WSIS Forum 2026 explores how the IGF should evolve after gaining a permanent mandate

The future of the Internet Governance Forum (IGF) took centre stage at the WSIS Forum 2026, where policymakers, former diplomats, technical experts and internet governance practitioners discussed how the forum should evolve following the UN’s decision to grant it a permanent mandate.

Speakers agreed that the challenge is no longer whether the IGF should continue, but how it can become more relevant, effective and responsive to emerging issues such as AI while preserving its multistakeholder character. The discussion focused on four broad priorities, such as strengthening government participation, improving intersessional work, deepening links with national and regional IGF initiatives (NRIs), and ensuring the forum has sufficient institutional capacity and sustainable funding.

Governments need a stronger role without changing the IGF’s character

A recurring theme was how to increase meaningful government participation without transforming the IGF into a traditional intergovernmental negotiation forum.

Anriette Esterhuysen, human rights defender and computer networking pioneer from South Africa, argued that governments must participate more actively, particularly to strengthen digital policymaking in developing countries, but warned against reducing their involvement to formal speeches by senior officials.

Instead, she said governments should engage openly on practical policy challenges that require collaboration with the wider internet governance community.

Former Latvian ambassador Janis Karklins echoed this view, arguing that governments would only dedicate time and resources to the IGF if it addressed issues directly relevant to their national priorities.

Planning for the upcoming IGF in Nairobi, he suggested, should take into account the policy needs of African governments to ensure the forum delivers practical value.

Jennifer Chung, Chair of the Multistakeholder Advisory Group (MAG), also stressed that the initiative should be understood as a ‘government dialogue with stakeholders’ rather than a separate government track, preserving the IGF’s long-standing multistakeholder model.

Meanwhile, IGF Programme and Technology Manager Chengetai Masango said discussions on the exact format remain ongoing, with organisers considering how the dialogue could build on existing high-level sessions rather than creating an entirely new structure.

Stronger outcomes through year-round collaboration

Participants also debated how the IGF could produce more tangible results while remaining a platform for dialogue rather than negotiations.

Konstantinos Komaitis opened the discussion by asking how the IGF could move beyond its reputation as a ‘talking shop’ without becoming another UN negotiating process.

Esterhuysen argued that achieving greater impact requires changing the way the IGF works rather than changing its mandate. She suggested more structured intersessional work, thematic synthesis and longer-term collaboration on priority issues instead of relying primarily on standalone workshops during the annual meeting.

Andrea Calderaro, Director of Cyber Diplomacy at the EU Institute for Security Studies (EUISS), similarly argued that the most valuable work happens between annual IGF meetings, with governments and stakeholders conducting national consultations and bringing those experiences into global discussions.

Masango defended dialogue as the forum’s core purpose, but agreed that stronger follow-up and more practical outputs are needed. He said previous initiatives, including voluntary commitments, had not always been sufficiently tracked or incorporated into future work.

National and regional IGFs seen as a growing strength

Speakers also highlighted the growing importance of national, regional and youth Internet Governance Forums, which now number more than 180 worldwide.

Esterhuysen welcomed their explicit recognition in the WSIS+20 outcome document, describing them as one of the IGF’s greatest successes.

Chung said the relationship between the global IGF and NRIs should evolve beyond annual event coordination towards continuous thematic collaboration and shared learning throughout the year.

She noted particularly strong growth among youth initiatives, especially in Africa and Asia, arguing that younger participants increasingly want meaningful involvement in shaping Internet governance discussions rather than symbolic participation.

Esterhuysen proposed a two-way model in which the global IGF identifies concrete policy questions, NRIs and intersessional groups examine them throughout the year, and the Secretariat synthesises the results into practical, non-negotiated policy options for governments and other stakeholders.

Permanent mandate brings new expectations

The discussion also touched on longer-term institutional questions, including funding and Secretariat capacity.

Although speakers acknowledged that financial sustainability remains an important challenge, they agreed that the immediate priority is preparing a successful IGF meeting in Nairobi while gradually implementing reforms in the years ahead.

