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AI is reshaping work more through job transformation than job loss, WSIS panel hears

AI is changing the world of work in more complex ways than simply replacing workers, according to experts speaking at the WSIS Forum 2026. Panellists from the International Labour Organization (ILO) and the International Telecommunication Union (ITU) argued that while AI will automate some tasks, its broader impact will be felt through changing job quality, workplace surveillance, recruitment practices and skills requirements, making human-centred policies essential to ensure workers benefit from the digital transition.

The discussion highlighted that governments, employers and workers all have a role in shaping the future of work, with speakers calling for stronger labour protections, social dialogue and investment in digital skills to prevent AI from deepening existing inequalities.

AI is changing tasks and working conditions more than eliminating jobs

Sher Verick, Head of the Employment Strategies Unit in the Employment Policy Department of the ILO, challenged the widespread narrative that AI will trigger mass unemployment. Presenting findings from the ILO’s AI exposure index, he said around one in four workers worldwide are exposed to AI, yet only 3.3% of global employment falls into occupations that are highly vulnerable to automation.

‘The focus shouldn’t only be on job losses,’ Verick argued, explaining that AI is transforming how work is organised rather than simply eliminating occupations. Jobs involving a diverse range of tasks are more likely to change than disappear, while new roles are already emerging across AI supply chains, including data annotation and other support functions.

He stressed that the most significant impact may be on job quality rather than job numbers. Automated recruitment systems, algorithmic task allocation and AI-driven performance monitoring are already reshaping working conditions across sectors, while productivity gains could eventually create new employment opportunities through wider economic growth.

Algorithmic management raises new concerns for workers

Uma Rani Amara, Senior Economist at the Research Department of the ILO, argued that the conversation about AI should extend well beyond generative AI tools such as ChatGPT to include the algorithmic management systems increasingly used across workplaces.

Drawing on examples from manufacturing and healthcare, she explained that AI-powered surveillance tools, CCTV systems and digital performance dashboards are allowing employers to monitor workers more closely than ever before. While companies often present these technologies as efficiency tools, she warned that they can increase workplace stress, intensify workloads and reduce workers’ autonomy.

In hospitals, digital workflow management systems may improve patient scheduling and resource allocation, but they also place nurses and doctors under greater pressure by increasing workload intensity and extending on-call responsibilities. Even commonly used tools such as messaging applications can create new privacy risks when sensitive information is shared outside secure systems.

Rani also drew attention to what she described as AI’s ‘invisible workforce’, the millions of people, largely based in the Global South, who label data, moderate content, and perform other essential tasks that allow AI systems to function.

‘We should stop calling it AI and start calling it ‘human-in-the-loop intelligence’,’ she said, arguing that AI’s apparent autonomy obscures the human labour underpinning every stage of its development.

She called for stronger protections for these workers through measures such as fair labour standards, mandatory disclosure of AI supply chains and certification systems showing where training data originates and under what working conditions it was produced.

Governments must shape the future of work

Juan Chacaltana, Senior Employment Policies Specialist at ILO, argued that technological change should not be viewed as an inevitable force to which societies simply adapt.

‘The future of work should be shaped through policy,’ he said, presenting findings from an ILO review of 75 employment policy documents that found governments increasingly integrating digital technologies into employment services, labour market information systems and skills programmes.

However, he cautioned against viewing digital tools as a solution in themselves. While technologies can help modernise public employment services and support labour market formalisation, they cannot replace traditional drivers of economic development such as productivity growth, investment and strong institutions.

Chacaltana also warned that governments should avoid using digital tools primarily for surveillance or enforcement. Instead, introducing digital identity systems, AI-assisted public services and labour market technologies should involve workers, employers and other stakeholders through meaningful social dialogue.

The discussion also highlighted groups facing particular risks during the AI transition. Rani warned that young workers could lose the entry-level jobs that traditionally provide experience and career progression, while women risk a ‘double whammy’ of displacement from automation alongside discrimination embedded in biassed AI recruitment systems. Older workers and people in informal employment could also face new forms of exclusion or reduced autonomy as algorithmic systems increasingly influence workplace decisions.

Skills and cooperation are key to an inclusive AI transition

Praachi Kumar, Capacity Development Officer at ITU, said demand for AI-related training has grown rapidly, with interest in AI courses through ITU Academy tripling over the past five years.

The Academy now serves more than 115,000 ICT professionals, the majority from developing countries, while ITU’s Digital Transformation Centres initiative has reached around 700,000 people in underserved communities through digital skills programmes.

