Executive summary
Artificial intelligence (AI) has emerged as one of the defining drivers of productivity and growth for the next decade - the technology is changing how people work and how knowledge is created. Research carried out by AWS and Telecom Advisory Service, cited in last year's Unlocking Europe's AI Potential report, estimated that cloud-enabled AI could add $1.5 trillion to global GDP by 2030.
Regulatory fragmentation
Skills shortages
Challenging funding environment (with investment in AI held back by difficulty accessing funding pathways)
This report finds that Europe has many of the key ingredients needed to succeed: world-class research institutions, a strong industrial base, and a highly educated workforce. Europe’s tech sector has immense potential – currently worth nearly $4 trillion and boasting almost 40,000 funded tech companies (up from 13,000 in 2016). Access to a broad choice of open source and proprietary software from a mix of European and international providers (coupled with world-class infrastructure) puts Europe in a prime position to become a world leader in AI. Across businesses of all industries and sizes that have adopted AI, the technology offers improved innovation, efficiencies, and interoperability. Europe has the chance to pioneer a range of genuinely successful models of AI adoption and innovation. Businesses across different industries have the tools and resources to apply AI to a wide range of challenges in different ways.
While new challenges are also emerging, obstacles identified in our previous reports stubbornly remain, including:
The rapid pace of AI innovation is compressing decades of economic transformation into months. Accelerated AI deployment from other regions means that Europe risks missing out on its portion of the $1.5 trillion AI opportunity.
In this context, Europe must move at speed to identify its blockers and its accelerators and make bold commitments to support AI adoption. Achieving this will require policymakers to align their priorities more closely with the practical needs of European businesses and citizens.
This report shows how adoption is evolving, how prepared people and businesses are to use AI effectively, and how the wider environment – from skills and regulation to investment – is enabling or constraining progress. Taken together, they point to a continent moving quickly on AI uptake, but facing growing pressure on the conditions required to convert that momentum into long-term competitiveness.
Headline year-on-year changes | 2024 | 2025 | 2026 |
|---|---|---|---|
Business AI adoption | 33% | 42% | 54% |
Citizens who say they are using AI on a daily basis | 20% | 30% | 36% |
Citizens familiar with what AI is | 55% | 72% | 80% |
Citizens who have had any training in how to use AI | 19% | 31% | 31% |
Businesses citing skills gap | 39% | 40% | 44% |
Business % of AI spend on compliance | Not tracked | 40% | 42% |
Reported increase in tech investment by businesses | +21% | +24% | +26% |
The last year’s progress
Europe's AI journey
European adoption of AI is accelerating. However, even as uptake grows, progress into advanced use cases is not keeping pace, limiting the technology’s full potential to transform the continent’s economy and society.
In an increasingly competitive global AI era, rising adoption alone is not enough to secure a lasting edge. While the data shows clear progress on adoption, it also indicates that businesses are not yet moving from basic AI adoption to harnessing its most advanced uses:
The initial stage of AI uptake, when businesses are using AI primarily for incremental improvements such as efficiency gains and process streamlining rather than for innovation.
Intermediate state of AI adoption
When AI is supporting a more innovative customer experience alongside operational efficiency.
When firms are integrating the most advanced use cases of AI, combining multiple models, developing custom AI solutions, or using agentic and autonomous AI. At this stage, businesses are rapidly innovating with AI and, in turn, disrupting their industry.
The majority of European businesses are at the first, most basic stage of adoption. Unless more European businesses move beyond basic applications and deploy AI in advanced, transformative ways, Europe risks falling behind.
Year-on-year snapshot
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From 2025 to 2026, European business AI adoption has grown by 29%.
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Cloud adoption shows similar momentum: 68% of businesses in our survey now report using cloud technologies, up from 58% last year (a 17% growth rate).
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Together, these trends suggest Europe has the digital foundations required to compete in a technology-driven global economy.
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Businesses reported that they increased their AI investment by an average of 26% in 2026, signalling confidence in the technology's potential. Among high-growth startups, this figure rises to 35%.
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62% of businesses report that AI adoption is a priority for their business, rising to 66% among medium-sized businesses and 70% among large enterprises.
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22% of AI adopters are using AI's most advanced capabilities,[1] a small increase from 21% in 2025.
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There are signs of progress: due to increases in AI adoption, in real terms, this equates to over 1 million businesses progressing to the most advanced stage of adoption in the past year.
