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OECD calls for smarter regulation to boost competitiveness and innovation

The Organisation for Economic Co-operation and Development (OECD) has published a report on regulatory simplification, warning that excessive and fragmented rules can undermine competitiveness, investment, and innovation. The report, titled ‘Smart Regulations, Strong Business’, was approved and declassified by the OECD Regulatory Policy Committee on 18 May.

The report draws on the OECD’s Simplifying for Success surveys, conducted between July and September 2025 among governments and business organisations across OECD Members, accession countries, and the European Union. Responses were received from 34 jurisdictions, with the analysis also drawing on OECD regulatory governance data and discussions from a 2025 high-level symposium.

The OECD emphasises that regulation remains essential for market functioning, public health and safety, and transparent government processes. However, the report argues that the accumulation of rules and administrative requirements has created increasingly complex systems that are more difficult for businesses to navigate, comply with and adapt to.

Survey findings show that government respondents in 72% of participating countries and business organisations in 90% of countries consider current levels of regulation and bureaucracy to be excessive. More than three-quarters of business organisations also said full compliance is too costly, while many linked the regulatory environment to negative effects on competitiveness, investment, and innovation.

The report says regulatory burdens often stem from reporting, record-keeping, permitting, inspections, and fragmented rules, rather than solely from substantive policy goals. The OECD recommends targeting areas where regulatory burdens are greatest, streamlining administrative procedures through risk-based and digital approaches, and making rulemaking more future-ready through evidence-based policymaking, stakeholder engagement and stronger coordination.

Why does it matter?

Governments around the world are seeking ways to improve competitiveness and stimulate innovation while maintaining high standards of consumer protection, safety and market oversight. As regulatory frameworks expand, concerns have grown about the cumulative costs of compliance and administrative complexity for businesses.

The OECD’s findings contribute to broader debates on regulatory reform, highlighting the importance of balancing effective regulation with efficiency. The report also reflects growing interest in digital tools, risk-based approaches and evidence-driven policymaking as ways to reduce unnecessary burdens without weakening regulatory objectives.

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NHS England expands AI assistant rollout to more than 500,000 staff

NHS England will provide more than 500,000 clinicians and support staff with access to AI tools under an agreement to expand the use of Microsoft 365 Copilot across healthcare services. The rollout is expected to reach more than 500,000 staff by October 2026.

NHS England said the AI assistant can help staff draft documents, analyse data and reduce administrative workloads, enabling clinicians to spend more time on patient care. According to NHS England, the tools could save staff an average of around two working days per month.

The agreement follows a large healthcare trial involving more than 30,000 NHS workers across 90 NHS organisations. NHS England said the trial found that AI-powered administrative support could save an average of 43 minutes per employee per day, equivalent to approximately five working weeks annually.

Microsoft 365 Copilot is expected to support a range of functions, including clinical administration, ward management, medical secretarial work and broader operational and management tasks. Use cases include drafting patient letters, supporting discharge processes, analysing service data, building rotas, creating meeting minutes, drafting board papers, and assisting human resources, finance, and procurement teams.

Each NHS trust will receive a central allocation of licences based on organisational headcount, typically starting at around 2,000 Microsoft 365 Copilot licences. NHS England said the rollout forms part of broader efforts to improve productivity, reduce waiting times and support the government’s 10-Year Health Plan.

Why does it matter?

Healthcare systems worldwide are exploring how generative AI can reduce administrative burdens and allow medical professionals to focus more on patient care. Administrative tasks account for a significant share of healthcare workloads, making productivity gains particularly valuable in resource-constrained environments.

The NHS rollout represents one of the largest deployments of generative AI tools in a public healthcare system. Its outcomes could influence how other health services approach AI adoption, workforce productivity and the integration of AI into everyday clinical and administrative operations.

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UK launches AI skills and jobs initiative for young people

The UK government has announced a new package for young people entering the labour market as AI continues to reshape entry-level roles and career pathways. The package includes an Early Careers Jobs Alliance, AI bootcamps, and expanded technology training for students from disadvantaged schools, with AI bootcamps serving as a central route into paid apprenticeships for young people at risk of unemployment.