Kumar said lifelong learning must remain human-centred, combining technical knowledge with practical experience and peer learning. She also highlighted new multilingual AI governance courses developed in partnership with UNESCO to help address widening skills gaps.

Throughout the discussion, speakers agreed that preparing workers for AI requires far more than technical training. They called for coordinated action across labour, education and technology ministries, alongside stronger partnerships between governments, employers, trade unions and international organisations.

Closing the session, moderator Maria Prieto Berhouet said the debate had consistently returned to one central principle: AI should serve people, not the other way around. Rather than allowing technological change to dictate the future of work, participants argued that governments and social partners must actively shape AI’s role so it enhances productivity while protecting workers’ rights, dignity and opportunities.

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UNCTAD says digital divide goes beyond internet access

UNCTAD has warned that closing the digital divide now requires more than expanding internet access, as AI reshapes trade, production and development prospects.

The organisation said digital inclusion increasingly depends on whether developing countries can use digital tools and AI to build productive capacity, support local firms, create jobs and expand trade opportunities.

Its analysis argues that digital skills, institutional capacity, data governance and fairer participation in the digital economy must match connectivity.

UNCTAD said developing countries need stronger local expertise and greater influence over how data is governed, rather than relying only on digital trade arrangements shaped by larger economies.

Building domestic AI and data capacity through skills development, technology transfer and policy support could reduce long-term dependence on foreign platforms, infrastructure and funding.

The article also points to examples of national capacity-building, including Ghana’s efforts to develop local technical expertise for digital policy.

UNCTAD also pointed out its work on e-commerce, digital trade, data governance and the digital economy supports countries in identifying policy options suited to their development needs.

The organisation also highlighted tools such as its Frontier Technologies Readiness Index and Science, Technology and Innovation Policy Reviews as ways to help governments assess readiness and strengthen digital policy.

Why does it matter?

UNCTAD’s framing shows that the digital divide is becoming a question of capability rather than connectivity alone. Countries may have internet access but still lack the skills, institutions, data governance and domestic technology base needed to benefit from AI-driven economic change. The issue is therefore moving from infrastructure policy into trade, development, technology transfer and digital sovereignty debates. For developing countries, the risk is not only being offline, but also being dependent on external platforms and excluded from shaping the rules and value chains of the AI economy.

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AI governance must move from principles to practical action, UN dialogue hears

Bridging the global AI divide will require much more than expanding access to AI tools, participants heard during a thematic session of the United Nations Global Dialogue on AI Governance. Speakers argued that countries need digital infrastructure, reliable electricity, skilled workforces, trusted institutions and governance capacity if they are to shape AI on their own terms rather than simply consume technologies developed elsewhere.

Throughout the discussion, governments, UN agencies, academics and industry representatives stressed that the next phase of AI governance should focus on implementation. They called for stronger international cooperation, investment in local capabilities and practical measures to ensure AI contributes to sustainable development instead of reinforcing existing inequalities.

Capacity building means creating AI, not just using it

Opening the session, Robert Opp of the UN Development Programme (UNDP) argued that the world is moving from a digital divide to an AI divide, one shaped not only by access to technology but also by countries’ ability to adopt, govern and develop AI responsibly.

Loretta Hieber Girardet of the UN Office for Disaster Risk Reduction (UNDRR) added that governments need trusted institutions, robust data systems and technical expertise if AI is to improve disaster resilience and public services.

The session’s co-chairs, Rashid Khan, Co-Founder of Yellow.ai, and Mark Alexandre Doumba, Gabon’s Minister of Digital Economy and Innovation, reinforced that message by arguing that AI governance should now move beyond high-level principles towards practical action. Khan said the challenge is no longer agreeing that AI should be inclusive and trustworthy, but creating the standards, infrastructure and skills needed to make those principles meaningful.

Doumba argued that developing countries should not try to replicate the resource-intensive path taken by major AI powers. Instead, they should build AI ecosystems suited to their own economies, languages and cultural contexts.

‘We should not measure success by who builds the biggest models,’ he suggested, but by whether AI creates jobs, improves public services and supports local innovation.

Several participants also stressed that capacity development must extend far beyond basic AI literacy. Shikoh Gitau argued that countries should become creators of AI rather than passive users, describing the goal as building AI ‘for us, by us’. That requires investment not only in technical skills, but also in research, standards, financing and local entrepreneurial ecosystems.

Government representatives echoed that assessment. Speakers from South Africa, Bangladesh, Nepal, Oman and Ethiopia all identified electricity, connectivity, computing power, public-sector capacity and access to quality data as essential foundations for meaningful AI participation.

