global population, reaching a point where it is extremely difficult to say with certainty whether certain content has been created by AI or not.

We are confronted with this phenomenon through photos, video and audio recordings that can easily confuse us and force us to question our perception of reality.

Digital twins are being used by scammers in the crypto space to impersonate influencers and execute fraudulent schemes.

And while the public often focuses on deepfakes, at the same time we are witnessing inventions and patents emerging around the world that deserve admiration, but also spark important reflection: are we nearing, or have we already crossed, the ethical red line?

For these and many other reasons, in a world where the visual and functional differences between science fiction and reality have almost disappeared, the latest inventions come as a shock.

We are now at a point where we are facing technologies that force us to redefine what we mean by the word ‘reality’.

Neuralink: Crossing the boundary between brain and machine

Amyotrophic lateral sclerosis (ALS) is a rare neurological disease caused by damage and degeneration of motor neurons—nerve cells in the brain and spinal cord. This damage disrupts the transmission of nerve impulses to muscles via peripheral nerves, leading to a progressive loss of muscle function.

However, the Neuralink chip, developed by Elon Musk’s company, has helped one patient type with their mind and speak using their voice. This breakthrough opens the door to a new form of communication where thoughts become direct interactions.

Liquid robot from South Korea

Scenes from sci-fi films are becoming reality, and in this case (thankfully), a liquid robot has a noble purpose—to assist in rescue missions and be applied in medicine.

Currently in the early prototype stage, it has been demonstrated in labs through a collaboration between MIT and Korean research institutes.

ULS exoskeleton as support for elderly care

Healthcare workers and caregivers in China have had their work greatly simplified thanks to the ULS Robotics exoskeleton, weighing only five kilograms but enabling users to lift up to 30 kilograms.

This represents a leap forward in caring for people with limited mobility, while also increasing safety and efficiency. Commercial prototypes have been tested in hospitals and industrial environments.

https://twitter.com/ulsrobotics/status/1317426742168940545

Agrorobots: Autonomous crop spraying

Another example from China that has been in use for several years. Robots equipped with AI perform precise crop spraying. The system analyses pests and targets them without the need for human presence, reducing potential health risks.

The application has become standardised, with expectations for further expansion and improvement in the near future.

The stretchable battery of the future

Researchers in Sweden have developed a flexible battery that can double in length without losing energy, making it ideal for wearable technologies.

Although not yet commercially available, it has been covered in scientific journals. The aim is for it to become a key component in bendable devices, smart clothing and medical implants.

Volonaut Airbike: A sci-fi vehicle takes off

When it comes to innovation, the Volonaut Airbike hits the mark perfectly. Designed to resemble a single-seat speeder bike from Star Wars, it represents a giant leap toward personal air travel.

Functional prototypes exist, but testing remains limited due to high production costs and regulatory hurdles related to traffic laws. Nevertheless, the Polish company behind it remains committed to this idea, and it will be exciting to follow its progress.

NEO robot: The humanoid household assistant

A Norwegian company has been developing a humanoid robot capable of performing household tasks, including gardening chores like collecting and bagging leaves or grass.

These are among the first serious steps toward domestic humanoid assistants. Currently functioning in demo mode, the robot has received backing from OpenAI.

Lenovo Yoga Solar: The laptop that loves sunlight

If you find yourself without a charger but with access to direct sunlight, this laptop will do everything it can to keep you powered. Using solar energy, 20 minutes of charging in sunlight provides around one hour of video playback.

Perfect for ecologists and digital nomads. Although not yet commercially available, it has been showcased at several major tech expos.

https://www.youtube.com/watch?v=px1iEW600Pk

What comes next: The need for smart regulation

As technology races ahead, regulation must catch up. From neurotech to autonomous robots, each innovation raises new questions about privacy, accountability, and ethics.

Governments and tech developers alike must collaborate to ensure that these inventions remain tools for good, not risks to society.

So, what is real and what is generated?

This question will only become harder to answer as time goes on. But on the other hand, if the technological revolution continues to head in a useful and positive direction, perhaps there is little to fear.

The true dilemma in this era of rapid innovation may not be about the tools themselves, but about the fundamental question: Is technology shaping us, or do we still shape it?

