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Spain pushes for AI regulation to protect workers

Spain has called for stronger regulation of AI and algorithmic management in the workplace, arguing that digital technologies should strengthen workers’ rights rather than undermine them.

Speaking at the VI Ibero-American Ministerial Conference on Labour in Avilés, Spain’s Second Vice President and Minister of Labour, Yolanda Díaz, urged governments across the region to establish governance frameworks that ensure transparency, human oversight and the ethical use of AI in employment.

The conference focused on two priorities shaping the future of work. Ministers agreed on the need to professionalise, formalise and improve working conditions in the care sector, recognising its economic and social importance while addressing the precarious conditions faced by many workers, particularly women.

Delegations also examined the growing use of algorithmic management, stressing that governments should actively regulate AI to protect labour rights.

The meeting concluded with the adoption of the Avilés Ministerial Declaration and the Ibero-American Commitment on the Social and Solidarity Economy 2026–2030. Together, the documents establish shared principles on care work, algorithmic governance and labour rights while strengthening regional cooperation to promote inclusive economic development, quality employment and more resilient labour markets ahead of the XXX Ibero-American Summit in Madrid later this year.

At the same time, the commitment strengthens regional cooperation to promote inclusive economic development, quality employment and more resilient labour markets ahead of the XXX Ibero-American Summit scheduled to take place in Madrid later this year.

Why does it matter?

The conference reflects growing international concern that AI is reshaping the workplace faster than labour regulations are evolving. By calling for greater transparency, human oversight and accountability in algorithmic management, Spain is arguing that AI should improve working conditions without weakening workers’ rights or limiting human decision-making.

The adoption of shared regional principles also highlights how labour policy is becoming an increasingly important part of AI governance. As algorithmic systems play a larger role in hiring, scheduling, performance management and other employment decisions, governments are placing greater emphasis on ensuring that technological innovation remains aligned with fairness, inclusion and decent work.

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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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OECD explores AI-powered regulatory inspections

The Organisation for Economic Co-operation and Development (OECD) has published a working paper examining how data-driven regulation and digital technologies, including AI and data analytics, can help authorities carry out more targeted, risk-based and effective inspections.

The paper identifies licensing, permitting and inspections as the three pillars of regulatory delivery, arguing that these mechanisms are most effective when supported by risk-based approaches that minimise unnecessary administrative burdens while improving regulatory outcomes. The core argument is that by adopting risk-based approaches supported by technology, regulators can concentrate their efforts where they are most needed rather than applying uniform enforcement across all actors.

The OECD highlights practical uses for AI and data analytics, including identifying high-risk areas, prioritising inspections, streamlining enforcement and allocating resources more efficiently. The aim is to improve compliance while reducing unnecessary interventions for lower-risk businesses and activities.

The paper also argues that technologies can strengthen public trust in regulation by making inspections more transparent, consistent and evidence-based, improving both the effectiveness and legitimacy of regulatory enforcement.

The project forms part of broader EU efforts to modernise regulatory delivery. Drawing on Italy’s pilot experience, the OECD aims to identify lessons that can be applied across member states and other jurisdictions pursuing evidence-based regulatory reform.

Why does it matter?

The paper illustrates how AI and data analytics could help regulators move away from one-size-fits-all enforcement towards more targeted, risk-based oversight. By focusing inspections where they are most needed, authorities could improve compliance while reducing unnecessary administrative burdens, particularly for smaller businesses.

The report also reflects a wider shift towards evidence-based regulation. As governments seek to modernise public administration without weakening regulatory standards, technologies such as AI are increasingly being viewed as tools for improving both regulatory efficiency and public trust through more transparent and proportionate enforcement.

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Google says AI power users drive UK productivity gains

Workplace AI adoption in the UK has more than doubled over the past year, reaching 73%, according to a new Google report. However, the benefits remain uneven, with a small group of advanced users seeing significantly stronger career outcomes than the wider workforce.

The report categorises workers into four groups: AI Spectators, who have not yet engaged with the technology; Experimenters, who use basic AI functions; Practitioners, who use AI regularly; and AI Trailblazers, who apply it in advanced and innovative ways.

Although AI Trailblazers account for just 15% of users, they report significantly better outcomes, including faster promotions, larger pay increases and substantial weekly time savings.

The report found that advanced users outperform other workers across several indicators, including promotions, performance reviews and salary growth. However, differences in adoption across age, gender and geography suggest that unequal access to AI skills could widen existing labour market disparities.

Google argues that closing this gap will require greater investment in AI literacy, organisational support and workplace culture. Initiatives such as national upskilling programmes and diagnostic tools are intended to help workers progress from basic experimentation to more advanced AI use, supporting broader productivity growth.

Why does it matter?

