Artificial intelligence

EU and Brazil strengthen cooperation through new Digital Partnership

The European Union and Brazil have signed a new Digital Partnership to strengthen cooperation on shared digital policy priorities, including AI, data governance, digital infrastructure, connectivity, online platforms and digital public goods and services.

The partnership was signed in Brasília and is intended to raise EU-Brazil digital cooperation to a more strategic level. According to the European Commission, Digital Partnerships are a core instrument of the EU’s external digital policy and are used to structure cooperation with like-minded partners.

The agreement builds on more than two decades of EU-Brazil cooperation, including the EU-Brazil Strategic Partnership and the existing EU-Brazil Digital Dialogue. The two sides said the partnership will support joint work on resilient global supply chains, rules-based digital governance and wider sharing of the benefits of technological progress.

The signing follows the adoption of mutual EU-Brazil data adequacy decisions in January 2026, which allow personal data to flow freely and securely between the two jurisdictions without additional requirements. The Commission described those decisions as creating the world’s largest area of free and safe data flows, covering around 670 million consumers.

Future cooperation under the Digital Partnership will be developed through technical workstreams and high-level exchanges. The first Digital Partnership Council is expected to meet within the next year to set out a joint roadmap for cooperation.

Why does it matter?

The partnership strengthens digital cooperation between the EU and one of Latin America’s largest economies at a time when AI governance, data protection, online platforms and digital public infrastructure are becoming central to international relations. It also shows how the EU is using digital partnerships and data adequacy decisions to expand trusted digital cooperation beyond Europe, while promoting regulatory alignment, secure data flows and shared approaches to global digital governance.

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IMF chief calls for stronger cooperation on AI-related cybersecurity risks

International Monetary Fund (IMF) Managing Director Kristalina Georgieva has called for greater international cooperation to address cybersecurity risks associated with advanced AI systems, warning that rapidly evolving AI capabilities could pose challenges for the global financial system if misused.

Speaking to journalists in Brussels, Georgieva said new AI models are increasing the ability to identify cybersecurity vulnerabilities at a scale previously unavailable. She noted that these capabilities can support efforts to strengthen cyber defences by helping organisations detect and address weaknesses more quickly.

At the same time, Georgieva said the same capabilities could be misused by malicious actors. Referring to recent developments in advanced AI systems, she said that frontier models can be used positively to identify cybersecurity vulnerabilities but that, ‘in the wrong hands,’ those capabilities could be directed against financial infrastructure.

Her comments come amid growing discussion among policymakers, regulators, and financial institutions about the implications of increasingly capable AI systems for cybersecurity and financial stability. Earlier this year, Georgieva warned that the international monetary system was not adequately prepared to address rapidly evolving AI-related cyber risks and called for greater attention to safeguards needed to protect financial stability.

According to Georgieva, stronger cooperation will be necessary across countries and sectors to address these risks. She highlighted the importance of collaboration between advanced and developing economies, as well as between public institutions and private-sector actors responsible for critical digital infrastructure.

She also pointed to the interconnected nature of the global financial system, arguing that vulnerabilities in one jurisdiction can have wider implications. Because financial systems are closely linked across borders, weaknesses in cybersecurity protections may create risks beyond the countries where they originate.

In addition to cooperation, Georgieva stressed the importance of investing in cyber resilience. She said governments should consider cybersecurity requirements when planning public spending and ensure that sufficient resources are available to strengthen defences against evolving threats.

Her remarks align with broader concerns raised by financial authorities regarding the growing role of AI in cybersecurity. While advanced models may help identify vulnerabilities and improve defensive capabilities, they may also lower barriers for conducting sophisticated cyber operations. Financial institutions and regulators have increasingly examined how to strengthen preparedness and resilience in response to these developments.

Georgieva also referred to broader risks associated with rapid AI adoption, including the potential for market volatility driven to changing expectations for AI technologies. She described such risks as low-probability but potentially high-impact events.