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Rewriting the AI playbook: How Meta plans to win through openness

Meta hosted its first-ever LlamaCon, a high-profile developer conference centred around its open-source language models. Timed to coincide with the release of its Q1 earnings, the event showcased Llama 4, Meta’s newest and most powerful open-weight model yet.

The message was clear – Meta wants to lead the next generation of AI on its own terms, and with an open-source edge. Beyond presentations, the conference represented an attempt to reframe Meta’s public image.

Once defined by social media and privacy controversies, Meta is positioning itself as a visionary AI infrastructure company. LlamaCon wasn’t just about a model. It was about a movement Meta wants to lead, with developers, startups, and enterprises as co-builders.

By holding LlamaCon the same week as its earnings call, Meta strategically emphasised that its AI ambitions are not side projects. They are central to the company’s identity, strategy, and investment priorities moving forward. This convergence of messaging signals a bold new chapter in Meta’s evolution.

The rise of Llama: From open-source curiosity to strategic priority

When Meta introduced LLaMA 1 in 2023, the AI community took notice of its open-weight release policy. Unlike OpenAI and Anthropic, Meta allowed researchers and developers to download, fine-tune, and deploy Llama models on their own infrastructure. That decision opened a floodgate of experimentation and grassroots innovation.

Now with Llama 4, the models have matured significantly, featuring better instruction tuning, multilingual capacity, and improved safety guardrails. Meta’s AI researchers have incorporated lessons learned from previous iterations and community feedback, making Llama 4 an update and a strategic inflexion point.

Crucially, Meta is no longer releasing Llama as a research novelty. It is now a platform and stable foundation for third-party tools, enterprise solutions, and Meta’s AI products. That is a turning point, where open-source ideology meets enterprise-grade execution.

Zuckerberg’s bet: AI as the engine of Meta’s next chapter

Mark Zuckerberg has rarely shied away from bold, long-term bets—whether it’s the pivot to mobile in the early 2010s or the more recent metaverse gamble. At LlamaCon, he clarified that AI is now the company’s top priority, surpassing even virtual reality in strategic importance.

He framed Meta as a ‘general-purpose AI company’, focused on both the consumer layer (via chatbots and assistants) and the foundational layer (models and infrastructure). Meta CEO envisions a world where Meta powers both the AI you talk to and the AI your apps are built on—a dual play that rivals Microsoft’s partnership with OpenAI.

This bet comes with risk. Investors are still sceptical about Meta’s ability to turn research breakthroughs into a commercial advantage. But Zuckerberg seems convinced that whoever controls the AI stack—hardware, models, and tooling—will control the next decade of innovation, and Meta intends to be one of those players.

A costly future: Meta’s massive AI infrastructure investment

Meta’s capital expenditure guidance for 2025—$60 to $65 billion—is among the largest in tech history. These funds will be spent primarily on AI training clusters, data centres, and next-gen chips.

That level of spending underscores Meta’s belief that scale is a competitive advantage in the LLM era. Bigger compute means faster training, better fine-tuning, and more responsive inference—especially for billion-parameter models like Llama 4 and beyond.

However, such an investment raises questions about whether Meta can recoup this spending in the short term. Will it build enterprise services, or rely solely on indirect value via engagement and ads? At this point, no monetisation plan is directly tied to Llama—only a vision and the infrastructure to support it.

Economic clouds: Revenue growth vs Wall Street’s expectations

Meta reported an 11% year-over-year increase in revenue in Q1 2025, driven by steady performance across its ad platforms. However, Wall Street reacted negatively, with the company’s stock falling nearly 13% following the earnings report, because investors are worried about the ballooning costs associated with Meta’s AI ambitions.

Despite revenue growth, Meta’s margins are thinning, mainly due to front-loaded investments in infrastructure and R&D. While Meta frames these as essential for long-term dominance in AI, investors are still anchored to short-term profit expectations.

A fundamental tension is at play here – Meta is acting like a venture-stage AI startup with moonshot spending, while being valued as a mature, cash-generating public company. Whether this tension resolves through growth or retrenchment remains to be seen.

Global headwinds: China, tariffs, and the shifting tech supply chain

Beyond internal financial pressures, Meta faces growing external challenges. Trade tensions between the US and China have disrupted the global supply chain for semiconductors, AI chips, and data centre components.