Calderaro argued that the IGF should increasingly serve as a hub connecting the growing number of international digital governance processes rather than functioning only as an annual conference.

Esterhuysen also urged the forum to become more willing to address politically sensitive issues, including corporate accountability, arguing that its permanent mandate provides an opportunity to take on more substantive policy debates.

Closing the session, participants broadly agreed that the IGF’s future lies not in becoming a negotiating body, but in strengthening dialogue, improving policy-relevant outputs, deepening collaboration across national and regional initiatives, and ensuring governments, civil society, academia, the private sector and technical communities remain equally engaged as internet governance continues to evolve.

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Stronger health data governance seen as key to trusted AI and digital health at WSIS Forum 2026

Strong legislative frameworks for health data governance are becoming essential to ensure that AI and digital health technologies remain trustworthy, equitable and rights-based, speakers said during a session at the WSIS Forum 2026.

The discussion brought together representatives from governments, international organisations, civil society and the private sector, who agreed that while AI and digital technologies are transforming healthcare, governance frameworks have not always kept pace. Speakers repeatedly argued that stronger legislation, greater international coordination and broader stakeholder participation will be necessary to build public trust and enable responsible data sharing across borders.

The session formed part of the WSIS Forum 2026, held in Geneva from 6 to 10 July. Co-organised by the International Telecommunication Union (ITU), UNESCO, UNDP and UNCTAD together with more than 50 UN organisations, the forum serves as one of the UN’s principal multistakeholder platforms for digital cooperation and sustainable development.

Trust begins with governance

Opening the discussion, Mathilde Forslund of Transform Health argued that health data has become the foundation of modern healthcare, powering everything from patient care and disease surveillance to AI innovation and health system planning.

However, she stressed that technological progress alone is insufficient.

‘Digital technologies and AI are transforming health systems rapidly, but these benefits will only be realised equitably and responsibly if governance keeps pace and public trust is maintained,’ she said.

Forslund argued that trusted governance requires legislation grounded in human rights, transparency and equity, alongside inclusive decision-making that informs citizens how their health data is collected, shared and protected. She also called for stronger national legal frameworks governing both health data and AI while encouraging greater regional and international alignment to prevent fragmented rules from undermining interoperability and cross-border cooperation.

Rather than starting from scratch, she noted that countries can already build on existing resources, including Transform Health’s Health Data Governance Principles, WHO guidance on AI, OECD recommendations and emerging regional initiatives such as the European Health Data Space (EHDS) and the Africa CDC’s work on continental health data governance.

National legislation provides legal certainty

Drawing on Zambia’s experience, Andrew Kashoka, Director of Information Technology at the Ministry of Health of Zambia, explained that governments increasingly recognise the need for legal certainty as digital health systems expand.

He argued that while policies and strategies provide direction, legislation ultimately establishes enforceable rights and obligations governing consent, privacy, accountability and access to health data.

‘Technology moves faster than policy and policy moves faster than legislation,’ Kashoka observed.

He described Zambia’s National Digital Health Strategy and the country’s participation in the WHO Global Initiative on Digital Health (GUIDE), noting that electronic health records, digital public infrastructure and AI all require strong legal foundations to maintain public confidence.

Kashoka also highlighted the Africa CDC’s continental health data governance framework, saying it provides African countries with shared principles that support legal interoperability, trusted cross-border collaboration, regional disease surveillance and responsible AI innovation.

Coordination, not policy, remains the biggest challenge

Several speakers suggested that governance challenges stem less from the absence of policies than from fragmented implementation.

Linda Bonyo, Founder of the Lawyers Hub and the Africa AI Policy Lab, argued that numerous organisations are already developing health data and AI governance initiatives, but often work independently with limited coordination.

She criticised the exclusion of parliaments and judicial institutions from governance discussions, arguing that legislators and courts play essential roles in creating and interpreting legal frameworks.

Bonyo also called for stronger institutional capacity, particularly among national data protection authorities that increasingly find themselves overseeing AI without sufficient technical expertise or financial resources.

