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AI for Good Global Commission launches to expand trusted AI access

Rwanda’s President Paul Kagame, Salesforce Chair and CEO Marc Benioff and International Telecommunication Union Secretary-General Doreen Bogdan-Martin have announced the launch of the AI for Good Global Commission.

The Commission brings together more than 40 founding members, including heads of state and government, technology executives and heads of UN agencies.

It is co-chaired by Kagame and Benioff, with Bogdan-Martin serving as vice-chair. ITU said the Commission will work to identify practical pathways to strengthen trust, expand access and unlock AI’s potential to address real-world challenges.

The initiative will focus on technical, socioeconomic and policy questions around AI, with an emphasis on responsible innovation, human capability and broad-based economic and social benefits.

Access is a central part of the Commission’s mandate. ITU said 2.2 billion people remain offline, limiting their ability to benefit from AI developments.

The Commission builds on ITU/UNESCO Broadband Commission for Sustainable Development, which has focused on connectivity, digital inclusion and economic development.

Its inaugural meeting will take place during the AI for Good Global Summit 2026 from 7 to 10 July. The Summit is part of Digital Week, which also includes the first UN-mandated Global Dialogue on AI Governance and the WSIS Forum 2026.

Why does it matter?

The AI for Good Global Commission places digital inclusion at the centre of global AI governance debates. Its launch highlights a key challenge: many countries and communities cannot benefit from AI if they lack connectivity, infrastructure, skills and institutional capacity. The Commission’s relevance will depend on whether it can move beyond high-level commitments and help turn access, trust and responsible innovation into practical support for developing countries.

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Ireland introduces AI Bill to implement EU AI Act

Ireland’s government has introduced the Regulation of AI Bill 2026, with Digital Transformation Minister Niamh Smyth describing the legislation as essential to protecting citizens while supporting innovation during its Second Stage debate in the Dáil.

The Bill is intended to give full effect to the EU AI Act in Ireland by establishing the national institutions needed to supervise and enforce the regulation ahead of the EU implementation deadline of 2 August 2026.

A central element of the Bill is the establishment of the AI Office of Ireland as an independent statutory body. The office will act as Ireland’s national point of contact with the European Commission and other member states, oversee enforcement of the AI Act, promote AI literacy and innovation, and operate a regulatory sandbox for start-ups and small and medium-sized enterprises.

Smyth acknowledged both the opportunities and risks presented by AI, highlighting advances in areas such as healthcare and scientific research while warning that, without appropriate safeguards, the technology could reinforce discrimination, manipulate behaviour and exploit vulnerabilities. She emphasised that the Bill is an implementing measure and does not introduce obligations beyond those already established by the EU AI Act.

Smyth also said the legislation would strengthen Ireland’s position as an ‘EU centre of excellence and digital regulatory hub‘. She argued that a robust enforcement framework would provide businesses with the regulatory certainty needed to invest and innovate, with the government seeking passage of the Bill before the August deadline.

Why does it matter?

Ireland’s implementation of the EU AI Act carries particular significance because many of the world’s largest technology companies base their European operations there. The establishment of an independent AI Office with enforcement responsibilities and a regulatory sandbox positions Ireland as a key player in applying the EU’s AI rules in practice.

The legislation also illustrates the broader challenge facing EU member states as the AI Act enters into force. Governments must rapidly establish the institutions, expertise and enforcement mechanisms needed to supervise AI systems while providing businesses with regulatory certainty and supporting continued innovation.

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Pax Silica expands with new AI partnership, supply chain initiatives, and workforce programme

The United States has announced a series of new initiatives under the Pax Silica partnership aimed at strengthening AI supply chain security, expanding international cooperation on AI, and supporting advanced manufacturing capabilities among participating economies.

The announcements were made following the 2026 Pax Silica Summit, the second meeting of the initiative launched by the US Department of State in December 2025. Pax Silica focuses on strengthening economic security and resilient supply chains across sectors, including semiconductors, critical minerals, advanced manufacturing, energy inputs, AI, and digital infrastructure, through cooperation among participating countries.