Meta’s international outlook is dimming with tariffs increasing and Chinese advertising revenue falling. That is particularly problematic because Meta’s AI infrastructure relies heavily on global suppliers and fabrication facilities. Any disruption in chip delivery, especially GPUs and custom silicon, could derail its training schedules and deployment timelines.

At the same time, Meta is trying to rebuild its hardware supply chain, including in-house chip design and alternative sourcing from regions like India and Southeast Asia. These moves are defensive but reflect how AI strategy is becoming inseparable from geopolitics.

Llama 4 in context: How it compares to GPT-4 and Gemini

Llama 4 represents a significant leap from Llama 2 and is now comparable to GPT-4 in a range of benchmarks. Early feedback suggests strong performance in logic, multilingual reasoning, and code generation.

However, how it handles tool use, memory, and advanced agentic tasks is still unclear. Compared to Gemini 1.5, Google’s flagship model, Llama 4 may still fall short in certain use cases, especially those requiring long context windows and deep integration with other Google services.

But Llama has one powerful advantage – it’s free to use, modify, and self-host. That makes Llama 4 a compelling option for developers and companies seeking control over their AI stack without paying per-token fees or exposing sensitive data to third parties.

Open source vs closed AI: Strategic gamble or masterstroke?

Meta’s open-weight philosophy differentiates it from rivals, whose models are mainly gated, API-bound, and proprietary. By contrast, Meta freely gives away its most valuable assets, such as weights, training details, and documentation.

Openness drives adoption. It creates ecosystems, accelerates tooling, and builds developer goodwill. Meta’s strategy is to win the AI competition not by charging rent, but by giving others the keys to build on its models. In doing so, it hopes to shape the direction of AI development globally.

Still, there are risks. Open weights can be misused, fine-tuned for malicious purposes, or leaked into products Meta doesn’t control. But Meta is betting that being everywhere is more powerful than being gated. And so far, that bet is paying off—at least in influence, if not yet in revenue.

Can Meta’s open strategy deliver long-term returns?

Meta’s LlamaCon wasn’t just a tech event but a philosophical declaration. In an era where AI power is increasingly concentrated and monetised, Meta chooses a different path based on openness, infrastructure, and community adoption.

The company invests tens of billions of dollars without a clear monetisation model. It is placing a massive bet that open models and proprietary infrastructure can become the dominant framework for AI development.

Meta is facing a major antitrust trial as the FTC argues its Instagram and WhatsApp acquisitions were made to eliminate competition rather than foster innovation.

Meta’s move positions it as the Android of the LLM era—ubiquitous, flexible, and impossible to ignore. The road ahead will be shaped by both technical breakthroughs and external forces—regulation, economics, and geopolitics.

Whether Meta’s open-source gamble proves visionary or reckless, one thing is clear – the AI landscape is no longer just about who has the most innovative model. It’s about who builds the broadest ecosystem.

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Beyond the imitation game: GPT-4.5, the Turing Test, and what comes next

From GPT-4 to 4.5: What has changed and why it matters

In March 2024, OpenAI released GPT-4.5, the latest iteration in its series of large language models (LLMs), pushing the boundaries of what machines can do with language understanding and generation. Building on the strengths of GPT-4, its successor, GPT-4.5, demonstrates improved reasoning capabilities, a more nuanced understanding of context, and smoother, more human-like interactions.

What sets GPT-4.5 apart from its predecessors is that it showcases refined alignment techniques, better memory over longer conversations, and increased control over tone, persona, and factual accuracy. Its ability to maintain coherent, emotionally resonant exchanges over extended dialogue marks a turning point in human-AI communication. These improvements are not just technical — they significantly affect the way we work, communicate, and relate to intelligent systems.

The increasing ability of GPT-4.5 to mimic human behaviour has raised a key question: Can it really fool us into thinking it is one of us? That question has recently been answered — and it has everything to do with the Turing Test.

The Turing Test: Origins, purpose, and modern relevance

In 1950, British mathematician and computer scientist Alan Turing posed a provocative question: ‘Can machines think?’ In his seminal paper ‘Computing Machinery and Intelligence,’ he proposed what would later become known as the Turing Test — a practical way of evaluating a machine’s ability to exhibit intelligent behaviour indistinguishable from that of a human.

In its simplest form, if a human evaluator cannot reliably distinguish between a human’s and a machine’s responses during a conversation, the machine is said to have passed the test. For decades, the Turing Test remained more of a philosophical benchmark than a practical one.