She further highlighted practical barriers limiting African participation in international governance discussions, including visa restrictions and the high cost of attending Geneva-based meetings.

Summarising the challenge, Bonyo remarked that the problem is ‘not a policy problem… it’s implementation,’ urging countries to develop governance frameworks rooted in local realities rather than simply adopting foreign regulatory models.

Private sector and technical standards also matter

Representing the technical and private-sector perspective, Simão Ferraz de Campos Neto, Senior Counsellor at the International Telecommunication Union (ITU), argued that clearer rules and common technical standards are essential if health data is to be shared safely without discouraging innovation.

He noted that organisations frequently hesitate to share data not because they oppose collaboration, but because legal uncertainty creates concerns about liability.

Campos Neto called for interoperable technical standards, machine-readable datasets and standardised data-sharing agreements that could make trusted health data exchange significantly easier.

He also cautioned against treating AI as a single technology requiring uniform regulation.

Instead, he advocated proportionate, risk-based regulation that reflects the diversity of AI applications, while avoiding excessive regulatory burdens that could slow innovation.

Momentum builds towards global action

Closing the discussion, Jamal Alshanfari, Ambassador and Head of Oman Health office in Geneva, pointed to growing political momentum following discussions at the World Health Assembly, where member states expressed broad support for developing stronger global health data governance arrangements.

He identified four priorities for the next phase of work. The phases are expanding international consensus, strengthening national legislation and institutional capacity, providing practical implementation guidance, and ensuring that governments, civil society, academia, industry and end users all participate in shaping future frameworks.

Alshanfari also reminded participants that governance discussions should ultimately focus on those most affected by digital health technologies.

‘Everybody forgets about the end user,’ he said, stressing that trust depends on governance frameworks serving citizens as much as institutions.

In her closing remarks, Forslund said the discussion demonstrated encouraging progress across national, regional and global initiatives, while acknowledging that implementation remains the greatest challenge. She pointed to the upcoming World Health Assembly as an important opportunity to advance work on a possible global resolution on health data governance.

The session concluded with broad agreement that trusted AI in healthcare will depend not only on technological innovation but also on stronger legislation, greater international coordination, practical implementation, and governance frameworks that place citizens’ rights and public trust at their centre.

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South Korea funds AI environmental technology commercialisation

South Korea will invest about 41 billion won by 2027 to support the rapid commercialisation of AI-powered environmental products and services.

The Ministry of Climate, Energy and Environment and the Korea Environmental Industry & Technology Institute selected 17 companies for the programme from 145 project proposals.

The projects cover five areas: carbon neutrality, water management, resource circulation, environmental safety and weather and climate monitoring.

Selected initiatives include an AI system that integrates solar power, energy storage and heat pumps to reduce heating and cooling costs by more than 20% compared with existing systems.

Another project will use AI to analyse ageing and fatigue in water supply networks, detect early signs of abnormality, and help prevent sinkholes and other disasters.

In the environmental safety field, selected companies will develop systems that combine CCTV and sensor data to predict and detect indoor air pollution and fire smoke, aiming to reduce exposure time to harmful substances.

The ministry said 16 of the 17 selected companies are small and medium-sized enterprises, while nine are located outside the Seoul metropolitan area.

Officials said the programme aims to bring AI-based environmental products and services to market within one to two years, while supporting domestic innovation and potential overseas expansion.

Why does it matter?

The programme shows how AI is being used as a deployment tool for environmental policy, rather than only as a research technology. Applications such as building energy optimisation, water-infrastructure monitoring and pollution detection can produce practical benefits if they move quickly from pilot stage to commercial use. The focus on SMEs and firms outside the Seoul metropolitan area also links AI innovation to regional development and to the export potential of environmental technology.

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OECD proposes policy priorities for AI use in SME sustainable finance

The Organisation for Economic Co-operation and Development (OECD) has published a policy paper examining how AI and digital tools can help small and medium-sized enterprises (SMEs) gain better access to sustainable finance, where they remain significantly underrepresented.