The Early Careers Jobs Alliance will bring together government, employers, trade unions and young people to examine how AI is changing entry-level employment and career development. Backed by £20 million in funding, the initiative will initially focus on the Digital and Technologies sector before expanding across all eight Industrial Strategy sectors, including advanced manufacturing, clean energy, defence, financial services, and life sciences.

The alliance will analyse how entry-level work is evolving, develop guidance for businesses on redesigning roles while preserving career pathways, and identify examples of good practice. An initial report is expected in autumn.

Through the TechFirst programme, at least 400,000 students from some of the UK’s most disadvantaged schools will receive support in AI and digital skills through training sessions, competitions, extracurricular activities and engagement with industry. The AI bootcamps are intended to provide a more direct route into work for young people at risk of leaving education or training.

The UK government will also pilot free AI bootcamps in Lancashire and Greater Manchester this summer for young people at risk of leaving school after GCSEs and entering unemployment. Participants who successfully complete the bootcamp will be guaranteed a paid AI apprenticeship with local employers, with a broader rollout across England planned if the pilot proves successful.

A separate pilot linked to the North East AI Growth Zone will launch in early 2027 for young people aged 18 to 24 who are not in education or employment. Participants will receive at least 6 months of hands-on AI training with companies including Accenture, Microsoft, and Sage.

Why does it matter?

AI is beginning to transform many entry-level and administrative roles, raising concerns about how young people will gain work experience and build careers in an increasingly automated economy.

The UK’s approach combines workforce planning, skills development and employer engagement to help ensure that AI adoption creates new opportunities rather than limiting access to employment. The initiative also reflects growing efforts by governments to align education and training systems with the changing demands of the labour market.

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China launches a major 6G pilot programme to accelerate future connectivity

China’s Ministry of Industry and Information Technology has launched a ministry-provincial collaborative pilot programme to advance 6G innovation and development.

The initiative is designed to support future commercial deployment of next-generation communications technologies and strengthen the country’s 6G industrial ecosystem.

The programme focuses on advancing frontier 6G technologies and deepening the integration of communications networks with AI, satellite internet, and wireless sensing. It will also accelerate research and development of 6G base stations, core network equipment, terminals, chips, and operating systems.

Pilot regions will test practical applications tailored to local economic priorities. Planned use cases include immersive communications, industrial manufacturing, embodied intelligence, low-altitude economic activities, and smart maritime operations.

The initiative follows China’s recent approval of trial spectrum in the 6 GHz band for 6G technology testing in selected regions. That approval was granted to the IMT-2030 (6G) promotion group to support 6G technology trials and validation.

China currently operates the world’s largest 5G network and is seeking to build on that infrastructure base as global competition shifts towards 6G. Authorities say future 6G networks could deliver major improvements in speed, reliability, latency, and connectivity across terrestrial, aerial, maritime, and space-based networks.

Why does it matter?

The pilot programme shows how China is moving from 6G research towards coordinated industrial testing and local application scenarios. By linking 6G with AI, satellite internet, wireless sensing, chips, operating systems, embodied intelligence, and the low-altitude economy, China is treating next-generation connectivity as part of a wider industrial and strategic technology agenda.

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Dutch study explores how to scale AI across government organisations

Dutch research organisation TNO has conducted an exploratory study examining how AI applications can be scaled across government organisations in the Netherlands. The study was commissioned by the Ministry of the Interior and Kingdom Relations because AI offers opportunities for public sector services and operations.

The study supports the Netherlands’ Digitalisation Strategy, which calls for a more proactive government role in the development and adoption of AI. One option under consideration is an AI scaling facility that would support the reuse and further development of successful AI applications, helping deploy them more quickly and across a wider range of organisations.

According to the study, scaling AI is not a linear or one-size-fits-all process. Depending on their goals, context, and partnerships, organisations may follow different approaches, including scaling within one organisation, replicating solutions across similar organisations, adapting them to new sectors or tailoring broad solutions to local needs.

TNO identifies seven approaches to AI scaling: scaling in, scaling out, scaling beyond, scaling together, scaling down, scaling up and scaling deep. The strategies cover internal adoption, cross-organisational reuse, sectoral adaptation, collaborative development, localisation, policy and standards work, and cultural or behavioural change inside organisations.