The IMF has previously highlighted the economic implications of AI, including its potential effects on labour markets and productivity. Georgieva has argued that governments should prepare for significant technological change while ensuring that the benefits of AI are broadly shared.

Why does it matter?

The comments in Brussels place cybersecurity and financial resilience at the centre of ongoing discussions about AI governance. As governments, regulators, and financial institutions continue to assess the implications of increasingly capable AI systems, questions around international cooperation, preparedness, and cyber resilience are expected to remain a key focus of policy discussions.

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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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Spanish minister says AI regulation boosts competitiveness and trust

Spain’s Minister for Digital Transformation and Public Function, Óscar López, said that AI regulation strengthens competitiveness rather than discouraging investment. Speaking at the Foro Talento España event organised by TRIVU, he argued that trust is becoming a key factor in the development and adoption of AI.

López pointed to OpenAI’s decision to open its first office in Spain as evidence that AI regulation can coexist with innovation and investment. He said Spain’s approach helps create a more predictable and trustworthy environment for businesses and technology development.

The minister also highlighted government investments in digital skills and talent development. He cited initiatives including the National Digital Skills Plan, university programmes focused on AI and cybersecurity, and plans to recruit 1,600 ICT specialists for the public sector.

These efforts have contributed to growth in higher education, technology training and STEM employment. Speaking in Madrid, López said continued investment in talent, digital skills and emerging technologies will be essential as AI and other advanced digital sectors continue to evolve in Spain.

Why does it matter?

The relationship between AI regulation and innovation remains a central policy debate worldwide. While some argue that regulation could slow investment and technological development, others contend that clear rules can increase trust, reduce uncertainty and encourage long-term adoption.

Spain’s position reflects a growing European approach that views regulation and innovation as complementary rather than competing objectives. By combining AI governance measures with investments in skills, education and digital talent, policymakers are seeking to build an environment that supports both technological development and public trust.

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Latin American AI proposals draw on EU risk-based regulation

Latin American countries are increasingly looking to the EU’s risk-based approach as they develop AI governance frameworks, according to an International Bar Association analysis.

The IBA noted that Chile, Peru, Brazil and El Salvador have introduced or advanced AI-related legislation in recent years, with several initiatives focusing on risk classification, fundamental rights and accountability. Peru implemented an AI law in 2023 and updated it in 2025, while Brazil has considered similar draft legislation, and El Salvador enacted an AI law in 2025.

Chile has become one of the region’s most active AI policy actors. It helped launch Latam-GPT, an open-source language model trained on Latin American data, and is considering an AI bill that would classify systems according to risk. The proposal includes stricter obligations for high-risk uses, as well as regulatory sandboxes and measures intended to support innovation and smaller businesses.

Legal experts cited by the IBA said the EU model fits parts of Latin America’s existing regulatory culture, particularly in data protection and cybersecurity. However, they also warned that EU-style requirements on risk governance, technical documentation, testing and incident reporting could strain regulators and smaller companies with limited resources.

The analysis also points to regional challenges, including legal differences between countries, gaps in data governance and different economic priorities. While Europe’s AI focus often centres on highly regulated sectors, experts said Latin America may see greater value from AI applications in financial inclusion, payments, healthcare, agriculture, commerce and logistics.

Why does it matter?

Latin America’s approach to AI regulation could shape governance conditions for a region of more than 650 million people. If countries align closely with the EU model, transparency, accountability and fundamental rights may become central pillars of regional AI governance. However, the IBA analysis also shows the risk of importing complex compliance models without sufficient regulatory capacity, which could burden smaller firms and slow adoption in markets where AI could support financial inclusion, healthcare, agriculture and public services.

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Japan strengthens generative AI procurement guidelines

Japan has approved updated guidelines for the procurement and use of generative AI across government information systems, strengthening governance and risk-management requirements for public administration.

The revised document, titled ‘The Guideline for Japanese Government’s Procurements and Utilizations of Generative AI for the sake of Evolution and Innovation of Public Administration’, was approved on 12 June 2026 by the Council for the Promotion of a Digital Society Executive Board Meeting.