The paper maps practical applications of AI and digital tools across the entire financing lifecycle, from sustainability data generation and reporting by SMEs to loan origination, credit assessment and portfolio monitoring by financial institutions. The OECD notes that AI has the potential to support the front, middle and back office of lending operations rather than a single stage of the financing process.

Drawing on country examples and recent initiatives, the OECD argues that technological adoption must be accompanied by appropriate governance. It identifies four policy priorities: developing interoperable data infrastructure, strengthening verification mechanisms, creating incentives for SME sustainability reporting and ensuring accountable use of AI in financing decisions.

Why does it matter?

Small and medium-sized enterprises account for much of economic activity and employment but often struggle to access sustainable finance because they lack the resources to produce the data and reporting required by lenders and investors. AI could reduce these costs by automating data collection, reporting and credit assessment, making green finance more accessible to smaller businesses.

The OECD also emphasises that technology alone will not close the financing gap. Real progress depends on reliable data infrastructure, effective verification and clear governance to ensure AI-supported financing decisions are transparent, accountable and fair, preventing existing inequalities from being reinforced.

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China links AI data centre to direct green electricity supply

China has launched what state media described as the country’s first AI data centre powered entirely through a direct green electricity connection, linking AI infrastructure more closely with renewable energy supply.

The facility has started operations in Zhongwei, in the Ningxia Hui Autonomous Region, a western region that has become central to China’s computing and clean-energy strategy.

Operated by China Telecom Ningxia Branch, the data centre is built to a wind-powered liquid-cooling standard. According to the company, the facility achieves a Power Usage Effectiveness rating of 1.15, supporting high-performance AI computing while reducing energy use compared with conventional data centres.

The project is part of China’s wider effort to connect computing capacity with renewable energy resources. Ningxia has already hosted large-scale projects that directly supply green electricity to data centre clusters, including a 500 MW solar facility in Zhongwei linked to China’s computing-electricity coordination model.

Zhongwei is also a key node in China’s ‘Eastern Data, Western Computing’ initiative, which aims to shift data-intensive workloads from eastern economic centres to western regions with more land and renewable-energy resources.

The new facility is expected to support AI computing, data processing and industrial digital transformation. It could also increase demand for servers, AI chips, liquid-cooling equipment and other parts of China’s domestic technology supply chain.

The project highlights how energy availability and efficiency are becoming central to AI infrastructure policy, as countries and companies face rising power demand from data centres and advanced AI systems.

Why does it matter?

AI infrastructure is becoming an energy-policy issue. China’s green-powered data centre model shows how governments may try to match growing AI compute demand with renewable-energy deployment, regional data-centre planning and industrial supply-chain development. For China, the project also supports a broader strategy of moving compute workloads westward, reducing pressure on eastern cities and using renewable resources in regions such as Ningxia. The challenge will be proving that such facilities can deliver reliable AI computing at scale while genuinely reducing emissions across the full power and data-centre system.

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UN secretary-general calls for greater transparency on AI’s climate impact

UN Secretary-General António Guterres has called on AI companies to publicly disclose the environmental impact of their operations, including carbon emissions, water consumption, and land use. Speaking at London Climate Action Week, Guterres proposed an AI Environmental Transparency Initiative, arguing that communities are often left without clear information about the environmental impact of nearby data centre developments.

Citing a UN study, Guterres said data centres consumed more electricity in 2025 than all but ten countries, accounting for around 1.5% of global electricity demand. That share could approach 3% by 2030, while AI-related water consumption and pollution are also projected to rise significantly. By 2030, that figure is projected to nearly double to close to 3 per cent, while the water use and pollution associated with AI are also expected to double within four years.

Guterres noted that coal still provides around 30% of the electricity used by data centres globally, while renewables account for approximately 27%. He called on AI companies to power their facilities entirely with renewable energy by 2030. Guterres called on AI firms to commit to powering their facilities entirely from renewable sources such as wind and solar by 2030, though existing clean energy commitments from major tech companies have already been complicated by the rapid pace of AI deployment.

