UN’s Independent International Scientific Panel on AI has begun work on a global study examining how AI is reshaping economies and societies. The 40-member panel aims to assess AI’s risks and opportunities, with a focus on maintaining human oversight in decision-making.
Human-centred design stands at the core of the panel’s approach. Members are exploring how AI can complement rather than replace human capabilities, an idea often described as ‘augmented intelligence’.
Research will examine impacts across key sectors, including labour markets and healthcare, while also addressing inclusivity challenges such as language diversity and access to digital infrastructure.
Concerns over trust, ethics and accountability are driving the initiative. Warnings from UN leadership have highlighted the dangers of unregulated AI, reinforcing the need for governance frameworks that reflect social and human rights principles.
Proposals under consideration include tools such as AI watermarking to improve transparency and distinguish between human and machine-generated content.
Findings from the study are expected to inform global policy discussions, with a first report scheduled for presentation at an international dialogue on AI governance in Geneva. Long-term outcomes will depend on aligning technological innovation with ethical safeguards and inclusive development goals.
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Canada and Finland have issued a joint statement setting out a new phase of bilateral cooperation focused on Arctic and maritime issues, defence and resilience, and advanced technologies, including sovereign technology, AI, quantum computing, and high-performance computing.
The statement says the two countries met in Ottawa to advance bilateral cooperation amid strategic competition and an emerging international order.
On technology, the statement welcomes a Canada–Finland joint statement on sovereign technology and AI cooperation, aimed at expanding collaboration on advanced technologies that deliver shared economic benefits.
It also says the two countries will deepen coordination to strengthen sovereign technology, grow capacity, and reduce dependencies in what it describes as an increasingly contested digital landscape. Finland’s participation in the Sovereign Technology Alliance is also to be explored.
The two governments also say they will collaborate on research and innovation in high-performance computing and AI, including support for AI adoption across industry and government and the identification of investment opportunities for small and medium-sized enterprises.
The statement adds that they will continue cooperation on network communication technologies that will underpin sovereign AI infrastructure and promote opportunities for their telecommunications industries through multilateral initiatives, including the Global Coalition on Telecommunications.
The text also refers to AI gigafactories, facilities designed to provide the computing power needed to develop, train, and deploy advanced AI models and applications. In that context, it welcomes the longstanding cooperation between Export Development Canada and Nokia and notes a memorandum of understanding signed this week to support Nokia’s efforts to build AI gigafactories.
Beyond AI, the statement says Canada and Finland will explore cooperation in quantum research, innovation, commercialisation, and workforce development, including through a Canadian quantum trade mission to Finland. It also links bilateral technology cooperation to critical minerals, trusted supply chains, and wider economic and security cooperation.
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ARTICLE 19, alongside more than 40 civil society organisations, has raised concerns about proposed changes to the European Union AI Act under the so-called AI Omnibus package. The groups argue the revisions could weaken existing protections.
According to ARTICLE 19, the proposal risks reducing safeguards for people affected by high-risk AI systems, including areas such as biometric identification and education. The organisations say the changes could leave individuals without adequate protection.
The publication also criticises the legislative process, stating that the European Commission did not follow standard procedures such as impact assessments or public consultation. This raises concerns about transparency and accountability in the legislative process.
ARTICLE 19 is calling on the European Union‘s institutions to restore key safeguards, particularly transparency requirements and oversight powers, to ensure fundamental rights are protected across the European Union.
This contrasts with representatives of leading industry businesses, who call for more relaxed AI Act rules so as to ensure the EU businesses remain competitive. This highlights a shared struggle between innovation and legislation.
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The Nigeria Customs Service has begun a capacity development programme focused on AI-driven processes, according to an official social media post. The initiative aims to strengthen operational efficiency in key areas.
The Nigeria Customs Service stated that the training covers revenue generation, remittances and reconciliation processes. AI tools are being introduced to improve accuracy and streamline financial operations.