One of the summit’s principal outcomes was the signing of a Joint Statement on AI Opportunity by the United States and nearly three dozen partner economies. According to the US Department of State, the statement promotes a pro-innovation and pro-growth approach to AI governance while emphasising secure AI supply chains and support for startups, developers, and private-sector innovation. Signatories include countries from Europe, the Indo-Pacific, the Middle East, and Latin America, including Australia, Germany, India, Japan, the Republic of Korea, Singapore, the United Kingdom, and the United States.

The summit also expanded the Pax Silica partnership itself. Ten additional participants, including Argentina, Chile, Costa Rica, El Salvador, the European Union, Germany, Greece, Kazakhstan, the Netherlands, and Panama, joined the initiative, bringing the total number of signatories to 24. Taiwan continues to support the initiative’s principles through a separate joint statement on economic security cooperation with the United States.

Another announcement focused on strengthening the security and transparency of AI supply chains. The US Department of State plans to launch a competitive funding programme for a pilot AI Assistance Project in Panama to develop an AI supply chain credentialing and provenance platform. According to the Department, the proposed platform would integrate with customs authorities, ports, and logistics systems to help verify and facilitate shipments of semiconductors, AI infrastructure, critical minerals, and other strategic goods. If successfully implemented in Panama, the project could later be expanded to additional Pax Silica partners.

The summit also introduced Foundry School, a workforce development initiative established jointly by the US Department of State and Stanford University. The programme will begin with seminars at Stanford for entrepreneurs and industrial leaders and will be complemented by an advanced manufacturing curriculum that participating educational institutions across Pax Silica economies will be able to adopt. The initiative aims to strengthen expertise in advanced manufacturing, recognising its growing importance for both economic competitiveness and technological development.

Pax Silica reflects broader government efforts to strengthen resilience across AI-related supply chains as geopolitical competition increasingly intersects with technological development. In recent years, countries have introduced a range of policies covering semiconductor production, critical minerals, export controls, and trusted technology partnerships, while also seeking to balance innovation with economic and national security considerations.

The summit’s outcomes indicate that Pax Silica is evolving beyond a policy dialogue into a broader cooperation framework encompassing AI governance, supply chain security, industrial capacity, and workforce development. Whether the initiatives announced at the summit expand beyond their initial pilot phase will depend on implementation by participating governments and continued international cooperation among partner economies.

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University of Wisconsin launches College of Computing & AI

The University of Wisconsin-Madison has launched its College of Computing & Artificial Intelligence (CAI), the institution’s first new college in more than four decades.

The new college brings together the departments of Computer Sciences, Statistics and the Information School, building on the School of Computer, Data & Information Sciences established in 2019.

The college will focus on computing and AI education and research while promoting collaboration across fields including health, engineering, business, the social sciences, the arts and the humanities.

The university also plans to launch new academic programmes, recruit 50 faculty members over the coming years and expand partnerships with industry and government to strenthen research, education and innovation.

Why does it matter?

The creation of a dedicated College of Computing & Artificial Intelligence reflects the growing importance universities are placing on AI as a cross-disciplinary field rather than a specialised area within computer science. By bringing together expertise from multiple disciplines, the university aims to prepare students and researchers to address the technical, social and ethical challenges of AI.

The investment also highlights intensifying competition among higher education institutions to attract talent, research funding and industry partnerships in AI. Expanding faculty, academic programmes and collaboration with government and business positions the university to play a larger role in developing the next generation of AI research and workforce skills.

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Microsoft launches $2.5 billion AI implementation business

Microsoft has announced a $2.5 billion investment to create Microsoft Frontier Company, a new operating business focused on helping organisations deploy AI systems at scale.

The company said the unit will embed 6,000 engineers, consultants, support specialists and industry experts with customers to design, deploy and continuously improve AI systems linked to measurable business outcomes.

Microsoft said the initiative responds to a shift in enterprise AI adoption, as companies move from experimentation to implementation, return on investment, and the protection of proprietary knowledge.