Environmental sustainability moves to the centre of AI governance

One of the strongest themes throughout the discussion was that environmental sustainability should no longer be treated as a secondary issue in AI governance.

The UN Environment Programme (UNEP) argued that AI depends on extensive use of electricity, water, minerals and manufacturing while also generating growing volumes of electronic waste. Because these impacts extend across entire supply chains, speakers said governance should address AI’s full environmental lifecycle rather than focusing solely on the operation of AI models.

Participants also highlighted questions of environmental justice. Several speakers warned that many of the environmental costs associated with AI infrastructure, including mining, water consumption and waste, are disproportionately borne by communities in developing countries that receive relatively few of AI’s economic benefits.

Rather than assuming AI will automatically solve environmental challenges, panellists called for internationally comparable methods to measure AI’s environmental footprint, greater transparency from technology companies and stronger accountability across supply chains.

The discussion reflected a broader shift in international AI policy debates, with environmental sustainability increasingly treated as a core governance issue alongside safety, human rights and economic development.

Local languages and cultures must shape AI development

Another recurring message was that AI will only become genuinely global if it better reflects the world’s linguistic and cultural diversity.

Estonian President Alar Karis described how Estonia has invested heavily to ensure that AI systems can operate effectively in the Estonian language, despite the country’s relatively small population. Alongside partnerships with companies such as OpenAI and Google, Estonia has focused on training teachers, integrating AI into education and ensuring that modern Estonian-language content remains available for future AI systems.

Other speakers argued that similar efforts are needed worldwide. They noted that current AI models overwhelmingly favour dominant languages, leaving thousands of languages and many indigenous knowledge systems largely excluded from the AI ecosystem.

Several participants warned that countries lacking local datasets, evaluation benchmarks and language resources risk becoming dependent on technologies designed for entirely different cultural contexts.

The discussion also highlighted the importance of standards and international cooperation. UNESCO presented its ongoing work to implement its Recommendation on the Ethics of Artificial Intelligence through large-scale training programmes, language-diversity initiatives and AI competency frameworks for teachers and public officials.

Meanwhile, standards experts argued that participation in international standard-setting should itself be viewed as a form of capacity development, enabling developing countries to help shape the technical foundations of future AI systems.

Trust, children’s rights and implementation now take priority

Beyond infrastructure and capacity, speakers repeatedly argued that trust will determine whether AI delivers a broad public benefit. Participants emphasised that trustworthy AI requires transparent governance, accountable institutions and meaningful public oversight rather than technical performance alone.

Children’s rights received particular attention during the session. UNICEF warned that children are adopting AI technologies faster than adults are learning to regulate them, creating new risks around privacy, safety and development. Representatives called for child-centred benchmarks, stronger safeguards for children’s data and mandatory child-rights impact assessments for AI systems deployed in education, healthcare and other public services.

Several speakers also argued that governance should focus more on AI deployment than on frontier model development alone, ensuring that systems remain accountable throughout their lifecycle and can be adapted to local social and institutional realities.

Closing the session, Khan and Doumba returned to the discussion’s central message: that AI governance should ultimately be judged by practical outcomes rather than technological competition. Countries need the capability to shape AI according to their own priorities, they said, while international cooperation should ensure that no society is left behind.

Participants were encouraged to leave Geneva not simply with new principles, but with concrete commitments on financing, infrastructure, skills and cooperation that can be reviewed when the Global Dialogue reconvenes in 2027.

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Closing the AI divide means building capacity, not just expanding access

The global AI divide is no longer simply about who has internet access or the latest AI tools. It is increasingly defined by who has the infrastructure, computing power, skilled workforce and institutional capacity to develop, govern and adapt AI and who does not.

That was the central message of a discussion on bridging AI divides at the inaugural United Nations Global Dialogue on AI Governance, where governments, UN agencies and experts argued that narrowing AI inequalities will require a fundamental shift from expanding access to building long-term national capabilities.

From access to capability

Speakers repeatedly argued that AI has exposed a new generation of digital inequalities that extend well beyond connectivity.

Robert Opp, Chief Digital Officer of the UN Development Programme (UNDP), distinguished between an access divide and an adoption divide, warning that AI technologies are spreading faster than governments and institutions can build the capacity to use them responsibly.

Loretta Hieber Girardet, Chief Risk Knowledge of the UN Office for Disaster Risk Reduction (UNDRR), echoed that concern, saying countries need trusted institutions, governance frameworks, digital infrastructure and technical expertise if AI is to strengthen development rather than deepen existing vulnerabilities.