Guterres linked the proposal to broader concerns about climate change and energy security, arguing that both are rooted in continued dependence on fossil fuels. He noted that the planet has just endured its eleven hottest years on record, and that last year marked the first time the three-year global temperature average broke through the 1.5 degrees Celsius threshold set by the 2015 Paris Agreement.

He also noted that renewable energy surpassed one-third of global electricity generation in 2025 for the first time, while coal’s share fell below one-third, although he cautioned that rising AI-related electricity demand could complicate progress.

Coal’s share of global generation also fell below one-third for the first time, though significant challenges remain, particularly given policy reversals in the US under President Donald Trump, who has embraced fossil fuels and cut support for renewables.

Guterres, whose term ends in December 2026, will convene world leaders again at the annual COP climate summit later this year. He reiterated calls for every major emitter to accelerate action, reduce methane emissions, and move away from coal, oil, and gas, with the speech delivered during a heatwave affecting much of London and Europe.

Why does it matter?

The rapid expansion of AI infrastructure is bringing its environmental footprint under increasing scrutiny. As data centres consume growing amounts of electricity and water, policymakers are beginning to ask whether AI companies should be subject to the same transparency expectations applied to other carbon-intensive industries. Standardised reporting could provide governments, investors and local communities with a clearer understanding of AI’s environmental impact.

The proposal also highlights the growing intersection between AI governance and climate policy. As countries seek to expand AI capabilities while meeting emissions targets, the availability of clean energy, sustainable infrastructure and transparent environmental reporting is likely to become an increasingly important part of discussions on responsible AI development.

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MIT researchers develop cooling system to cut data centre energy and water use

A startup founded by researchers from MIT has developed a nuclear-inspired cooling system designed to improve data centre energy efficiency while reducing water consumption. The technology targets one of the fastest-growing sources of electricity demand, as the rapid expansion of AI infrastructure drives increased computing requirements.

Ferveret’s system uses a specialised liquid to immerse servers, replacing traditional air-based cooling methods that account for a significant share of data centre energy consumption. Its Adaptive Phase Cooling approach improves heat transfer through controlled bubble formation, increasing efficiency while reducing reliance on water-intensive cooling systems.

The company reports computational efficiency gains of up to 15% compared with existing liquid cooling technologies, alongside improved overall performance when combined with power optimisation software. Ferveret is already testing its system with several data centre operators and AI hardware companies as it moves towards wider commercial deployment.

The startup says its modular design enables easier integration into existing facilities while allowing data centres to operate more effectively in regions with limited water resources. By reducing energy waste and improving heat management, the technology aims to support the growing demand for AI computing without further increasing environmental strain.

Why does it matter? 

The rapid growth of AI is driving unprecedented demand for computing power, placing increasing pressure on electricity grids, water supplies and data centre infrastructure. Cooling systems are a major contributor to both energy consumption and operating costs, making efficiency improvements a growing priority for the technology sector.

Innovations such as liquid immersion cooling could help reduce the environmental footprint of AI infrastructure while supporting continued growth in computing capacity. As governments and companies seek to balance AI expansion with sustainability goals, advances in cooling, power management and resource efficiency are becoming an increasingly important part of the broader AI ecosystem.

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Researchers develop AI governance tools for public health across the Global Majority

A research team led by Professor Jude Kong from the University of Toronto is developing new tools to monitor, assess, and govern the use of AI in public health across the Global Majority, with a particular focus on Africa.

The team, which includes Jake Effoduh, Jim Hinton, Abbas Yazdinejad, and Maral Niaz, has begun mapping how AI is being integrated into healthcare systems and infrastructure. The work focuses on identifying key actors, technologies and use cases, providing a clearer picture of how AI is becoming embedded in public health systems.

The next phase involves developing a dynamic dashboard designed to track AI systems and support evidence-based decision-making. Rather than relying solely on top-down governance frameworks, the team aims to co-develop tools that policymakers, civil society organisations, educators and practitioners can use in their own contexts.