The programme is part of broader efforts to enhance technical skills within the service and align operations with evolving digital practices. It reflects a focus on improving internal systems and data management.
The Nigeria Customs Service positions the initiative as a step towards modernising customs processes and strengthening institutional capacity in Nigeria.
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The UK Ministry of Justice, alongside HM Courts & Tribunals Service, has launched a study examining how AI can be used to generate court transcripts more efficiently.
The initiative aims to reduce the cost and time required for accessing official court records.
Currently, transcript fees can be prohibitively expensive, limiting access for victims seeking clarity on court proceedings. The proposed use of AI-based systems, including in-house tools such as Justice Transcribe, could lower these barriers while maintaining required accuracy standards.
The policy forms part of broader efforts in the UK to modernise the justice system and enhance transparency. It aligns with legislative developments, including the Victims and Courts Bill, and plans to provide free access to sentencing remarks in Crown Court cases from 2027.
By improving access to legal records, the initiative seeks to strengthen accountability and support victims’ understanding of judicial processes, contributing to a more accessible and responsive justice system.
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The Ministry of Land, Infrastructure and Transport in South Korea has selected six pilot projects under the K-City Network Global Cooperation Program to deploy AI-based smart city models across Southeast Asia.
The initiative reflects efforts to extend tested domestic systems into international urban contexts.
Projects will be implemented in Brunei, Bacoor, Ho Chi Minh City, Can Tho, Surin and Penang, focusing on areas such as traffic optimisation, water management and disaster response. These pilots aim to assess the adaptability and performance of AI-enabled infrastructure in diverse environments.
The programme operates as a government-to-government cooperation mechanism, combining technical deployment with policy coordination. Selected projects were evaluated based on innovation, feasibility and potential for broader regional application.
By testing AI-driven urban systems in partner countries, the initiative by South Korea seeks to support digital transformation while contributing to more efficient, resilient and data-driven public services.
It also reflects wider trends in cross-border collaboration on smart city governance and infrastructure development.
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The Ministry of Foreign Affairs of the Republic of Azerbaijan has highlighted the growing role of AI and digital technologies in diplomacy, according to an official publication. The discussion reflects wider efforts to modernise diplomatic practices.
The Ministry of Foreign Affairs of the Republic of Azerbaijan emphasised that digital tools are increasingly shaping communication, policy coordination and international engagement. AI is seen as part of this evolving diplomatic environment.
The publication underlines the importance of adapting institutional frameworks and skills to keep pace with technological changes such as AI developments. This includes strengthening digital capabilities within diplomatic services.
The Ministry of Foreign Affairs of the Republic of Azerbaijan presents these developments as part of broader efforts to integrate digital innovation into foreign policy in Azerbaijan.
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The European Investment Fund (EIF) will manage a €210 million financing initiative to support high-tech businesses in Bulgaria, focusing on sectors such as AI, microelectronics and advanced technologies.
The programme operates within the JEREMIE Bulgaria framework, which aims to improve access to capital for small and medium-sized enterprises.
An initiative that reflects a broader EU strategy to strengthen innovation capacity and support sustainable economic growth through targeted investment mechanisms.
The EIF, a subsidiary of the EIB Group, will prioritise equity financing and scale-up support to address structural gaps that often limit the expansion of high-growth companies within national markets.
A programme that also aligns with wider efforts to retain technological talent and reduce reliance on external capital by reinforcing domestic innovation ecosystems.
By supporting dual-use technologies and strategic sectors, the measure contributes to both economic competitiveness and technological resilience.
Through its revolving funding model, reinvested capital is expected to sustain long-term financing capacity, reinforcing the position of Bulgaria within regional venture capital networks and supporting the development of a more mature innovation economy.
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A global AI governance initiative jointly drafted by 16 organisations, including the Chinese Association for AI, has been released under the organisation of the China Science and Technology Policy Research Association.