The guidelines update a first version adopted in May 2025 and reflect advances in generative AI technologies, expanded government use cases and domestic and international AI policy developments. They are intended to promote the use of generative AI in government while setting rules for governance, procurement, development, operation and use.

The document covers generative AI systems and models, large language models, AI governance frameworks, high-risk generative AI projects, Chief AI Officers and risk management throughout the lifecycle of government AI systems.

Each ministry and agency is expected to promote the use of generative AI while assessing risks for specific use cases. Chief AI Officers will be responsible for centrally managing generative AI systems, including planning, administrative data handling, procurement, operation and risk cases.

The guidelines also set out a framework for high-risk uses of generative AI. Chief AI Officers must assess risk classifications with planners, use a high-risk project assessment tool and report likely high-risk projects to the Advanced AI Utilization Advisory Board, including project details, objectives, mitigation measures and quality assurance plans.

Why does it matter?

Japan’s update shows how governments are moving from experimentation with generative AI towards formal operating rules for public-sector deployment. The guidelines link AI adoption to procurement controls, lifecycle governance, high-risk assessment and institutional accountability through Chief AI Officers. That matters because public administrations are under pressure to use GenAI to improve services and efficiency, while also managing risks related to security, administrative decision-making, personal data, intellectual property, and public trust.

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UNESCO, TESDA and HP Foundation expand digital and AI skills training in the Philippines

UNESCO, the Technical Education and Skills Development Authority (TESDA), and the HP Foundation are expanding access to free digital skills and AI courses in the Philippines through the UNESCO Global Skills Academy. The initiative will make HP LIFE courses available through the TESDA Online Program, the country’s national eLearning platform.

TESDA said the collaboration will provide learners with access to free digital and entrepreneurship training aligned with evolving industry needs. The courses are intended to help learners develop practical digital skills and competencies that are increasingly in demand across the digital economy.

HP LIFE is a free business and digital skills training programme run by the HP Foundation. Its courses introduce learners to key AI concepts, responsible AI use, and practical applications of AI in business and everyday work, alongside topics such as entrepreneurship, marketing and finance.

The collaboration is facilitated via the UNESCO Global Skills Academy, which works with international organisations, governments, and industry partners to expand access to quality skills development opportunities. The academy aims to help 10 million young people and adults worldwide develop skills that improve employability by 2029.

TESDA said the partnership will help expand access to high-quality and industry-relevant training for learners across the Philippines. The initiative is expected to strengthen digital, entrepreneurial and AI-related skills that can enhance employment opportunities and livelihoods.

Why does it matter?

Digital skills and AI literacy are increasingly important for participation in modern economies, yet access to high-quality training remains uneven in many parts of the world. Expanding access to free online learning opportunities can help individuals develop skills that improve employability, entrepreneurship and participation in the digital economy.

The initiative also reflects a broader trend of collaboration between international organisations, governments and the private sector to address digital skills gaps. As AI becomes more widely used across industries, programmes that combine digital literacy, AI awareness and practical workforce skills are becoming an increasingly important component of national development and workforce strategies.

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MHRA report highlights public priorities for AI regulation in healthcare

The UK’s Medicines and Healthcare products Regulatory Agency (MHRA) has published two reports examining the views of patients, healthcare professionals and other stakeholders on the use of AI in healthcare.

The findings are intended to support the work of the independent National Commission into the Regulation of AI in Healthcare and inform future regulatory approaches.

The consultation gathered input from patients, healthcare professionals, industry representatives, researchers and public institutions. A separate Call for Evidence received submissions from 760 individuals and organisations.

Participants broadly recognised the potential benefits of AI in healthcare while emphasising the need for safeguards to ensure safety, effectiveness, transparency and accountability.

Several priorities emerged consistently across the engagement process. Contributors supported ongoing monitoring of AI systems after deployment, transparent decision-making, clear accountability mechanisms and human oversight.