A related ‘Conversation starter’ has also been developed to help organisations assess AI scaling initiatives at the outset. The recommendations include treating scaling as a strategic decision, selecting an approach aligned with intended outcomes, addressing governance and organisational culture, reusing existing solutions where possible, investing in AI literacy and documentation, clarifying ownership and funding arrangements, and regularly assessing whether scaling remains desirable, feasible and legally appropriate.

Why does it matter?

Many governments are moving beyond AI experimentation and focusing on how successful projects can be deployed at scale. However, expanding AI use across public institutions often involves organisational, governance and cultural challenges that extend beyond technology itself.

The Dutch study highlights the need for structured approaches to AI adoption, emphasising reuse, collaboration and institutional capacity. Its findings could help governments accelerate AI deployment while maintaining accountability, effectiveness and compliance with legal requirements.

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Ireland launches fund for fact-checking and anti-disinformation training

Ireland’s media regulator, Coimisiún na Meán, has launched a funding call to support training in fact-checking, prebunking and debunking for journalists and media professionals during 2026.

The programme is aimed at graduate, early-career and mid-career professionals working in news and current affairs. Eligible activities include training courses, mentorship programmes, internships and collaborative projects designed to strengthen fact-checking and verification skills.

The fund forms part of the regulator’s Media Skills and Development Programme and supports objectives outlined in Ireland’s National Counter Disinformation Strategy. Applications are open to academic institutions, accredited bodies and representative organisations, including partnerships involving media organisations.

Minister for Culture, Communications and Sport Patrick O’Donovan said the initiative would help strengthen professional skills and support high-quality journalism. Applications are open until 2 July 2026, with all funded activities to be delivered in Ireland during 2026.

Why does it matter?

Fact-checking, verification and disinformation response skills are becoming increasingly important as journalists navigate rapidly evolving information environments shaped by social media, generative AI and coordinated influence campaigns.

By investing in professional training, Ireland aims to strengthen media resilience, support evidence-based reporting and enhance the capacity of news organisations to identify and counter misleading or false information.

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Cambridge researchers test AI-designed vaccine in human trial

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

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

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

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

Why does it matter?

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

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

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UN warns of AI’s growing environmental footprint

As AI continues to reshape economies, industries and daily life, a new report from the United Nations University (UNU) highlights the environmental challenges associated with its rapid adoption. While discussions often focus on greenhouse gas emissions linked to AI systems, researchers argue that the technology’s impact on water resources, land use and electronic waste deserves equal attention.

According to the report, data centres supporting AI applications could consume up to 945 terawatt-hours of electricity annually by 2030. Beyond electricity demand, AI-related water consumption could reach levels equivalent to the annual household needs of 1.3 billion people, while the land footprint associated with AI infrastructure may exceed 14,500 square kilometres.

Researchers note that environmental pressures vary significantly depending on the technologies and energy sources used to power AI systems.

The UN report also finds that routine AI use, rather than model training alone, accounts for a significant share of resource consumption. Everyday activities such as generating images, videos and text require substantial computing power, with image generation demanding significantly more energy than basic text-based tasks. Growing adoption may further increase total resource consumption despite improvements in efficiency.

Researchers note that the environmental costs of AI infrastructure are often concentrated in specific regions, while the benefits of AI are distributed more broadly across the global economy. Expanding data centres, rising electricity demand, increasing water consumption and growing volumes of electronic waste could place additional pressure on communities and countries already facing resource constraints.

The report calls for responsible AI development supported by greater transparency, sustainable infrastructure planning, international cooperation and governance measures aimed at keeping technological progress within environmental limits.

Why does it matter?

Debates about AI sustainability often focus on carbon emissions, but the report argues that water consumption, land use and electronic waste are becoming equally important considerations as AI infrastructure expands. These impacts could become increasingly significant as governments and companies invest in larger data centres and more powerful AI systems.

The findings also highlight the need for environmental considerations to be integrated into AI governance and infrastructure planning. As AI adoption accelerates worldwide, policymakers face growing pressure to balance technological innovation with sustainability and resource management goals.