The findings suggest that simply adopting AI is not enough to generate widespread economic benefits. The greatest productivity and career gains are concentrated among workers who integrate AI deeply into their daily work, highlighting the importance of skills development and organisational support.

The report also points to a growing policy challenge. If access to advanced AI skills continues to vary across demographic groups and regions, AI could widen existing inequalities in the labour market. Expanding AI literacy and helping more workers move beyond basic use may therefore be as important as increasing adoption itself.

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AI could reorganise 27% of EU jobs, OpenAI says

OpenAI Economic Research has published a report mapping how AI could reshape the European labour market across occupations and countries.

The report extends OpenAI’s AI Jobs Transition Framework to the EU, using Eurostat employment data and the European Skills, Competences, Qualifications and Occupations taxonomy to examine where AI may create growth, increase automation pressure, or change work organisation.

The framework identifies four occupational groups: roles that may grow with AI, occupations with higher near-term automation potential, occupations likely to reorganise and occupations with less immediate change.

Applied to the EU, the framework suggests that about 12% of employment is in occupations that may grow with AI, while about 14% is in roles with relatively higher near-term automation potential. Another 27% is in occupations likely to undergo workflow and skills changes, while 47% is in roles with less immediate change.

OpenAI said country-level differences are significant. Luxembourg, Sweden and the Netherlands have larger shares of occupations that may grow with AI, while Germany, Greece and Italy have larger employment shares in occupations with higher automation potential.

The company said the framework should not be read as a job-loss forecast, but as a planning tool for policymakers, employers, educators and researchers.

OpenAI said stronger labour-market monitoring, national readiness planning and better links between skills systems and AI adoption data could help Europe prepare for occupational transitions before they appear in headline employment statistics.

Why does it matter?

The report frames AI’s labour-market impact as uneven and occupation-specific, rather than a single economy-wide shock. That matters for policymakers because reskilling, education reform and labour-market support need to be targeted where transition pressure is likely to appear. The country differences also show that AI policy in Europe may need to reflect national labour-market structures rather than EU-wide rules.

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HP adopts OpenAI Frontier for enterprise AI

HP has announced a strategic partnership with OpenAI to integrate OpenAI Frontier across parts of its customer-facing services and internal operations.

The company said the partnership supports its broader future-of-work strategy, with an initial focus on customer experience, partner services, employee productivity and software development.

HP plans to use OpenAI Frontier to create a more consistent experience across its retail, partner, chat and voice channels, helping customers and partners resolve routine queries and complete workflows more efficiently.

The company said it is among the first global enterprises to adopt the Frontier platform. While specific use cases will evolve over time, the initial focus includes customer and partner tools, telemetry insights through the Workforce Experience Platform, employee productivity and software development.

These include customer and partner-facing tools, customer telemetry insights and reporting through HP’s Workforce Experience Platform, employee productivity and software development.

The partnership follows an evaluation phase that began in February 2026, during which HP assessed OpenAI Frontier’s technical capabilities, enterprise integration, security features and potential business applications.

HP said it also tested agentic capabilities during the evaluation. The company said the results led it to conclude that OpenAI offers models and agent-based capabilities aligned with its strategic priorities.

HP and OpenAI now plan to co-develop future use cases. HP said these will need to meet its enterprise standards, particularly around data integration, governance and security.

OpenAI said HP had already used OpenAI APIs and tools such as ChatGPT and Codex in early projects. The companies said the new partnership is intended to move beyond pilots toward broader enterprise deployment.

HP also linked the partnership to its broader AI hardware strategy, saying it is developing agentic AI devices and dedicated hardware designed to support continuous AI inference and integrate seamlessly into workplace workflows.

For AI workloads that require continuous inference, HP said it is building devices with dedicated hardware optimised to run agentic AI workloads around the clock.

HP also pointed to its Workforce Experience Platform, which is used to manage device fleets and provide telemetry insights across PCs, workstations, printers and collaboration tools.

HP said the partnership reflects a broader shift from isolated AI pilots to enterprise-wide deployment, with AI increasingly serving as an operating layer embedded across customer services, software development and business operations.

Why does it matter?

The partnership illustrates how large enterprises are moving beyond experimental AI deployments towards organisation-wide integration. Rather than treating AI as a standalone application, companies are increasingly embedding it into customer support, software development, employee productivity and operational workflows.

It also highlights the growing importance of enterprise AI governance. As organisations deploy increasingly capable agentic systems, success will depend not only on model performance but also on secure integration, data governance and oversight that ensure AI can operate reliably within existing business processes.

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Spain calls for stronger AI rules in labour relations

Spain’s Second Vice President and Minister of Labour and Social Economy, Yolanda Díaz, has called for stronger regulation of AI and algorithmic decision-making in the workplace.