The discussion also highlighted how investment patterns reinforce those divides. Pedro Manuel Moreno, Deputy Secretary-General of UN Trade and Development (UNCTAD), noted that AI infrastructure investment is increasingly concentrated in a small number of countries and companies because investors naturally gravitate towards locations offering reliable electricity, high-speed connectivity, skilled workers and predictable governance. Without those foundations, he warned, many developing countries risk being left behind regardless of how quickly AI technologies spread globally.

Several government representatives reinforced that message by pointing to persistent shortages of electricity, broadband connectivity, computing infrastructure, quality datasets and digital skills as barriers to meaningful participation in the AI economy.

Capacity building means creating AI, not simply using it

Participants argued that AI capacity building should be redefined.

Moderator Shikoh Gitau said many current initiatives focus too heavily on teaching people how to use AI applications, while overlooking the broader ecosystem needed to create AI locally. Instead, she advocated an approach centred on ‘AI for us, by us’, combining investment in research, technical skills, financing, standards, entrepreneurship and local innovation.

UNESCO presented several initiatives intended to move countries in that direction. Assistant Director-General Khaled El-Enany highlighted the implementation of UNESCO’s Recommendation on the Ethics of Artificial Intelligence through training programmes for more than 50,000 public officials and judicial actors, AI competency frameworks for teachers and students, and projects promoting language diversity and responsible AI governance.

El Salvador offered an example of how countries are beginning to build national AI ecosystems. Vice President Félix Ulloa outlined investments in AI-supported education, telemedicine, regulatory sandboxes and a National AI Agency, alongside legislation covering AI, data protection, cybersecurity and robotics. While noting significant progress, he acknowledged that challenges remain in extending connectivity and digital opportunities to rural communities.

Throughout the discussion, speakers stressed that developing countries should become active contributors to AI development rather than remaining consumers of technologies designed elsewhere.

Language, culture and local knowledge matter

Several speakers argued that AI divides are also cultural and linguistic.

Co-chair Jovan Kurbalija, Executive Director of Diplo, said discussions about AI often focus on technology while overlooking knowledge itself. He argued that indigenous traditions, oral histories and local knowledge systems should be recognised as valuable resources for AI development, ensuring that technological progress strengthens rather than erodes humanity’s diverse intellectual heritage.

Valts Ernštreits highlighted the scale of linguistic exclusion, noting that only around 1,000 of the world’s roughly 7,000 languages currently have sufficient digital resources to support meaningful AI development. Without targeted investment, he warned, thousands of language communities risk being left outside the AI revolution.

Other speakers similarly argued that AI systems should reflect local cultures, values and institutions instead of simply adapting models developed for dominant markets. Building trustworthy AI, they said, requires communities to participate directly in data governance, research and system design.

A shared responsibility

While speakers differed on specific policy approaches, they broadly agreed that international cooperation will be essential to prevent AI from reinforcing existing global inequalities.

Suggestions included expanding public-private partnerships, strengthening participation by developing countries in international standards-setting, supporting open models and open standards, and creating a global AI fund to help countries invest in computing infrastructure, institutions and human capital.

Closing the session, Kurbalija returned to the discussion’s central theme, arguing that AI should ultimately help preserve and advance humanity’s collective wisdom rather than simply automate knowledge. Co-chair Samba Diouf added that regional cooperation will be particularly important for smaller countries that cannot realistically build every component of the AI ecosystem on their own.

Taken together, the discussion suggested that bridging AI divides will require far more than expanding access to technology. It will depend on whether countries can build the institutions, skills, infrastructure and knowledge needed to shape AI on their own terms, and ensure its benefits are shared more evenly across the world.

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UNESCO highlights civil servants’ role in AI governance

UNESCO’s AI literacy training for civil servants has highlighted the importance of public-sector capacity in responsible AI governance.

The programme focuses on AI ethics, governance, risk management and responsible use, rather than only on productivity tools or prompt-writing skills.

UNESCO said many participants initially expected practical training on AI tools, but later connected issues such as accountability, transparency, bias, procurement and oversight to their own public-sector responsibilities.

The experience showed that meaningful human oversight depends not only on technical safeguards inside AI systems, but also on the capacity of officials involved in procuring, deploying, regulating and monitoring those systems.

UNESCO said participants often finished the programme with more questions than they had at the beginning. The organisation framed that as a sign of growing awareness of the complexity of AI governance, not as a lack of understanding.

