Agentic AI, physical AI, and advanced robotics – the next-generation of AI tools – represent a shift from tools that support work to systems that can increasingly plan, act, and execute across complex workflows.
These technologies reward speed, readiness, and strong digital foundations and they will amplify the gap between organisations that can scale quickly and those that cannot. Without decisive action, Europe faces a deeper divergence between a smaller group of advanced adopters while the broader economy risks being left behind entirely. In an era of compressed innovation cycles, this risk is no longer theoretical; uneven uptake of next-generation technologies will compound the two-tier AI economy identified in last year’s report.
The next wave of AI threatens to widen this divide
Awareness of agentic AI is increasing, but the gap between familiarity and deployment remains significant:
Less than a quarter of businesses (24%) say they have heard of agentic AI.
Of those who are familiar with the technology, only 3% report that they have fully deployed agentic AI, while 10% are experimenting or piloting the technology.
When the technology was explained, a further 59% say they have plans to use agentic AI or are considering it, while 17% say they’d have no plans to adopt it.
However, businesses that have adopted agentic AI are already realising benefits across their operations. Of those who have adopted, the average business was already able to identify at least two clear benefits as a result of this adoption, showcasing the transformative potential of the technology.
The specific benefits varied: 42% report faster decision-making and execution, 32% report increased operational efficiency or productivity, and 22% report improved scalability of operations. We are at the early stages of agentic AI – as the technology advances and adoption and use increase, these benefits will compound over time and be realised through more transformative use cases. The distance between early adopters and the rest of the economy is likely to widen.
While the potential is clear actual deployment of agentic AI remains concentrated among early movers. Among these early adopters, startups are once again disproportionately represented:
Only 19% of businesses overall say they feel fully or very ready to adopt the next-generation AI technologies, such as agentic AI, physical AI, or advanced robotics – in contrast to the 78% of startups who report they are ready. Midcaps[1] are also emerging in terms of next-generation AI readiness – they are twice as likely to be fully ready for next-generation AI than the national average.
41% of all businesses say they are only somewhat ready to adopt next-generation AI technology, and 33% say they are slightly ready or not ready at all.
The challenges preventing next-generation AI adoption mirror the broader challenges holding back Europe’s AI transformation and they are becoming more decisive as innovation cycles accelerate.
Unless these challenges are addressed, the next wave of AI is likely to deepen Europe’s emerging digital divide:
34% of businesses cite skills shortages as a hurdle to adopting next-generation AI technologies, while 29% cite insufficient internal financial resources.
22% cite legal uncertainty arising from AI and digital regulation, and a further 19% cite regulatory complexity operating across borders.
These challenges have real, measurable consequences: they slow AI adoption, stall progress into advanced use cases, and leave many organisations unprepared for the next-generation of AI technologies:
Skill shortages
Those citing skills shortages are 35% less likely to be at the advanced stage of AI adoption (17% vs 26%) and 39% less likely to report readiness for next-generation AI (14% vs 23%).
Insufficient internal financial resources
Those citing insufficient internal financial resources are 41% less likely to be advanced adopters (16% vs 27%) and 46% less likely to report readiness for next-generation AI (13% vs 24%).
Legal uncertainty
Those citing legal uncertainty are 42% less likely to be advanced adopters (15% vs 26%) and 48% less likely to report readiness for next-generation AI technologies (12% vs 23%).
As next-generation AI moves from frontier innovation to mainstream deployment, the countries and companies that close this capability gap fastest will define the next era of innovation. In practice, this creates an uneven landscape: organisations with the strongest digital foundations will accelerate rapidly, while others fall behind.
Europe’s momentum in AI is real and growing fast. Breakthroughs are no longer arriving every few years, they are happening every day, reshaping what is possible for organisations. The next phase of Europe’s competitiveness will be defined by who can convert innovation into measurable outcomes at scale – across businesses and borders. Success will belong to those who can deliver the fastest time-to-value, turning AI capability into operational impact in days rather than months, and driving sustained adoption.
At Mindflow, we see this shift firsthand. Our no-code agentic platform enables teams to automate everyday enterprise cybersecurity and IT workflows, keeping humans in control while AI systems execute complex tasks. Built on AWS with Amazon Bedrock, Mindflow gives organisations the flexibility to deploy powerful swarms of AI agents safely and securely in ways that match real operational needs.
Agentic AI is also changing the pace of execution. As AI moves from assisting people to acting alongside them, what once took months can now take days or even hours. This faster cycle is unlocking productivity, resilience, and innovation at levels we have never seen before, but only for organisations that can adopt and scale these technologies effectively. This acceleration not only enables users to refocus on activities that truly create value by automating repetitive and low-value tasks but also empowers them to accomplish what was previously impossible, unlocking new use cases and operational models that were out of reach without this level of automation and integration.
The organisations seeing real results with AI are not only investing in technology, but also talent and skills. Deploying systems that can act autonomously within business processes demands AI literacy across teams, strong operational foundations, and leaders who understand how to redesign workflows around human and agent collaboration. That’s why lowering the barrier to entry is critical: those who know business processes best, often non-technical experts, must have the autonomy to automate and create agents themselves. By empowering these domain experts, organisations ensure that automation truly reflects operational realities and accelerates practical innovation.
Choice matters just as much. Innovation moves fastest when businesses can access the best technologies available, combine tools freely, and switch models as needs evolve. Open frameworks give organisations the ability to scale across regions, adapt to new risks, and keep up with rapid innovation cycles. When flexibility is limited, progress slows and competitiveness suffers.
Policymakers play a vital role in enabling safe innovation at speed, supporting cross-border scaling, and preserving technology choice. But organisations must also evolve. Embedding AI into daily operations and strengthening human-agent collaboration is essential to unlocking sustained productivity gains. Only then can Europe fully capture the productivity gains of agentic AI and translate innovation into sustained economic growth.
Paul-Arthur Jonville
CEO
Mindflow