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Among experienced AI adopters,[2] this rises to 26% (vs. 22% overall) who are at the most advanced stage of AI adoption.
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However, to keep pace with innovation, Europe must move faster.
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The distribution of AI uptake among adopters remains uneven: 62% of large enterprises and 59% of SMEs remaining at the most basic stage of AI adoption compared to only 34% of startups.
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This divergence reinforces the continued emergence of a ‘two-tier AI economy’ where a small group of firms, largely startups, race ahead with advanced AI use, while most businesses (such as SMEs, mid-sized businesses, and large enterprises) remain stuck in basic applications and are unable to capture the full productivity and innovation benefits.
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42% on average of business tech budgets now goes to compliance, up from 40% last year.
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Businesses who report regulation as their main hurdle to AI adoption report that their top three regulatory concerns are complexity or a lack of certainty in the fields of cybersecurity (50%), data protection (47%), and intellectual property protection and commercialisation (42%).
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It is not only businesses that are increasing their adoption of AI – citizens are integrating AI in their day-to-day activities faster than many businesses and public institutions are adapting. Reported daily AI use by citizens has risen from 20% to 36% since 2024, and 80% of citizens now say they are familiar with AI, while 40% say that they have used AI chatbots in the past six months. This indicates that European businesses have access to a market of customers who are likely to be ready to engage with AI solutions.
At the same time, citizens’ priorities for public spending reveal a clear expectation: technology should strengthen essential services rather than become an end in itself. Healthcare (72%), defence and security (58%), energy security and the green transition (55%), and skills and education (51%) rank well above AI-specific infrastructure (8%) and Europe-based cloud infrastructure (6%). In other words, citizens want better outcomes – more efficient hospitals, stronger security, improved public services – not simply investment in technology. AI’s role, in their view, is to enhance delivery, productivity, and resilience in the areas that matter most to their daily lives.
What’s new this year
Europe now faces a critical choice. The continent is producing world-class AI startups and has crossed the threshold where more companies are using AI than not. However, persistent challenges threaten Europe’s future competitiveness and could widen the gap between the continent and faster-moving global competitors.
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The pace of innovation
AI and cloud technologies are now accelerating innovation cycles at unprecedented speed. While the move from dial-up internet to widespread mobile connectivity took a decade, the evolution of AI models and deployment of new usage methods such as agentic AI are evolving annually. This shift has fundamentally changed the nature of what it means to succeed in adopting AI technologies globally.
Regulatory fragmentation and complexity is becoming a competitive disadvantage
European businesses navigate 27 different regulatory frameworks on critical issues impacting AI adoption, including AI policy, cybersecurity, data protection, and business regulations, slowing down businesses precisely when speed matters most. The IMF estimates that cross-border friction inside the EU is equivalent to a 110% tariff.
Europe's best are considering re-locating to accelerate growth
Regulatory burden and market opportunities are beginning to reshape Europe’s ability to retain its most promising startups. 38% of startups, the very companies driving Europe's AI future, would consider relocating outside Europe to grow faster. Among the highest growth startups, which will be critical to Europe’s competitiveness, this rises to over half (51%).
Adoption must move from experimentation to advanced AI use. Companies at the experimenting stage report 40% productivity gains from their AI adoption, versus 62% for companies at the most advanced stages. Every month that businesses remain stuck in experimentation is a month of missed productivity, slower innovation, and weaker competitiveness with those at the most advanced stage of adoption 55% more likely to report productivity gains.
This is significant – helping basic adopters to reach advanced AI use could unlock €191 billion GVA for Europe.[3]
Regulatory fragmentation and complexity:
Despite simplification efforts, regulatory fragmentation continues to make scaling across Europe complex, costly, and uncertain for businesses.
The digital skills gap:
Skills shortages remain a primary challenge to AI adoption, with many businesses lacking the talent, workforce readiness, or capacity needed to implement and scale AI use effectively.
Access to funding pathways:
Unclear and fragmented funding and incentive structures limit businesses’ ability to move from experimentation to large-scale AI transformation.
Three structural challenges persist
Europe faces two critical risks if these challenges are not addressed
Competitiveness: Structural challenges prevent Europe from converting its strong foundations into sustained growth, productivity gains, and global competitiveness.
Founder flight: High-growth startups increasingly consider scaling outside Europe as a faster and more viable path to access capital, geographies, and scale.