Localisation also proved important. Through the AI Ethics Experts Without Borders network, training was adapted to national contexts and delivered in languages used by officials in their daily work, including cohorts in Egypt and Tunisia.

UNESCO said AI literacy should be seen as a foundation for broader institutional readiness, including risk assessment methods, procurement guidance, monitoring processes, internal governance structures and cross-government coordination.

Why does it matter?

AI governance often focuses on principles, laws and technical safeguards, but implementation depends on the officials who must apply those tools in practice. Civil servants involved in procurement, regulation, service delivery and oversight need enough AI literacy to ask informed questions, identify risks and challenge vendor or institutional assumptions. Without that capacity, “human oversight” can become a procedural checkbox rather than a meaningful accountability mechanism.

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UNCTAD calls for stronger global data governance for AI

UN Trade and Development (UNCTAD) is urging governments, businesses and civil society to strengthen global data governance as AI becomes embedded across every sector of the economy.

The organisation argues that data has become a strategic resource whose benefits should be shared more equitably, particularly with developing countries that generate growing volumes of valuable digital data but have limited influence over the rules governing its use.

UNCTAD describes data as a shared resource that should be managed for the public good rather than treated solely as a commercial asset. Rather than advocating a single global regulatory framework, it supports an incremental approach based on common principles, safeguards and international cooperation.

The aim is to facilitate cross-border data flows while protecting public interests and supporting responsible AI development.

As the secretariat of the UN Commission on Science and Technology for Development, UNCTAD is coordinating a working group on data governance comprising government representatives alongside experts from academia, business and civil society.

The group is developing recommendations on how data should be governed and shared, with its findings expected to inform a future report to the UN General Assembly.

The discussion comes as AI is increasingly deployed across healthcare, education, agriculture and financial services.

UNCTAD argues that data governance must evolve alongside AI to ensure digital innovation supports sustainable development and prevents decision-making from becoming concentrated among a small number of countries and technology companies.

Why does it matter?

As AI becomes increasingly dependent on access to large, high-quality datasets, data governance is emerging as a strategic policy issue alongside AI regulation itself. How data is collected, shared and governed will influence not only innovation and economic competitiveness but also who benefits from the AI economy.

UNCTAD’s proposal also reflects growing concern that developing countries could become providers of valuable data without having a meaningful role in shaping the rules governing its use. By promoting common principles rather than a single global regulatory model, the organisation is seeking to build broader international cooperation while preserving national policy flexibility.

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Alberta uses Claude Code to review government systems

The Government of Alberta has used Anthropic’s Claude Code to review and secure provincial government systems, according to a case study published by the company. Anthropic said Alberta’s Ministry of Technology and Innovation used Claude Code with its Opus and Sonnet models to analyse code, identify vulnerabilities and support remediation.

According to Anthropic, the ministry scanned 466 million lines of code in about 20 hours, covering systems used across 27 provincial ministries. Around 50 AI agents worked in parallel to identify security vulnerabilities, infrastructure weaknesses and documentation gaps.

The ministry manages about 1,280 applications and 3,400 code repositories supporting services including social services, public safety and wildfire response. Anthropic said many had never undergone comprehensive security reviews, resulting in accumulated technical debt and incomplete documentation.

Alberta used a two-stage review process. A rules engine first identified known patterns, after which Claude Code analysed the results and cited the relevant files and lines for each finding. Anthropic said the approach uncovered issues that conventional automated scanning tools had missed.

Claude Code was also used to generate fixes, write tests where needed and assist with modernising legacy systems. Anthropic said ministry engineers reviewed and approved all proposed patches before deployment, maintaining human oversight throughout the remediation process.

Alberta also developed specialised Claude-based review agents for continuous security testing during software development. These include red-team agents that probe applications for vulnerabilities, blue-team agents that assess compliance with security standards, and additional agents that review code quality and public-facing content.

Why does it matter?

The case illustrates how governments are beginning to use AI coding agents to modernise and secure large portfolios of legacy software, an area that has traditionally required significant time and specialised expertise. If these tools prove reliable, they could help public administrations reduce technical debt, improve cybersecurity and accelerate software maintenance across critical public services.

At the same time, the deployment highlights the importance of governance in public-sector AI adoption. Alberta’s reported use of human review before implementing AI-generated changes reflects a growing emphasis on combining AI-assisted development with oversight, accountability and established security practices.

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Japan to establish AI council to drive national AI adoption

Japan’s government has approved plans to establish a new council to accelerate AI adoption and review the legal frameworks governing its development and use. The initiative forms part of the country’s 2026 policy guidelines and reflects growing efforts to integrate AI into key sectors of the economy.