Speaking at the University of Oxford, Díaz said the debate should no longer focus on whether AI should be used, but on how to organise its deployment so that labour rights and fundamental rights are protected.

She argued that AI and algorithms already influence recruitment, hiring, performance evaluation, promotion, contract changes, dismissals and pension-related decisions. According to Díaz, stronger oversight is needed to ensure transparency and accountability where algorithmic management affects workers.

Spain’s Rider Law was presented as an early example of algorithmic transparency in labour relations, requiring digital labour platforms to disclose information about algorithms that affect working conditions and access to work.

Díaz also criticised proposals to deregulate AI, arguing that technological development should serve the public good rather than concentrate power among a small number of technology companies.

Her intervention comes as the EU rules for high-risk AI systems in areas including employment are set to apply later than initially expected. The European Commission says these rules will apply from 2 December 2027 under the new AI Omnibus enforcement timeline.

Díaz said governments should actively shape how AI is used in the workplace through regulation and public policy, rather than leaving the future of work to market forces alone.

Why does it matter?

AI is increasingly used to manage recruitment, performance assessment, scheduling, promotion and dismissal decisions. Spain’s position places algorithmic transparency and worker rights at the centre of the European AI debate, especially as the EU’s employment-related high-risk AI obligations are delayed. The intervention also shows how member states may move ahead with stricter national rules when they believe EU-level protections are too slow or insufficient.

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ECB highlights gap between AI adoption and productivity

Firms across the euro area are increasingly adopting AI, but only a small share are integrating it deeply enough to generate meaningful productivity gains. Data from the European Central Bank’s SAFE survey shows that although more than 70% of firms report using AI in some form, only 7% have integrated it deeply into their core operations.

Firms that use AI intensively are more likely to embed it in core business processes rather than limiting it to routine or experimental tasks. They are also more likely to innovate, expand their product offerings and align AI investments with long-term growth strategies.

Competitive pressure is also driving deeper AI adoption, particularly among established firms responding to technologically advanced rivals. However, skills shortages, legacy systems and financing constraints continue to limit many companies’ ability to scale AI effectively.

Why does it matter?

The findings suggest that simply adopting AI is not enough to generate significant economic benefits. Productivity gains appear to depend on integrating AI into core business functions, innovation strategies and long-term investment plans rather than using it only for isolated or experimental tasks.

The survey also highlights structural challenges facing Europe’s digital transformation. Without investment in skills, financing and modern digital infrastructure, many firms may struggle to move beyond basic AI adoption, potentially widening the productivity gap between AI leaders and businesses that lack the resources to scale the technology.

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Microsoft and Europol disrupt Amadey and StealC malware infrastructure

Microsoft has disrupted more than 200 command-and-control servers linked to Amadey and StealC, two widely used cybercrime tools that support credential theft, fraud and ransomware attacks.

The company’s Digital Crimes Unit said the action targeted the shared infrastructure behind the two tools rather than treating them as separate threats. In the first two weeks of May, Amadey and StealC were linked to more than 140,000 infected computers worldwide.

Amadey is often used to gain access to devices, while StealC is used to steal passwords and sensitive information. Microsoft said the tools form part of a wider cybercrime supply chain in which specialised malware services help attackers turn initial access into fraud, ransomware, espionage or other operations.

Microsoft said investigators used AI, including Copilot, to analyse malware and identify connections between the two tools more quickly. The company said the analysis helped its legal team treat both malware families as part of a single conspiracy under the US Racketeer Influenced and Corrupt Organizations Act.

The action was carried out with Europol and industry partners, including ESET, BitSight, Lumen and Mitsui Bussan Secure Directions. Europol’s European Cybercrime Centre also investigated StealC as part of Operation Endgame, alongside European law enforcement partners and cybersecurity companies, including IBM X-Force and Proofpoint.

Microsoft said it has identified more than 18,000 victim computers since the start of the operation and is working with telecommunications providers to help protect affected users.

The company said findings from the case will feed into its Statutory Automated Disruption programme, which accelerates the removal of malicious domains and infrastructure.

Why does it matter?

The operation reflects a shift in cybercrime disruption strategy. Instead of targeting one malware family or service at a time, Microsoft and its partners focused on the shared infrastructure that allows criminal tools to work together. That matters because modern cybercrime increasingly operates as a modular supply chain: one tool gains access, another steals credentials, and other actors monetise that access through fraud, ransomware or espionage. The use of AI to accelerate malware analysis also points to how defenders are trying to match the speed and scale of cybercriminal operations.

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UK’s FCA rethinks AI oversight for financial services

The UK’s Financial Conduct Authority (FCA) is rethinking how financial regulation should operate in the age of AI, according to a speech by chief executive Nikhil Rathi.