According to the text, the initiative calls for an open, fair, inclusive, and effective global AI governance system. Its main elements include ensuring benefits and improving livelihoods, maintaining security and preventing risks, upholding fairness, promoting balanced development, encouraging exchange and mutual learning, and building consensus.
Speakers cited in the release said rapid advances in AI are creating governance pressures that existing frameworks struggle to address. Liang Zheng, deputy secretary-general of the China Institute for Science and Technology Policy and director of the Institute for AI International Governance at Tsinghua University, said governance is not keeping pace with technological development and pointed to widening capability gaps between countries, as well as difficulties in building broader governance consensus.
The text also highlights risks linked to newer AI systems and agents. Cui Yong, a full professor at Tsinghua University, deputy director of the Network Technology Institute, council member of the China Communications Standards Association, and co-chair of the Internet Engineering Task Force Softwire Working Group on IPv6 transition, said AI agents are raising new governance concerns.
Yong said those concerns include responsibility for autonomous machine decision-making, the use of agents in crimes, including telecom fraud, and cross-border data leakage and privacy infringements linked to multi-agent interconnection.
The initiative is presented as drawing on the professional, neutral, and cross-border role of science and technology associations. The release says such bodies can help support evidence-based rulemaking, international exchange, participation in standard-setting, and talent development across both technical and governance fields.
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Every technological leap forces society to renegotiate its relationship with power. Intelligence, once a uniquely human advantage, is now being abstracted, scaled, and embedded into machines. As AI evolves from a tool into an autonomous force shaping economies and institutions, the question is no longer what AI can do, but who it will ultimately serve.
A new framework published by OpenAI sets out a vision for managing the transition towards advanced AI systems, often described as superintelligence. Framed as a policy agenda for governments and institutions, it attempts to define how societies should respond to rapid advances in AI governance, economic transformation, and workforce disruption.
At its core, the document is not a regulation but influence: an attempt to shape how policymakers think about industrial policy for AI, productivity gains, and the redistribution of technological power.
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AI industrial policy and the next economic transformation
The central argument is that AI will act as a general-purpose technology comparable to electricity or the combustion engine. It promises higher productivity, lower costs, and accelerated innovation across industries. In policy terms, this aligns with broader discussions around AI-driven productivity growth and economic restructuring.
However, historical precedent suggests that such transitions are rarely evenly distributed. Industrial revolutions typically begin with labour displacement, rising inequality, and capital concentration, before broader gains are realised. AI may intensify this dynamic due to its dependence on compute infrastructure, proprietary models, and large-scale data ecosystems.
Economic power may become increasingly concentrated among a small number of AI developers and infrastructure providers, posing a structural risk of reinforcing existing inequalities rather than reducing them.
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The return of industrial policy in the AI economy
A key feature of the document is its explicit endorsement of AI industrial policy as a necessary response to market limitations. Governments, it argues, must play a more active role in shaping outcomes through regulation, investment, and public-private coordination.
A broader global shift in economic thinking is reflected in this approach. Strategic sectors such as semiconductors, energy, and digital infrastructure are already experiencing increased state intervention. AI now joins that category as a critical technology.
Yet this approach introduces a significant tension. When leading AI firms contribute directly to the design of AI regulation and governance frameworks, the risk of regulatory capture increases. Policies intended to ensure fairness and safety may inadvertently reinforce the dominance of incumbent companies by raising compliance costs and technical barriers for smaller competitors.
In this sense, AI industrial policy may not only guide innovation but also determine market entry, competition, and the long-term economic structure.
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Redistribution, taxation, and the question of AI wealth
The document places strong emphasis on economic inclusion in the AI economy, proposing mechanisms such as a public wealth fund, AI taxation, and expanded access to capital markets. These ideas are designed to address one of the central challenges of AI-driven growth: the potential for extreme wealth concentration.