The new body will replace a digital administrative and fiscal reform council established under former Prime Minister Fumio Kishida. Authorities said it will lead to what they describe as an ‘AI transformation’, a broad effort to reshape public services, business processes and working practices through AI.

Japan sees AI as an important tool for addressing the challenges of an ageing population and a shrinking workforce. Priority areas include healthcare, elderly care, transportation, infrastructure, workplace productivity and public administration, alongside broader digitalisation measures such as expanding the use of electronic medical records.

Chief Cabinet Secretary Minoru Kihara said AI and digital technologies should reduce burdens on citizens and businesses while improving public services. The government said it intends to accelerate digital transformation as part of its broader programme of economic and administrative reform.

Why does it matter?

Japan’s decision reflects how governments are increasingly embedding AI into long-term economic and public-sector strategies rather than treating it as a standalone technology initiative. For countries facing ageing populations and labour shortages, AI is becoming a key policy tool for sustaining productivity, modernising public services and addressing workforce constraints.

The new council also illustrates the growing convergence of AI policy and regulatory reform. By reviewing legal frameworks alongside promoting adoption, Japan is seeking to ensure that governance evolves in step with technological deployment, balancing innovation with public trust and accountability.

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UN scientific panel presents first AI assessment to Global Dialogue on AI Governance

The multidisciplinary Independent International Scientific Panel on Artificial Intelligence presented its first annual report during the United Nations Global Dialogue on AI Governance in Geneva, offering an evidence-based assessment of AI’s opportunities, risks and societal impacts.

The session formed part of the inaugural Global Dialogue on AI Governance, held on 6-7 July. The dialogue was established in 2025 to support open, transparent and inclusive discussions on international AI governance, including AI’s role in sustainable development, digital divides, safety, human rights, transparency, accountability and human oversight.

Opening the presentation, Yoshua Bengio, professor of computer science at the University of Montreal, said the panel’s role was to assess scientific evidence rather than prescribe policy, leaving decisions to UN member states and the Global Dialogue process. He warned that AI is at a turning point because machine intelligence is advancing quickly, while there are still no technical guarantees that AI systems will follow human instructions, norms or laws.

Bengio said current AI systems are already associated with harms, including emotional attachment among vulnerable users, increased cybersecurity vulnerabilities, unequal access and deceptive behaviour that can make evaluation more difficult. He argued that concentrated commercial and geopolitical interests are driving AI development without sufficient guardrails and called for a coordinated international and democratic response guided by scientific evidence.

Maria Ressa, co-chair of the panel, described the report as an independent assessment produced by 40 experts who ‘answered only to the evidence’. She said the report represents the minimum consensus among panellists rather than the upper limit of concern, calling it the ‘floor’ rather than the ‘ceiling’ of the panel’s findings.

Ressa also highlighted AI’s positive uses, including protein structure prediction used by millions of researchers, medical screening in India and food-crisis warning systems deployed in multiple countries. However, she also pointed to concrete harms, including dangerous medical mistranslations, AI tools identifying exploitable software flaws and the death of a 14-year-old boy following prolonged interaction with a chatbot. She urged governments, civil society and industry not to wait for certainty before acting.

The working-group presentations expanded on these findings. Mennatallah El-Assady, Computer Science Professor at ETH Zurich, described AI as a rapidly evolving technology moving from earlier symbolic systems to today’s generative and increasingly agentic models. She warned that independent verification remains weak, public benchmarks are becoming saturated and advanced systems are showing signs of evaluation awareness, including the ability to detect tests or behave differently when being assessed.

El-Assady also raised concerns about auditability as AI systems become more autonomous and capable of invoking external tools. She said interpretability, reliable auditing and independent verification are immediate bottlenecks, especially as AI moves beyond software and into physical systems such as robotics.

Joëlle Barral, Senior Director of Research & Engineering at Google DeepMind, focused on AI’s real-world benefits in science, healthcare, education and agriculture. She said task-specific AI is already producing measurable gains, citing examples such as self-driving laboratories, protein structure prediction and diabetic retinopathy screening in India. However, she stressed that successful deployment depends on local context, institutional capacity, workflows and follow-up systems, rather than technology alone.

In healthcare, Barral distinguished between purpose-built clinical AI and general-purpose systems, warning against the unintended use of general-purpose chatbots for medical advice. In education and agriculture, she similarly argued that AI benefits depend on trained teachers, relevant tools, local institutions and long-term evaluation.