Early chatbots like ELIZA in the 1960s created the illusion of intelligence, but their scripted and shallow interactions fell far short of genuine human-like communication. Many researchers have questioned the test’s relevance as AI progressed, arguing that mimicking conversation is not the same as true understanding or consciousness.

Despite these criticisms, the Turing Test has endured — not as a definitive measure of machine intelligence, but rather as a cultural milestone and public barometer of AI progress. Today, the test has regained prominence with the emergence of models like GPT-4.5, which can hold complex, context-aware, emotionally intelligent conversations. What once seemed like a distant hypothetical is now an active, measurable challenge that GPT-4.5 has, by many accounts, overcome.

How GPT-4.5 fooled the judges: Inside the Turing Test study

In early 2025, a groundbreaking study conducted by researchers at the University of California, San Diego, provided the most substantial evidence yet that an AI could pass the Turing Test. In a controlled experiment involving over 500 participants, multiple conversational agents—including GPT-4.5, Meta’s LLaMa-3.1, and the classic chatbot ELIZA—were evaluated in blind text-based conversations. The participants were tasked with identifying whether they spoke to a human or a machine.

The results were astonishing: GPT-4.5 was judged to be human in 54% to 73% of interactions, depending on the scenario, surpassing the baseline for passing the Turing Test. In some cases, it outperformed actual human participants—who were correctly identified as human only 67% of the time.

That experiment marked the first time a contemporary AI model convincingly passed the Turing Test under rigorous scientific conditions. The study not only demonstrated the model’s technical capabilities—it also raised philosophical and ethical questions.

What does it mean for a machine to be ‘indistinguishable’ from a human? And more importantly, how should society respond to a world where AI can convincingly impersonate us?

Measuring up: GPT-4.5 vs LLaMa-3.1 and ELIZA

While GPT-4.5’s performance in the Turing Test has garnered much attention, its comparison with other models puts things into a clearer perspective. Meta’s LLaMa-3.1, a powerful and widely respected open-source model, also participated in the study.

It was identified as human in approximately 56% of interactions — a strong showing, although it fell just short of the commonly accepted benchmark to define a Turing Test pass. The result highlights how subtle conversational nuance and coherence differences can significantly influence perception.

The study also revisited ELIZA, the pioneering chatbot from the 1960s designed to mimic a psychotherapist. While historically significant, ELIZA’s simplistic, rule-based structure resulted in it being identified as non-human in most cases — around 77%. That stark contrast with modern models demonstrates how far natural language processing has progressed over the past six decades.

The comparative results underscore an important point: success in human-AI interaction today depends on language generation and the ability to adapt the tone, context, and emotional resonance. GPT-4.5’s edge seems to come not from mere fluency but from its ability to emulate the subtle cues of human reasoning and expression — a quality that left many test participants second-guessing whether they were even talking to a machine.

The power of persona: How character shaped perception

One of the most intriguing aspects of the UC San Diego study was how assigning specific personas to AI models significantly influenced participants’ perceptions. When GPT-4.5 was framed as an introverted, geeky 19-year-old college student, it consistently scored higher in being perceived as human than when it had no defined personality.

The seemingly small narrative detail was a powerful psychological cue that shaped how people interpreted its responses. The use of persona added a layer of realism to the conversation.

Slight awkwardness, informal phrasing, or quirky responses were not seen as flaws — they were consistent with the character. Participants were more likely to forgive or overlook certain imperfections if those quirks aligned with the model’s ‘personality’.

That finding reveals how intertwined identity and believability are in human communication, even when the identity is entirely artificial. The strategy also echoes something long known in storytelling and branding: people respond to characters, not just content.

In the context of AI, persona functions as a kind of narrative camouflage — not necessarily to deceive, but to disarm. It helps bridge the uncanny valley by offering users a familiar social framework. And as AI continues to evolve, it is clear that shaping how a model is perceived may be just as important as what the model is actually saying.

Limitations of the Turing Test: Beyond the illusion of intelligence

While passing the Turing Test has long been viewed as a milestone in AI, many experts argue that it is not the definitive measure of machine intelligence. The test focuses on imitation — whether an AI can appear human in conversation — rather than on genuine understanding, reasoning, or consciousness. In that sense, it is more about performance than true cognitive capability.