A central part of the approach is model choice. Microsoft said customers should be able to use different models for different scenarios, including models from OpenAI, Anthropic, Microsoft AI, open-source communities and specialised industry developers.

The company also said customer data, intellectual property, workflows and competitive knowledge should remain protected and should not be used to train models in ways that reduce customers’ market advantages.

Microsoft said early projects with organisations including the London Stock Exchange Group, Land O’Lakes, Unilever and Novo Nordisk have already delivered measurable outcomes through AI integration.

Rodrigo Kede Lima will serve as president of Microsoft Frontier Company. Microsoft said the new business will work with global systems integration partners, including Accenture, Capgemini, EY, KPMG and PwC.

Why does it matter?

The announcement shows how the enterprise AI market is shifting from access to models towards implementation, integration and measurable business outcomes. Many organisations already have AI tools, but struggle to embed them into workflows, protect proprietary data and show returns on investment. Microsoft’s new unit positions the company as an AI engineering and services partner across models, cloud infrastructure and enterprise operations, while also reflecting growing demand for multi-model AI ecosystems rather than single-provider dependency.

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EU launches Cybersecurity Skills Coalition EDIC

The European Commission and participating member states have launched the Cybersecurity Skills Coalition European Digital Infrastructure Consortium to strengthen cybersecurity skills across the EU.

The consortium, known as CSC-EDIC, will support the implementation of the EU Cybersecurity Skills Academy, a flagship initiative launched by the Commission in 2023.

Announced during Digital Skills EU Days 2026, the consortium will be based in Athens. Greece, Cyprus, Austria, Croatia and Slovenia are founding members, while Czechia and Poland have joined as observers. Other member states will be able to join later.

The Commission said CSC-EDIC will develop and deliver tailored cybersecurity training programmes, measure cybersecurity skills gaps and serve as the secretariat for the Industry-Academia Network.

Working with ENISA, the consortium will also support cyber resilience in critical sectors, particularly the healthcare sector. Planned activities include an EU-wide attestation scheme for cybersecurity skills, career pathways and micro-credentials.

The initiative has received a €3.1 million grant from the Digital Europe Programme to support its initial governance, staffing and operations.

The Commission said the Cybersecurity Skills Academy has already secured 26 industry pledges, helping train more than 900,000 cybersecurity professionals. Ten partnerships have also been established through the Industry-Academia Network.

Why does it matter?

Europe’s cybersecurity workforce shortage affects the resilience of governments, businesses and critical sectors such as healthcare. CSC-EDIC gives member states a formal structure to pool resources, coordinate training and align skills development with EU cyber priorities. The initiative also shows how the EU is treating cybersecurity capacity as part of digital infrastructure, rather than solely as a labour-market issue.

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UN scientific panel publishes first global AI assessment ahead of Geneva governance dialogue

The United Nations’ Independent International Scientific Panel on Artificial Intelligence has published its first preliminary report, providing an evidence-based assessment of AI’s opportunities, risks, and societal impacts ahead of next week’s inaugural Global Dialogue on AI Governance in Geneva. Rather than prescribing specific policies, the report aims to inform international discussions by providing an independent scientific foundation for AI governance decision-making.

Established by the UN General Assembly in August 2025 following commitments made in the Global Digital Compact, the panel brings together 40 independent experts from academia, civil society, the private sector, and the technical community. It is the first permanent UN scientific body dedicated exclusively to assessing the development and societal implications of AI. The report will serve as a key input to the Global Dialogue on AI Governance, which takes place on 6–7 July alongside the World Summit on the Information Society (WSIS) Forum and the AI for Good Global Summit in Geneva.

The preliminary report examines AI through four broad dimensions:

Scientific and technological developments;
Opportunities for sustainable development;
Emerging risks;
Approaches to international governance.

Instead of advocating a particular regulatory model, the panel seeks to establish a shared evidence base that can support future policymaking and international cooperation on AI.

