By Mauro Macchi, Matt Prebble, Dominic King and Laura Ann Wright
Closing the competitiveness gap is a central pillar of the European economic reform agenda. AI has the potential to boost productivity—but too few companies are making bold, transformative investments. Regional leaders need to move faster: business capabilities—in areas such as data, cloud and talent—and the regional AI ecosystem must be strengthened to capture the opportunity.
If the European economic reform agenda had a patron, it would be Janus. Like the two-faced Roman god of transitions, Europe appears perennially stuck between the future and the past: forcefully acknowledging the need for change—but often struggling to fully do so. The advent of artificial intelligence (AI) presents a crucial opportunity to revive flagging regional productivity. Businesses and policymakers must move quicker if action is to match rhetoric.
The latest attempt to kickstart European competitiveness came last year from the former head of the European Central Bank, Mario Draghi. His report highlighted AI as a potential solution to Europe’s productivity malaise, citing the technology’s transformative power over industries from automotive and energy to life sciences. The European Commission picked up the baton, releasing the EU AI Continent Action Plan—a roadmap for Europe to become a global leader in the responsible and productive deployment of the technology.
AI is not a silver bullet, but when combined with human ingenuity, it could help mitigate key challenges such as high energy prices. The promise is a new era of productivity growth and greater resilience—both essential if Europe is to achieve ambitious economic, social and environmental outcomes. World-leading companies across the continent are already investing in AI to boost competitiveness. For example, Anders Romare, CIO & Senior Vice President, Digital, Data & IT at Novo Nordisk, told us: “The productivity gains we are beginning to see—for example in drug discovery—are simply irresistible”.
Slow on the uptake
However, our recent paper—Europe’s AI Reckoning: Reinventing Industries for a New Era—reveals many business leaders continue to take an experimental approach. Just 8% of the ‘strategic bets’ we studied—major, transformational and sector-specific generative AI investments embedded into the core of the company’s value chain—are being scaled in Europe. And more than half (56%) of the 800 large European organisations we surveyed have yet to scale even one.
The internal barriers to scaling that respondents identified range from breaking up data siloes and bringing together multi-disciplinary teams to security risks. These are compounded by perennial European challenges, including regulatory complexity, a lack of risk capital and the fragmented single market.
That said, we found pockets of strength in certain industries. In automotive, for example, 70% of companies have scaled at least one strategic bet (with most focused on enhancing product design and customer engagement). Aerospace and defence follows (63%), with companies focusing mostly on improving simulations—such as crash tests and aerodynamics—and providing in-use data analysis. As Graham Smith, head of AI, data science and innovation at NatWest explains, the full potential of AI will only be realised “when you’re completely rethinking the way your business operates.”
Size matters
Our analysis also revealed that size matters when it comes to AI. Nearly half (48%) of European companies with US$10billion+ in annual revenues have scaled at least one strategic bet, on par with their US counterparts but well ahead of smaller peers (US$1 billion- US$9.9 billion) in the region (31%). This is a concern given that the US is home to a third more large companies than Europe.
So, what are the largest companies doing differently? We built an index to gauge the development and deployment of AI capabilities—from talent and data governance to the use of foundation models—that make scaling strategic bets possible. These capabilities help organisations achieve value from AI investments by unlocking new ways of working that go beyond simply layering technology on top of current processes—rather, equipping organisations with the capabilities to reinvent for efficiency, democratise knowledge and enhance collaboration between humans and autonomous agents. The largest European companies score an average of 54 (out of 100), again equal with US peers; those in the revenue bracket right below score just 39.
These capability gaps weigh on reinvention potential; for example, larger European businesses are 3x as likely to have integrated autonomous AI agents into various functions. There are clear frontrunners in automotive (scoring 57 out of 100) and aerospace and defence (52), while significant opportunities to build the capabilities necessary to scale AI exist in sectors such as industrial—which contributes more than a quarter of European output—and those providing critical infrastructure, such as energy, telecoms and utilities.
Sovereignty rules
The onus clearly falls on companies to invest in AI—to open the door to new ways of working in which processes are reinvented for efficiency, knowledge is democratised and collaboration between autonomous agents and people is seamless. The end-goal is reaching a ‘cognitive digital brain’—a central nervous system for enterprise decision-making and continuous learning that organises, processes and acts on data about businesses and the wider world in real-time.
It’s a vision that will not only require business leaders to upskill their people at scale—but also to recognise that the flipside of continuous technological transformation is greater exposure to external threats such as unauthorized access and cyberattacks. Building a secure digital core to reduce vulnerabilities, redundancy and technical debt is therefore critical.
Another requirement is how to reimagine Europe’s AI ecosystem as geopolitical risks grow. We’ve seen a clear mindset shift since the recent imposition of US tariffs, as companies look to balance critical technology dependencies in terms of control, cost and innovation. To build resilience, European companies should adopt a three-layered decoupling approach that factors in data workload sensitivities:
- Architectural: Use sovereign/private cloud for critical workloads to regain control over data.
- Legal: Operate with European and global trusted entities to reduce exposure to extraterritorial laws.
- Supply chain: Maximise open-source solutions to reduce dependence on proprietary software.
That said, individual company actions will only take Europe so far. Leaders across the public and private sectors need to jumpstart the development of a robust, competitive AI ecosystem that avoids duplications and creates more synergies across major countries. This should focus on the following priorities:
- Help smaller companies level up on AI: Smaller organisations need access to more compute capacity and high-quality data, as well as the funding advice, networking and training to boost adoption of sector-specific AI solutions.
- Nurture a sovereign European AI ecosystem: Foster work with European cloud providers and AI producers, while enabling access to innovation from trusted global players as they develop sovereign solutions and local legal entities.
- Develop a coordinated industrial strategy: A federated AI ecosystem—underpinning a competitive and values-driven AI economy—should be grounded in interoperability, cross-industry and cross-border collaboration and regulatory alignment.
How Europe rises to the twin challenges of shifting geopolitics and maximising AI potential will shape its growth trajectory in the coming years. Larger companies must embrace AI faster—and smaller peers must follow their lead. It’s time to turn principles into action and create a resilient, inclusive, innovative AI ecosystem.
The current market turmoil presents a fresh, immediate opportunity to accelerate the Europe’s economic reform agenda. Janus—also the god of beginnings—would doubtless approve.
Mauro Macchi
Matt Prebble
Dominic King
Laura Ann Wright