Critics point out that large language models like GPT-4.5 do not ‘understand’ language in the human sense – they generate text by predicting the most statistically probable next word based on patterns in massive datasets. That allows them to generate impressively coherent responses, but it does not equate to comprehension, self-awareness, or independent thought.

No matter how convincing, the illusion of intelligence is still an illusion — and mistaking it for something more can lead to misplaced trust or overreliance. Despite its symbolic power, the Turing Test was never meant to be the final word on AI.

As AI systems grow increasingly sophisticated, new benchmarks are needed — ones that assess linguistic mimicry, reasoning, ethical decision-making, and robustness in real-world environments. Passing the Turing Test may grab headlines, but the real test of intelligence lies far beyond the ability to talk like us.

Wider implications: Rethinking the role of AI in society

GPT-4.5’s success in the Turing Test does not just mark a technical achievement — it forces us to confront deeper societal questions. If AI can convincingly pass as a human in open conversation, what does that mean for trust, communication, and authenticity in our digital lives?

From customer service bots to AI-generated news anchors, the line between human and machine is blurring — and the implications are far from purely academic. These developments are challenging existing norms in areas such as journalism, education, healthcare, and even online dating.

How do we ensure transparency when AI is involved? Should AI be required to disclose its identity in every interaction? And how do we guard against malicious uses — such as deepfake conversations or synthetic personas designed to manipulate, mislead, or exploit?

 Body Part, Hand, Person, Finger, Smoke Pipe

On a broader level, the emergence of human-sounding AI invites a rethinking of agency and responsibility. If a machine can persuade, sympathise, or influence like a person — who is accountable when things go wrong?

As AI becomes more integrated into the human experience, society must evolve its frameworks not only for regulation and ethics but also for cultural adaptation. GPT-4.5 may have passed the Turing Test, but the test for us, as a society, is just beginning.

What comes next: Human-machine dialogue in the post-Turing era

With GPT-4.5 crossing the Turing threshold, we are no longer asking whether machines can talk like us — we are now asking what that means for how we speak, think, and relate to machines. That moment represents a paradigm shift: from testing the machine’s ability to imitate humans to understanding how humans will adapt to coexist with machines that no longer feel entirely artificial.

Future AI models will likely push this boundary even further — engaging in conversations that are not only coherent but also deeply contextual, emotionally attuned, and morally responsive. The bar for what feels ‘human’ in digital interaction is rising rapidly, and with it comes the need for new social norms, protocols, and perhaps even new literacies.

We will need to learn not only how to talk to machines but how to live with them — as collaborators, counterparts, and, in some cases, as reflections of ourselves. In the post-Turing era, the test is no longer whether machines can fool us — it is whether we can maintain clarity, responsibility, and humanity in a world where the artificial feels increasingly real.

GPT-4.5 may have passed a historic milestone, but the real story is just beginning — not one of machines becoming human, but of humans redefining what it means to be ourselves in dialogue with them.

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Microsoft at 50 – A journey through code, cloud, and AI

The start of a software empire

Microsoft, the American tech giant, was founded 50 years ago, on 4 April 1975, by Harvard dropout Bill Gates and his childhood friend Paul Allen. Since then, the company has evolved from a small startup into the world’s largest software company.

Its early success can be traced back to a pivotal deal in 1975 involving the Altair computer, which inspired the pair to launch the business officially.

That same drive for innovation would later secure Microsoft a breakthrough in 1980 when it partnered with IBM. A collaboration that was supplying the DOS operating system for IBM PCs, a move that turned Microsoft into a household name.

In 1986, Microsoft went public at $21 per share, according to the NASDAQ.  A year later, Gates popped up on the billionaire list, the youngest ever to hold the status at the time, at 31 years old.

Microsoft expands its empire

Throughout the 1980s and 1990s, Microsoft’s dominance in the software industry grew rapidly, particularly with the introduction of Windows 3.0 in 1990, which sold over 60 million copies and solidified the company’s control over the PC software market.

Microsoft, founded 50 years ago by Bill Gates and Paul Allen, evolved from a small startup to the world’s largest software company, revolutionising the tech landscape.

Over the decades, Microsoft has diversified its portfolio far beyond operating systems. Its Productivity and Business Processes division now includes the ever-popular Office Suite, which caters to both commercial and consumer markets, and the business-focused LinkedIn platform.