Rather than focusing solely on risks, the report examines AI’s growing role across sectors, including healthcare, education, agriculture, scientific research, and public administration. It describes AI as a general-purpose technology with the potential to accelerate innovation, improve productivity, and expand access to knowledge and public services. At the same time, the panel notes that these benefits remain unevenly distributed across countries and regions, with significant disparities in access to computing infrastructure, technical expertise, and digital resources.

The report estimates that more than one billion people now use AI-powered services each week, while frontier AI capabilities remain concentrated among a relatively small number of companies and countries. According to the panel, this concentration extends beyond AI models themselves to include computing infrastructure, specialised hardware, large-scale datasets, and technical talent, raising broader questions about equitable access to AI and the distribution of its benefits.

The panel also highlights the challenges facing developing countries, warning that many risk becoming primarily consumers rather than producers of AI technologies if investment in local infrastructure, research ecosystems, digital skills, and governance capacity does not keep pace with global developments. It identifies multilingual AI, locally relevant datasets, and stronger scientific capabilities as important factors in ensuring that AI systems better reflect diverse societies and languages rather than reinforcing existing global disparities.

Alongside these opportunities, the report identifies a range of emerging risks associated with increasingly capable AI systems. These include the use of AI for cyberattacks, fraud, disinformation, election interference, and other malicious activities, as well as broader concerns related to market concentration, transparency, and the growing dependence of many countries on a limited number of AI providers. The panel also notes that many governments currently lack the technical capacity to evaluate the most advanced frontier AI models independently.

Beyond security-related concerns, the report identifies environmental sustainability as an increasingly important governance issue. It notes that the rapid expansion of AI requires increasing amounts of computing power, electricity, water, and specialised hardware, and argues that future AI development should balance technological progress with efficient resource use and broader sustainable development objectives.

Speaking at the report’s launch, UN Secretary-General António Guterres said that the pace of AI development requires stronger international cooperation grounded in scientific evidence and inclusive dialogue.

Panel co-chair Maria Ressa described the publication as an independent scientific assessment designed to inform, rather than replace, intergovernmental decision-making. The report itself states that ‘effective AI governance requires international cooperation,’ while recognising that governance approaches will continue to reflect different national circumstances and policy priorities.

The publication marks the first major output of the Independent International Scientific Panel on AI since its establishment under the Global Digital Compact. Future reports are expected to provide regular scientific assessments of AI capabilities, impacts, and governance challenges as the technology continues to evolve.

Why does it matter?

As governments, international organisations, researchers, and industry representatives gather in Geneva next week for the inaugural Global Dialogue on AI Governance, the preliminary report is expected to provide an important reference point for discussions on the future of AI. By combining scientific evidence with a broad assessment of opportunities, risks, and governance considerations, it seeks to support a more informed international conversation on how AI can contribute to sustainable development, human rights, and shared global prosperity.

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Claude Science launches AI workbench for researchers

Claude Science has been launched as an AI workbench designed to streamline scientific research by bringing data analysis, coding and research tools into a single integrated environment. The platform is designed to help researchers analyse data, run multi-step workflows, and generate publication-ready outputs with full transparency.

The platform consolidates research tools such as databases, coding environments and analysis software, enabling scientists to work across disciplines without switching between applications. Outputs are fully auditable, with embedded code, workflow histories and documentation to support validation and reproducibility.

Claude Science also uses a multi-agent architecture comprising specialist agents and a reviewer agent that verifies calculations and citations. It can be deployed on local infrastructure or high-performance computing systems, allowing institutions to scale AI-assisted research while keeping sensitive data within their own environments.

Why does it matter?

Claude Science reflects a broader evolution of AI from a standalone assistant to an integrated research platform. By combining specialised AI agents, computational tools and transparent workflows in a single environment, it aims to simplify scientific research while improving reproducibility and collaboration.

The platform also raises broader questions about the future of AI in science. As researchers increasingly rely on AI to support data analysis and experimentation, ensuring transparency, validation and institutional control over sensitive research data will be essential to maintaining scientific integrity and trust.

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World Bank links Poland’s growth outlook to AI adoption

A World Bank Group report says faster AI adoption could significantly raise Poland’s economic output by 2035, but only if firms, workers and institutions can absorb the technology effectively.