Loreto Bravo, member of the UN Independent International Scientific Panel on AI, addressed AI’s economic implications, arguing that access to AI does not automatically translate into benefit. She said countries, firms and workers also need data, skills, infrastructure, management capacity and institutions to integrate AI into real tasks and workflows.

Bravo said the economic effects of AI are likely to differ across countries, sectors and workers. Large firms may reorganise more quickly, while smaller firms and developing economies may face greater barriers. She said the evidence does not support a single prediction of broad prosperity or mass unemployment, and that outcomes will depend on institutions, deployment choices and who captures the value created by AI.

Balaraman Ravindran, professor at Indian Institute of Technology Madras, examined security, alignment and environmental risks. He said AI development is outpacing risk mitigation, expanding cyber threats against both critical infrastructure and AI systems themselves. He also highlighted unresolved alignment problems, including bias, sycophancy, loss of control and AI-initiated deception.

Ravindran warned that the environmental costs of AI are also increasing as demand grows for computing power, energy, water and specialised hardware. He said the Global South faces disproportionate exposure because of structural vulnerabilities, limited local mitigation capacity and reliance on foreign software and infrastructure. He called for coordinated international standards rather than fragmented approaches driven only by companies or individual countries.

Rita Oluchi Orji, a Computer Science professor, focused on AI’s impact on human rights, information integrity and democracy. She said AI can support access to information and civic participation, but can also be engineered to persuade and manipulate people at scale. She warned of epistemic erosion, fragmented shared reality and unequal harms affecting groups such as women, girls, journalists and marginalised communities.

Orji said content moderation alone is insufficient if the systems that produce and amplify harmful material remain unchanged. She argued that governance must address targeting, amplification and optimisation models, not only individual pieces of false or harmful content.

Anna Korhonen, a Professor of Natural Language Processing at the University of Cambridge, addressed cultural and linguistic inclusion, child safety and mental health. She noted that while the world has more than 7,000 languages, current AI systems support only a small fraction of them, mostly the majority languages of the Global North. She said this exclusion is not inevitable and could be addressed through targeted investment and systemic changes.

Korhonen also warned about risks to children, including AI-generated child sexual abuse material, sexualised deepfakes and socially interactive AI toys that may encourage harmful parasocial relationships. On AI companions and mental health, she said such systems may help address loneliness, but also pose risks of emotional dependency, manipulation, privacy harms and reinforcement of harmful beliefs.

Haitao Song, President of the Shanghai Artificial Intelligence Research Institute and Director of the Global Industrial Artificial Intelligence Alliance Center of Excellence, focused on reliability and global governance frameworks. He said policymakers often have to make decisions with incomplete evidence and that current measurement systems cannot keep pace with AI development. He argued that existing approaches remain too narrow, focusing on compute and capabilities while paying insufficient attention to institutional development, talent and impact evaluation.

Song also noted that AI infrastructure and frontier models remain concentrated in a small number of economies, leaving many countries, especially in the Global South, with limited ability to participate in standard-setting. He described open-source AI as one possible contribution to inclusion, while acknowledging that it is not a complete solution.

Across the session, speakers repeatedly stressed that AI’s benefits are real but not automatic. They said successful use of AI depends on infrastructure, institutions, skills, local context, language inclusion and governance capacity. At the same time, they warned that harms are already visible, including cyber vulnerabilities, mistranslation, emotional dependency, manipulation, environmental pressure and risks to children.

The session concluded with Ressa and Bengio formally handing the report to the Global Dialogue. Bengio warned that many people still underestimate the possibility that AI capabilities may continue to grow in ways that could reshape global power dynamics. Ressa urged the Dialogue to act on the evidence presented by the panel, saying the difficult work now lies with policymakers and institutions responsible for shaping AI governance.

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WSIS session calls for meaningful connectivity as AI and e-governance expand

Speakers at the WSIS Forum 2026 warned that AI strategies, digital identity systems and e-government services are advancing faster than meaningful connectivity in many parts of Africa and the wider Global South, leaving rural communities, low-income groups, women and persons with disabilities at risk of further exclusion.

The session, titled ‘Closing Africa’s Connectivity Gap in the Age of AI and E-Governance’, took place during the WSIS Forum 2026 in Geneva. The annual forum, co-organised by ITU, UNESCO, UNDP and UNCTAD, brings together governments, international organisations, civil society, the private sector, academia and technical communities to discuss digital cooperation and sustainable development.