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Canada launches AI for All national strategy to accelerate adoption and digital sovereignty

Canada has launched AI for All, a new national AI strategy aimed at accelerating AI adoption, strengthening digital sovereignty, and positioning the country as a leading AI economy.

Announced by Prime Minister Mark Carney, the strategy combines proposed legislation, investments, and programmes intended to ensure AI is adopted responsibly and benefits businesses, workers, students, and communities across Canada.

The strategy targets an additional C$200 billion in economic growth, 250,000 new AI-related jobs over the next five years, and an increase in AI adoption from just over 12% today to 60% by 2034. The government also plans to provide up to 90,000 AI-related jobs and work placement opportunities for young Canadians.

The strategy is built around three principles: building trust, creating opportunities, and reinforcing Canadian sovereignty. To build trust, the government plans to modernise digital legislation, strengthen protections for personal information, address harms such as deepfakes and surveillance pricing, introduce an online safety regime, and expand the capabilities of the Canadian AI Safety Institute.

To create opportunities, the government will establish a National AI Literacy Initiative, provide access to trusted AI agents for post-secondary students, help small and medium-sized businesses adopt AI, support worker training, and launch an AI Missions Program with a flagship health mission focused on diagnostics, patient care, and system efficiency.

To reinforce sovereignty, Canada plans to build domestic AI foundations, including compute, cloud, connectivity, data, and talent. Measures include a world-leading public AI supercomputer, investments in sovereign compute and cloud infrastructure, better access to growth capital for Canadian AI companies, strategic public procurement, and expanded support for AI talent.

The government said the strategy is intended to ensure more AI value is created in Canada while strengthening privacy, data protection, public services, productivity, and economic security.

Why does it matter?

Canada’s AI for All strategy links AI adoption directly to economic growth, workforce development, public trust, and technological sovereignty. The strategy reflects a wider shift among governments: AI policy is no longer focused only on research excellence, but also on compute infrastructure, cloud sovereignty, data governance, safety institutions, business adoption, public procurement, and skills. Its success will depend on whether Canada can turn ambitious targets into measurable adoption across businesses, public services, and workers.

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OECD launches AI Policy Toolkit for governments

The Organisation for Economic Co-operation and Development (OECD) has launched the AI Policy Toolkit, a practical guide intended to help governments translate AI principles into policy action. Released by the OECD under the Global Partnership on Artificial Intelligence, the first version is designed as a non-prescriptive resource for policymakers working across the AI policy cycle.

Building on the OECD AI Principles, the toolkit is intended to help governments identify policy priorities, compare international approaches and adapt guidance to national circumstances. The platform incorporates AI-powered semantic search to help users identify relevant policy examples and practical approaches drawn from real-world experience.

The OECD developed the AI Policy Toolkit through co-creation with end-users across regions, including targeted interviews and workshops in Southeast Asia, Latin America, and Africa. Policymakers, industry representatives and experts helped shape the platform around implementation challenges, including balancing innovation and regulation, addressing infrastructure gaps and supporting AI adoption in sectors such as agriculture, education and healthcare.

According to the OECD, the development process highlighted two key lessons: AI policy is heavily influenced by national context, institutional capacity and levels of digital maturity, while challenges such as advanced AI risks and linguistic and cultural representation often require international cooperation. Contributors included governments and organisations from Costa Rica, Italy, France, South Korea, Japan, the United Kingdom, the European Union, the French Development Agency, and the Inter-American Development Bank.

The OECD says the toolkit will continue to evolve through feedback, additional policy examples, and expanded coverage of emerging issues, including sector-specific guidance, infrastructure, and regulatory approaches. The OECD said the toolkit’s broader objective is to help governments move from high-level AI principles to practical implementation while managing risks and promoting trustworthy AI.

Why does it matter?

Many governments have adopted AI principles and strategies, but translating these commitments into practical policies remains a challenge. The OECD’s toolkit seeks to bridge that gap by providing policymakers with implementation guidance, real-world examples and policy options tailored to different national contexts.

The initiative also reflects growing recognition that effective AI governance requires both domestic policymaking capacity and international cooperation, particularly as countries confront shared challenges related to advanced AI systems, infrastructure needs and regulatory approaches.

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