Making AI work for the D9+ countries 

Ipsos has released a new report, commissioned by Google, which: examines the scale adoption of AI across D9+ Member States, explores the barriers to further adoption, and makes recommendations for supporting adoption. The D9+ is an informal group of member states consisting of the 13 most digitally advanced countries of the EU, namely Sweden, Finland, Denmark, Belgium, the Netherlands, Spain, Portugal, Poland, Czechia, Slovenia, Estonia, Ireland and Luxembourg. 

Key Findings:

How far is the D9+ capturing the AI opportunity?

• The D9+ is leading overall adoption in Europe, but small-business AI adoption lags large firms by over 50% across most D9+ countries (ranging from 75% vs 37% in Denmark, to 46% vs 6% in Poland for 2025). In most cases, this gap is widening (for example, in Poland, 13% more large firms adopted AI in 2025 vs 2024, whereas the increase was only 2% for small firms).
• Most adoption growth is coming from digitally mature sectors like ICT (which reaches 87.9% of firms in Sweden), while employment across the D9+ is far more concentrated in labour-intensive sectors, such as wholesale and retail, that lag in adoption.
• Many organisations are using off-the-shelf products or piloting, not deeply embedding AI. For instance, 60% of businesses using AI in Spain remain in an experimentation phase, while only 6% report significant use. 

What is holding the D9+ back from greater AI adoption?

• Unclear ROI: Organisations struggle to estimate the business case and financial returns for implementing AI.
• Lack of AI Expertise & Literacy: There is a widespread shortage of both specialised technical skills and foundational AI understanding among workers and leadership.
• Security & Data Risks: Fears of cyberattacks, data privacy breaches, and accidental leaks are major deterrents.
• Regulatory Complexity: Overlapping legal frameworks create uncertainty, restricting firms to only the most low-risk use cases.
• Significant Trust Gap: Distrust in the accuracy and reliability of AI outputs, coupled with workforce fears about job displacement and surveillance, actively stifles adoption.
• Lack of Organisational Readiness: Many firms lack the foundational digital infrastructure, data governance, and strategic leadership required to deeply integrate AI tools alongside legacy software. 

How can the D9+ build on its success in AI adoption?

• Make the case for AI: Business leaders, especially in SMEs, need to hear a positive story about AI's potential for value creation, coupled with reassurance that governments have been and continue to regulate to mitigate ethical and security risks.
• Explain the regulations: Governments should demystify and simplify existing regulations by providing clear, plain-language guidance, while proactively co-designing unified operational guidelines, and expanding access to regulatory sandboxes.
• De-risk the transition to scale: Recognising that workflow redesign carries financial and operational risks, governments must support firms by providing access to specialised technical expertise, high-performance digital infrastructure, and safe testing environments.
• Focus on literacy as well as skills: Implement a workforce strategy that addresses immediate leadership gaps in foundational AI literacy while maintaining a focus on developing highly technical skills and general skills. 

Technical note:

This report draws on a rapid evidence assessment of approximately 150 studies into AI adoption across the D9+ countries, and 18 semi-structured interviews with senior stakeholders engaged with AI adoption issues across EU Member States, including Belgium, Czechia, Denmark, Estonia, Finland, Ireland, Netherlands, Poland, Portugal, Spain and Sweden. Interviews were conducted between January and May 2026. All studies reviewed were published after 2024 to ensure relevance to recent trends in generative AI.