In practice, this means creating tools that are not only technically robust but also socially legitimate and locally relevant. While strengthening AI literacy and governance capacity across the Global Majority, the initiative aims to empower policymakers with evidence-based insights, support civil society in understanding AI systems, and enable more informed and inclusive decision-making processes.

By bringing together expertise in technology, law, public policy and social impact, the project reflects the multidisciplinary nature of AI governance. The team will present its findings at the AI for Good Global Summit in Geneva, during ITU’s Kaleidoscope sessions on Thursday, 9 July 2026, from 15:30 to 16:30.

Why does this matter in AI world?

AI for the Global Majority (AI4GM) is a joint initiative of the Geneva Graduate Institute, Microsoft and the International Telecommunication Union. The initiative supports research on how AI can benefit majority populations in areas including governance, education, health, finance, and digital innovation.

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China brings AI into advanced ocean forecasting systems

China has unveiled LangYa 2.0, an upgraded AI-powered ocean forecasting system designed to predict complex marine phenomena with greater precision and detail. The model was unveiled at the Fourth China Digital Earth Conference in Qingdao and represents a step forward from earlier ocean monitoring tools.

Developed by the Institute of Oceanology at the Chinese Academy of Sciences, the system goes beyond monitoring variables such as temperature and salinity to forecast high-impact events, including typhoons, storm surges, extreme rainfall, internal waves, mesoscale eddies, and sea ice.

The platform combines specialised AI sub-models trained on diverse datasets and informed by physical ocean processes.

LangYa 2.0 is designed to provide decision-support information for applications including disaster preparedness, maritime safety, polar navigation and climate adaptation. The system can simulate rapid typhoon intensification and sudden track shifts, while also forecasting hidden ocean dynamics that may impact offshore infrastructure.

According to researchers, the model ranked first in a 2025 international Arctic sea ice forecasting evaluation, highlighting its potential for polar forecasting applications. Researchers are exploring ways to expand the system into broader climate and ecological modelling, with the aim of supporting future marine intelligence and environmental monitoring platforms.

Why does it matter?

Accurate ocean forecasting plays a critical role in disaster preparedness, maritime safety, climate adaptation and the protection of coastal infrastructure. AI-based systems can process large volumes of environmental data more quickly and identify complex patterns that may be difficult to capture using traditional forecasting methods alone.

LangYa 2.0 also reflects a broader trend towards using AI in Earth system science. As climate-related risks become more frequent and complex, governments and researchers are increasingly investing in AI-driven tools to improve environmental monitoring, risk assessment and decision-making.

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Cambridge researchers test AI-designed vaccine in human trial

Researchers at the University of Cambridge have developed an experimental vaccine using AI, marking what they describe as the first human test of a vaccine component designed entirely by AI. The experimental approach aims to provide broad protection against entire families of viruses, including coronaviruses with pandemic potential.

The AI system analysed genetic data from multiple coronaviruses and designed a ‘super-antigen’ intended to help the immune system recognise and respond to a broad range of viral variants, including those that may emerge through future mutations. An initial trial involving 39 volunteers focused primarily on safety, while a larger follow-up study is planned to evaluate immune responses and effectiveness in greater detail.

Researchers say the approach could help vaccine development keep pace with rapidly evolving threats, including influenza, emerging COVID-19 variants and viruses with the potential to spread from animals to humans. The team is also exploring similar AI-designed vaccines for influenza, bird flu, and Ebola-like viral haemorrhagic fevers, where current protection options remain limited.

Researchers describe the findings as an early but significant step towards using AI to accelerate vaccine design and strengthen preparedness for future disease outbreaks. The study highlights growing expectations that AI may become a central tool in global pandemic prevention strategies.

Why does it matter?

Traditional vaccine development often focuses on responding to specific pathogens after they emerge. By contrast, AI-assisted design could help researchers develop vaccines that provide protection against entire families of viruses before outbreaks occur.

If successful, the approach could shorten development timelines, improve preparedness for future pandemics and support efforts to address rapidly evolving infectious diseases. The research also highlights the growing role of AI in scientific discovery and biomedical innovation.

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