Speaking at techUK’s Agents of Change: Generative and Agentic AI in Financial Services 2026 event, Rathi said financial services will be central to making the UK a world-leading AI economy. He said the sector can provide the capital, infrastructure, and trust needed for AI to scale across the wider economy.

Rathi said more than 80% of financial services firms are already using or adopting AI, shifting the policy focus from adoption to large-scale deployment. He said AI is challenging the assumptions on which markets and regulation were built, making it necessary to preserve trust, competition, and resilience as technology moves faster than existing frameworks can keep pace.

The FCA chief identified two major scaling opportunities. The first is agentic AI, which Rathi said could evolve beyond summarisation and task automation into systems capable of coordinating workflows and executing transactions.

In retail markets, Rathi said agentic systems could support smarter bill management, personalised investment strategies, and reduced friction. In wholesale markets, they could support liquidity management, trading workflows, and other market functions.

Rathi stressed that accountability for regulated activities and their outcomes must remain clearly assigned, regardless of the degree of automation. He said investors may be reluctant to delegate important decisions to systems they do not understand, making human oversight and consumer confidence essential.

Rathi also identified tokenisation as a second major trend shaping financial markets. Rathi said tokenisation could lower costs, reduce risk, and unlock new services by creating more automated and programmable infrastructure for agentic finance.

He noted that banks are already piloting tokenized deposits and said the FCA had approved Baillie Gifford, alongside Bank of New York Mellon, to launch the UK’s first natively tokenised authorised fund.

Rathi said rapid AI progress raises fundamental questions for regulation. He argued that legislation alone cannot keep pace with technological change, requiring the FCA to evolve from a traditional rule-maker into a regulator focused on continuous supervision, stewardship and resilience.

The FCA is exploring agentic AI as a ‘first responder’ to speed up wholesale market monitoring. Rathi said the regulator could use its technology, large datasets, and supervisory judgement to tackle market abuse faster.

He said traditional rule-making will still be needed in some areas, but will not work everywhere. The FCA’s role will increasingly involve both stewardship and supervision, helping firms and markets navigate technological change and acting before legislation catches up.

Rathi also said AI will change competition in financial services. He said AI can lower barriers to entry and allow challengers to grow quickly, while some incumbents may fall behind.

The FCA chief said the regulator’s role is not to protect incumbents, but to ensure competition works in consumers’ and the economy’s interests. He said the FCA expects to use system-wide powers more frequently as part of its regular toolkit.

Operational resilience was another major theme of the speech. Rathi said financial services increasingly depend on cloud providers, model providers, data providers, and other parts of the AI stack, creating both opportunities and risks for systemic resilience, market integrity, and financial crime.

He said fraud increasingly sits at the intersection of financial services, technology, and telecoms. UK Finance’s Annual Fraud Report suggests the UK lost almost £1.3 billion through payment fraud last year, with two-thirds of authorised fraud cases linked to social media sites and messaging platforms.

Rathi said frontier AI could further magnify risks. Faster and more capable models could help firms identify vulnerabilities and strengthen defences, but could also help attackers move more quickly.

Boards and leadership teams must understand these risks, he said. Firms need to map and govern dependencies on model providers and other third parties, as the Critical Third Parties regime becomes more important.

Rathi said resilience will increasingly become a national security and system-wide challenge. He said no single firm, regulator or sector will be able to see all risks, making better information sharing essential.

The FCA is supporting AI adoption through tools including its Supercharged Sandbox, AI Lab, and the AI Consortium with the Bank of England. Rathi said these initiatives are intended to help firms build, test, and scale AI safely in UK financial services.

He said the FCA will publish more work soon, including the Mills Review on how AI could reshape retail financial services and later guidance on good and poor AI practice.

Rathi concluded that the key question is no longer whether AI will reshape financial services, but whether the UK can become the preferred location for developing and deploying AI safely, responsibly and at commercial scale. He said regulation must support innovation while keeping markets competitive, resilient, and fit for technological change.

Why does it matter?

The speech signals a broader shift in financial regulation from static rule-making towards continuous supervision in response to rapidly evolving AI technologies. As agentic AI, tokenisation and frontier models become more deeply embedded in financial services, regulators are increasingly focusing on governance, operational resilience, competition and accountability rather than relying solely on traditional legislative approaches.

It also illustrates how AI is becoming a strategic issue for financial stability and economic competitiveness. By combining regulatory sandboxes, supervisory innovation and collaboration with industry, the FCA aims to encourage responsible AI adoption while managing emerging risks related to fraud, third-party dependencies, cybersecurity and market integrity. The UK’s approach may influence how other financial regulators adapt to AI-driven transformation.

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