Equally significant is Microsoft’s Intelligent Cloud segment, led by its Azure Cloud Services, now the second-largest cloud platform globally, which has transformed the way businesses manage computing infrastructure.

The strategic pivot into cloud computing has been complemented by a range of other products, including SQL Server, Windows Server, and Visual Studio.

The giant under scrutiny

The company’s journey has not been without challenges. Its rapid rise in the 1990s attracted regulatory scrutiny, leading to high-profile antitrust cases and significant fines in both the USA and Europe.

Triggered by concerns over Microsoft’s growing dominance in the personal computer market, US regulators launched a series of investigations into whether the company was actively working to stifle competition.

The initial Federal Trade Commission probe was soon picked up by the Department of Justice, which filed formal charges in 1998. At the heart of the case was Microsoft’s practice of bundling its software, mainly Internet Explorer, with the Windows operating system.

 Flag, American Flag

Critics argued that this not only marginalised competitors like Netscape, but also made it difficult for users to install or even access alternative programs.

From Bill Gates to Satya Nadella

Despite these setbacks, Microsoft has continually adapted to the evolving technological landscape. When Steve Ballmer became CEO in 2000, some doubted his leadership, yet Microsoft maintained its stronghold in both business and personal computing.

In the early 2000s, the company overhauled its operating systems under the codename Project Longhorn.

The initiative led to the release of Windows Vista in 2007, which received mixed reactions. However, Windows 7 in 2009 helped Microsoft regain favour, while subsequent updates like Windows 8 and 8.1 aimed to modernise the user experience, especially on tablets.

The transition from Bill Gates to Steve Ballmer, and later to Satya Nadella in 2014, marked a new era of leadership that saw the company’s market capitalisation soar and its focus shift to cloud computing and AI.

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Under Nadella’s stewardship, Microsoft has invested heavily in AI, including a notable $1 billion investment in OpenAI in 2019.

The strategic move, alongside the integration of AI features across its software ecosystem, from Microsoft 365 to Bing and Windows, signals the company’s determination to remain at the forefront of technological innovation.

Microsoft’s push for innovation through major acquisitions and investments

Microsoft has consistently demonstrated its commitment to expanding its technological capabilities and market reach through strategic acquisitions.

In 2011, Microsoft made headlines with its $8.5 billion acquisition of Skype, a move intended to rival Apple’s FaceTime and Google Voice by integrating Skype across Microsoft platforms like Outlook and Xbox.

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Other strategic acquisitions played a significant role in Microsoft’s evolution. The company purchased LinkedIn, Skype, GitHub and Mojang, the studios behind Minecraft. In recent years, the company has made notable investments in key sectors, including cloud infrastructure, cybersecurity, ΑΙ, and gaming.

One of the most significant acquisitions was Inflection AI in 2024. This deal bolstered Microsoft’s efforts to integrate AI into everyday applications. Personal AI tools, essential for both consumers and businesses, enhance productivity and personalisation.

The acquisition strengthens Microsoft’s position in conversational AI, benefiting platforms such as Microsoft 365, Azure AI, and OpenAI’s ChatGPT, which Microsoft heavily supports.

By enhancing its capabilities in natural language processing and user interaction, this acquisition allows Microsoft to offer more intuitive and personalised AI solutions, helping it compete with companies like Google and Meta.

Microsoft acquires Fungible and Lumenisity for cloud innovation

In a strategic push to enhance its cloud infrastructure, Microsoft has made notable acquisitions in recent years, including Fungible and Lumenisity.

In January 2023, Microsoft acquired Fungible for $190 million. Fungible specialises in data processing units (DPUs), which are crucial for optimising tasks like network routing, security, and workload management.

By integrating Fungible’s technology, Microsoft enhances the operational efficiency of its Azure data centres, cutting costs and energy consumption while offering more cost-effective solutions to enterprise customers. This move positions Microsoft to capitalise on the growing demand for robust cloud services.

Similarly, in December 2022, Microsoft acquired Lumenisity, a company known for its advanced fibre optic technology. Lumenisity’s innovations boost network speed and efficiency, making it ideal for handling high volumes of data traffic.

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The move has strengthened Azure’s network infrastructure, improving data transfer speeds and reducing latency, particularly important for areas like the Internet of Things (IoT) and AI-driven workloads that require reliable, high-performance connectivity.