As AI systems increase productivity while reducing reliance on human labour, traditional tax bases such as wages and payroll contributions may weaken. The proposal to tax AI-generated profits or automated labour reflects an attempt to stabilise public finances in an increasingly automated economy.
Equally significant is the idea of a ‘right to AI’, which frames access to AI as a foundational requirement for participation in modern economic life. This positions AI not merely as a tool, but as a form of digital infrastructure essential to economic agency and inclusion.
However, these proposals face major implementation challenges. Measuring AI-generated value is complex, particularly in hybrid systems where human and machine inputs are deeply integrated. Without clear definitions, AI taxation frameworks and redistribution mechanisms could prove difficult to enforce at scale.
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Workforce disruption and the future of work
The document recognises that AI will significantly reshape labour markets. Many tasks that currently require hours of human effort are already being automated, with future systems expected to handle more complex, multi-step workflows.
To manage this transition, the proposal highlights reskilling programmes, portable benefits systems, and adaptive social safety nets, alongside experimental ideas such as a reduced working week. These measures aim to mitigate the impact of automation and workforce disruption while maintaining economic stability.
However, the pace of change introduces uncertainty. Historically, labour markets have adjusted over decades, allowing new roles to emerge gradually. AI-driven disruption may occur much faster, compressing adjustment periods and increasing transitional risk.
While the document highlights expansion in sectors such as healthcare, education, and care services, these ‘human-centred jobs’ require substantial investment in training, wages, and institutional support to absorb displaced workers effectively.
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AI safety, governance, and systemic control
Beyond economic considerations, the proposal places a strong emphasis on AI safety, auditing frameworks, and risk mitigation systems. The proposed measures include model evaluation standards, incident reporting mechanisms, and international coordination structures.
These safeguards respond to growing concerns around cybersecurity risks, biosecurity threats, and systemic model misalignment. As AI systems become more autonomous and embedded in critical infrastructure, governance mechanisms must evolve accordingly.
However, safety frameworks also introduce questions of control. Determining which systems are classified as high-risk inevitably centralises authority within regulatory and institutional bodies. In practice, this may restrict access to advanced AI systems to organisations capable of meeting stringent compliance requirements.
A structural trade-off between security and openness is emerging in the AI economy, raising questions about how innovation and oversight can coexist without reinforcing centralisation.
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Strategic influence and the future of AI governance
The proposal from OpenAI is both policy-oriented and strategically positioned. It acknowledges legitimate risks- inequality, labour disruption, and systemic instability, while offering a roadmap for managing them through structured intervention.
At the same time, it reflects the perspective of a leading actor in the AI industry. As a result, its recommendations exist at the intersection of public interest and commercial strategy. The dual role raises important questions about who defines AI governance frameworks and how economic power is distributed in the intelligence age.
The broader challenge is not only technological but also institutional: ensuring that AI industrial policy, regulation, ethics and economic design are shaped through transparent and democratic processes, rather than through concentrated private influence.
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AI industrial policy will define economic power
AI is no longer solely a technological development- it is a structural force reshaping global economic systems. The emergence of AI industrial policy frameworks reflects an attempt to manage this transformation proactively rather than reactively.
The success or failure of these approaches will determine whether AI-driven growth leads to broader prosperity or deeper concentration of wealth and power. Without effective governance, the risks of inequality and centralisation are significant. With carefully designed policies, there is real potential to expand access, improve productivity, and distribute benefits more widely.
Digital diplomacy may increasingly come to the fore as a mechanism for arbitrating competing approaches to AI policy and governance across jurisdictions. As regulatory frameworks diverge, diplomatic channels could serve to bridge gaps, negotiate standards, and balance strategic interests, positioning digital diplomacy as a practical tool for managing fragmentation in the evolving AI economy.
Ultimately, the intelligence age will not be defined by technology alone, but by the AI governance systems, economic frameworks, and industrial policy decisions that guide its development. The outcome will depend on the extent to which global stakeholders succeed in building a shared and coordinated vision for its future.
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