Opening the session, Thobekile Matimbe of Paradigm Initiative framed the discussion around evidence from more than 28 countries. She said governments are increasingly adopting AI strategies, digital IDs and online public services, but many people still lack the connectivity, devices and conditions needed to benefit from them. Based on Paradigm Initiative’s work, she argued that the digital divide is widening rather than narrowing.

Bridget Hanani Ndlovu outlined the scale of exclusion, noting that 2.6 billion people remain unconnected globally and that more than half of Africa’s population is still offline. She stressed that the problem is not only missing infrastructure, but also what she described as ‘deliberate disconnection’, including internet shutdowns.

Ndlovu said Paradigm Initiative’s 2025 review of 29 African countries found that nine had implemented internet shutdowns. She cited Kenya and Tanzania as examples where connectivity can be disrupted even when infrastructure exists, arguing that such measures limit people’s ability to access information, public services and economic opportunities.

She also warned that AI-powered digital identity systems can deepen exclusion when introduced in unequal contexts. Referring to Uganda, Ndlovu said elderly people, women and persons with disabilities had faced difficulties accessing services linked to digital ID systems. She said digital systems must be designed and implemented with affected communities in mind, rather than assuming that technology will automatically improve access.

Affordability was another recurring concern. Ndlovu said data costs remain prohibitive in several African countries, giving Zimbabwe as an example where internet access can be unaffordable for low-income users. She also pointed to infrastructure problems in parts of Nigeria, including Zamfara North, where communities continue to experience limited or unreliable access.

Shumaila Shahani, a human rights lawyer, said similar challenges exist in South Asia and urged participants to focus on the human consequences of weak connectivity. She said poor access is not only about slow speeds or failed downloads, but can determine whether people receive essential services. As an example, she said biometric failures can prevent people from receiving food rations.

Shahani also linked connectivity to electricity access, explaining that unreliable power and limited charging options can make mobile devices unusable. She said women and persons with disabilities are often particularly affected when charging points, devices, and digital services are not accessible to them.

Her main warning was that AI-enabled and digital systems become harmful when they replace older offline channels before everyone can use the new systems. She said the ‘new AI door’ is not the problem by itself, but that exclusion occurs when it becomes the only door available.

The panel also discussed Universal Service Funds (USFs), which are intended to support connectivity in underserved areas. Ndlovu said many African countries have USFs in law, but implementation is often weak, transparency is limited and public information on budgets and progress is difficult to find.

She cited several country examples, saying Ethiopia had created a framework without an operational fund, Somalia lacked a functioning USF, Sudan had repeatedly established a fund without effective implementation, and telecom operators in the Democratic Republic of the Congo had not made required contributions. She added that South Africa showed stronger transparency around its fund, while Namibia had begun rollout work and Tunisia had pursued alternative coverage models through ‘white zones’.

Shahani suggested that USFs should be complemented by other affordability measures, including reduced taxes on handsets, device financing, targeted support for women’s connectivity and legal obligations requiring private operators to extend rural coverage. She said the connectivity policy should also address the electricity infrastructure, including solar-powered towers.

The speakers also called for stronger accountability before governments deploy AI-integrated public systems. Ndlovu said governments should conduct human rights impact assessments before adopting digital identity or AI systems and should consult affected communities early, not only at the end of the policy process.

She argued that governments and international processes should measure harms and impacts, not only infrastructure rollout or the number of AI tools adopted. Matimbe supported this point, saying implementation must include civil society and other stakeholders at the national level, not only governments and companies.

Shahani added that connectivity statistics should better reflect meaningful access. She said counting someone as connected because they have 2G access does not capture whether they can actually use digital public services, AI tools or online education. Measurement, she argued, should include device capability, speed, affordability and daily use.

She also said national AI strategies must include explicit connectivity budgets, warning that ‘any national AI strategy without a connectivity budget’ is ‘just a press release’.

In the audience discussion, speakers addressed whether women’s connectivity should be treated separately from household access. Ndlovu said women are often specifically disadvantaged in access to technology and should not have to depend on devices controlled by others. Shahani added that if a woman relies on her partner’s phone, that access is not meaningful or independent.

Across the session, speakers agreed that meaningful connectivity in the AI era requires more than network coverage. It also depends on affordability, electricity, devices, protection from shutdowns, functioning Universal Service Funds, inclusive design, offline alternatives and rights-based assessments before new systems are deployed.

The discussion concluded with a shared emphasis on implementation. Speakers argued that governments, companies, civil society and technical experts need to work together to ensure that AI, digital identity and e-governance systems do not deepen exclusion, but instead expand access to services and opportunities for communities that remain offline or underserved.

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