Together, these acquisitions reflect Microsoft’s ongoing commitment to innovation in cloud services and technology infrastructure.

Microsoft expands cybersecurity capabilities with Miburo acquisition

Microsoft has also announced its agreement to acquire Miburo, a leading expert in cyber intelligence and foreign threat analysis. This acquisition further strengthens Microsoft’s commitment to enhancing its cybersecurity solutions and threat detection capabilities.

Miburo, known for its expertise in identifying state-sponsored cyber threats and disinformation campaigns, will be integrated into Microsoft’s Customer Security and Trust organisation.

The acquisition will bolster Microsoft’s existing threat detection platforms, enabling the company to better address emerging cyber threats and state-sanctioned information operations.

Miburo’s analysts will work closely with Microsoft’s Threat Intelligence Center, data scientists, and other security teams to expand the company’s ability to counter complex cyber-attacks and the use of information operations by foreign actors.

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Miburo’s mission to protect democracies and ensure the integrity of information environments aligns closely with Microsoft’s goals of safeguarding its customers against malign influences and extremism.

A strategic move that further solidifies Microsoft’s position as a leader in cybersecurity and reinforces its ongoing investment in addressing evolving global security challenges.

Microsoft’s $68.7 billion Activision Blizzard acquisition boosts gaming and the metaverse

Perhaps the most ambitious acquisition in recent years was Activision Blizzard, which Microsoft acquired for $68.7 billion in 2022.

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With this purchase, Microsoft significantly expanded its presence in the gaming industry, integrating popular franchises like Call of Duty, World of Warcraft, and Candy Crush into its Xbox ecosystem.

The acquisition not only enhances Xbox’s competitiveness against Sony’s PlayStation but also positions Microsoft as a leader in the metaverse, using gaming as a gateway to immersive digital experiences.

This deal reflects the broader transformation in the gaming industry driven by cloud gaming, virtual reality, and blockchain technology.

A greener future: Microsoft’s sustainability goals

Another crucial element of the company’s business strategy is its dedication to sustainability, which will serve as the foundation of its operations and future objectives.

Microsoft has set ambitious targets to become carbon negative and water positive and achieve zero waste by 2030 while protecting ecosystems.

With a vast global presence spanning over 60 data centre regions, Microsoft leverages its cloud computing infrastructure to optimise both performance and sustainability.

The company’s approach focuses on integrating efficiency into every aspect of its infrastructure, from data centres to custom-built servers and silicon.

A key strategy in Microsoft’s sustainability efforts is its Power Purchase Agreements (PPAs), which aim to bring more carbon-free electricity to the grids where the company operates.

By securing over 34 gigawatts of renewable energy across 24 countries, Microsoft is not only advancing its own sustainability goals but also supporting the global transition to clean energy.

Microsoft plans major investment in AI infrastructure

Microsoft has also announced plans to invest $80 billion in building data centres designed to support AI workloads by the end of 2025. A significant portion of this investment, more than half, will be directed towards the USA.

As AI technology continues to grow, Microsoft’s spending includes billions on Nvidia graphics processing units (GPUs) to train AI models.

The rapid rise of OpenAI’s ChatGPT, launched in late 2022, has sparked a race among tech companies to develop their own generative AI models.

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Having invested more than $13 billion in OpenAI, Microsoft has integrated its AI models into popular products such as Windows and Teams, while also expanding its cloud services through Azure.

Microsoft’s growth strategy shapes the future of tech innovation

All these acquisitions and investments reflect a cohesive strategy aimed at enhancing Microsoft’s leadership in key technology areas.

From AI and gaming to cybersecurity and cloud infrastructure, the company is positioning itself at the forefront of digital transformation. However, while these deals present significant growth opportunities, they also pose challenges.

Ensuring successful integration, managing regulatory scrutiny, and creating synergies between acquired entities will be key to Microsoft’s long-term success. In conclusion, Microsoft’s strategy highlights its dedication to innovation and technology leadership.

From its humble beginnings converting BASIC for Altair to its current status as a leader in cloud and AI, Microsoft’s story is one of constant reinvention and enduring influence in the digital age.

By diversifying across multiple sectors, including gaming, cloud computing, AI, and cybersecurity, the company is building a robust foundation for future growth.

A digital business model that not only reinforces Microsoft’s market position but also plays a vital role in shaping the future of technology.

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