The report estimates that Poland’s real GDP could be between 1.3% and 12.1% higher by 2035 than in a scenario where AI adoption remains at current levels. It also suggests that gains of 2% to 3% could appear within the next three years.

The estimates are based on a scenario in which AI adoption expands from 8.4% of Polish firms today to close to 45% by 2035. The report says adoption remains far below Denmark, where 42% of firms use AI.

Poland has several strengths, including 607,000 IT specialists, the largest pool in Central and Eastern Europe, and a high level of government AI readiness. However, only 50.4% of individuals have digital skills, compared with 60.4% across the EU.

The report says 48% of Polish workers are in highly AI-exposed occupations, below the EU average of 53%. It stresses that AI exposure does not automatically imply job losses, but can lead to either displacement or augmentation depending on skills, firm adoption and institutional support.

According to the World Bank, the main challenge is not only access to AI technology but also integrating it into business processes and enabling workers to move into higher-productivity roles.

The report calls for stronger labour-market monitoring, reskilling, support for firm-level AI adoption and policies that help Poland convert AI exposure into productivity gains.

Why does it matter?

The report frames AI adoption as a strategic economic issue, not only a technology upgrade. Poland already has strong digital foundations, including a large IT workforce, but low firm-level AI use could limit productivity gains if adoption does not accelerate. The findings also show that skills, labour mobility and institutional support will determine whether AI exposure leads to better jobs and higher productivity or deeper labour-market frictions.

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OpenAI launches GeneBench-Pro for AI biology research

OpenAI has introduced GeneBench-Pro, a research benchmark designed to assess whether AI agents can perform the complex, judgment-intensive analysis required in real-world computational biology.

Unlike conventional benchmarks that focus on factual recall or routine workflows, GeneBench-Pro is designed to measure what OpenAI calls ‘research taste‘, the sequence of judgement calls involved in scientific analysis, from interpreting ambiguous data and revising assumptions to deciding whether findings are robust enough to inform downstream research.

The benchmark comprises 129 problems spanning ten domains within computational biology, including statistical genetics, cancer genomics, clinical diagnostics, and pharmacogenomics. Each problem presents an AI agent with a realistic and deliberately messy dataset, brief experimental context, and a target to estimate.

To answer correctly, the model must explore the data iteratively, select an appropriate analytical approach, and supply a final answer without exploiting shortcuts or matching arbitrary author preferences. To prevent common benchmark shortcuts, every problem uses synthetically generated data whose underlying causal structure is fully known, allowing performance to be measured against a controlled ground truth.

OpenAI said its flagship model, GPT-5.6 Sol, achieved a pass rate of 28.7% at the highest reasoning setting, increasing to 31.5% in Pro mode. By comparison, the strongest model available when the original GeneBench was introduced scored below 5%.

External reviewers estimated that completing a typical GeneBench-Pro task would require 20 to 40 hours of expert work and cost thousands of dollars, whereas AI inference currently costs only a few dollars per run. OpenAI argues this suggests substantial economic potential even before models achieve expert-level performance.

OpenAI acknowledged that frontier models still solve fewer than one-third of the benchmark problems, often making partial progress but failing to complete the full chain of scientific reasoning expected from experienced researchers. To encourage independent evaluation, the company is open-sourcing ten representative tasks on Hugging Face and providing a 50-question subset to Artificial Analysis for third-party benchmarking.

Why does it matter?

GeneBench-Pro reflects a broader shift in AI evaluation from testing factual knowledge and coding ability to assessing whether models can support complex scientific reasoning. As computational biology increasingly becomes limited by data interpretation rather than data generation, reliable AI assistance in analytical workflows could accelerate research in areas such as genomics, drug discovery and precision medicine.

The benchmark also highlights the importance of rigorous evaluation methods for frontier AI. By using controlled synthetic datasets with known ground truth, GeneBench-Pro seeks to measure not only whether models reach the correct answer but also how well they make the sequence of judgements required in real-world scientific research.

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