Many respondents also argued that regulatory frameworks should evolve to keep pace with rapid technological advances while maintaining strong patient protections.

The findings will contribute to recommendations expected later in 2026 from the National Commission into the Regulation of AI in Healthcare. The recommendations are expected to help guide future regulatory decisions by the MHRA and other healthcare authorities.

Why does it matter?

Healthcare is one of the sectors where AI is expected to have the greatest impact, with applications ranging from diagnostics and clinical decision support to administrative efficiency and patient engagement. As adoption accelerates, regulators are increasingly focused on ensuring that AI systems are safe, effective and trustworthy.

The findings suggest that public support for healthcare AI is closely tied to transparency, accountability and human oversight. They also highlight the growing importance of adaptive regulatory frameworks that can support innovation while maintaining patient safety and public confidence in AI-enabled healthcare services.

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Microsoft president says AI’s future should be shaped by people, not technology alone

Microsoft Vice Chair and President Brad Smith has argued that the future impact of AI should be shaped by people rather than technology alone, emphasising the importance of human agency, creativity and the dignity of work.

In a recent blog post, Smith said concerns expressed by university graduates about AI’s impact on employment should be taken seriously by the technology sector.

Smith also noted that younger generations remain among the most active users of AI technologies but are increasingly questioning how AI will affect jobs, careers and society. He argued that graduates are sending a clear message that AI should support human capabilities instead of determining the role of people in the workforce.

The article draws on historical examples of technological disruption, including photography, computing and automation, arguing that new technologies have often transformed work rather than eliminated human creativity and ambition.

Smith acknowledged concerns about entry-level employment, workforce restructuring and economic uncertainty, while suggesting that AI adoption is likely to unfold over decades rather than over a short period.

Microsoft argues that individuals should focus on combining expertise in their chosen fields with AI literacy. The company also emphasises the importance of uniquely human skills such as creativity, curiosity, communication, compassion and judgement.

For organisations, Smith recommends using AI to strengthen institutional knowledge and productivity while retaining control over proprietary data, intellectual property and strategic decision-making.

Why does it matter?

The debate over AI’s impact on employment has become one of the central questions in technology policy and economic planning. While some forecasts focus on job displacement, others argue that AI will primarily transform how work is performed, creating demand for new skills and roles while reshaping existing occupations.

Smith’s comments offer insight into how a leading AI developer views the long-term transition. His emphasis on augmentation, workforce adaptation and human agency reflects a broader industry narrative that AI should enhance rather than replace human capabilities, while highlighting the growing importance of digital skills, lifelong learning and public participation in decisions about AI deployment.

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China sets AI integration targets for communications networks

China’s Ministry of Industry and Information Technology has released a three-year plan to accelerate the integration of AI with the country’s information and communications sector.

The implementation guideline, covering 2026 to 2028, sets targets for more autonomous networks, wider low-latency access to computing power and expanded AI applications. By 2028, China aims for information and communications networks to reach an initial stage of high-level autonomous intelligence.

The plan also calls for more than 30 high-value use cases, specialised intelligent agents and at least 75% coverage of one-millisecond-latency access to computing power in metropolitan areas.

MIIT identified several research priorities, including AI-driven network architectures, collaboration between large and small AI models, multi-agent systems and intelligent agent communications. It also calls for faster construction of major computing power channels and improved network resource scheduling.

Looking beyond the three years, China aims to make significant breakthroughs in core technologies for integrating AI with information and communications networks by 2030. The ministry said the longer-term goal is to strengthen integrated sensing, communications, computing and intelligence capabilities, while building a broader collaborative innovation and industrial ecosystem.

Why does it matter?

The plan shows China treating AI as part of the core architecture of future communications networks, not only as an application layer. The targets link AI, telecommunications, computing power and sensing infrastructure, which could shape how autonomous networks, industrial AI, smart cities and future digital services are deployed. It also reflects China’s broader push to align AI development with national digital infrastructure and industrial upgrading.

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