Public sector AI readiness: closing the gap between ambition and execution in Europe

Politico Europe · Feb 23, 2026 · Collected from RSS

Full Article

Across Europe, governments are moving quickly to harness the potential of artificial intelligence. National strategies are being announced, innovation hubs funded, and pilot programs launched. From healthcare to taxation, I have seen how AI is emerging as a powerful lever to enhance public services and strengthen Europe’s global competitiveness. The urgency is political and practical: Europe’s ageing population, and economic pressure are squeezing budgets. Citizens expect faster, simpler services. In this context, departments are looking for targeted AI uses that reduce manual workload and improve service quality without adding risk or cost. However, progress is uneven. Many organisations are still at trial stage. Capgemini research shows that nearly 90% plan to explore, pilot or implement agentic AI within the next two to three years, while EU institutions and member states are committing billions to digital transformation centered around AI. Only 21% of public sector organizations have advanced beyond experimentation to pilots or actual deployment of generative AI. Now, the focus must shift from ambition to readiness. The practical blocker is not enthusiasm: it is whether data is accurate, shared when needed, and safe to use. Here Europe has a unique opportunity to lead the way. A reality check for AI maturity Many organizations still lack the basics that make AI useful: up‑to‑date data, clear ownership, and simple routes to share information across teams. Fewer than one in four organizations globally report high maturity in these fields. For civil servants, this often translates into small teams juggling operational delivery with transformation agendas, learning new tools on the job, and managing risk without clear playbooks. This gap matters. AI initiatives built on fragile data foundations may face risks such as inefficiency, bias, and security vulnerabilities, which can erode trust in automated decisions, both internally and with citizens. Strengthening public sector data is therefore not only key to enabling AI, but also essential for improving the accuracy, efficiency and reliability of government decision-making. Getting the basics right also helps deliver “once‑only” service patterns so citizens no longer need to repeatedly provide the same information to different authorities, in line with the ambitions of the Interoperable Europe Act. The readiness gap Europe is not lacking in ambition. Progress is underway, but common challenges remain: data silos between agencies, varying quality standards, unclear governance for data sharing and legacy systems that limit interoperability. Cultural hesitancy toward data-driven decision-making adds complexity, but it is not insurmountable. The good news is that these issues can be addressed with a strategic focus on data foundations, and practical steps that reflect how government works: small, safe changes; clear owners; and visible benefits to users and staff. When data is accessible, trusted, and well-managed, civil servants can share information confidently, driving innovation while maintaining compliance and security. As a board member of DIGITALEUROPE, I see this growing momentum across countries and sectors to make data a strategic priority. Europe can lead the way in scaling AI responsibly and delivering smarter, more efficient public services for citizens. Four pillars: the foundations of public sector AI Governments cannot buy their way into AI readiness. They must build it through sustained investment in four interconnected pillars. First, data sharing. Solving complex public sector challenges with AI depends on information flowing safely across organizational boundaries. In practice, this means making it easier for departments and agencies to reuse data that already exists. While most public sector organizations have initiatives underway, only 35% have rolled out or have fully deployed data-sharing methods. Programs like Europe’s Common European Data Spaces show what is possible: secure, trustworthy environments for collaboration that benefit both organizations and citizens. Second, data control and sovereignty. Concerns about compliance and control are a daily reality for public sector leaders, and they are slowing AI adoption. More than half of public sector organizations are concerned about AI sovereignty, and these concerns are actively hindering wider adoption of generative AI. Compliance with data-localization laws and control over sensitive information become more complex when AI services are hosted in foreign jurisdictions. A 2024 European Commission report found that 80% of Europe’s digital technologies and infrastructure are imported. It is no surprise that sovereignty concerns are fuelling efforts to strengthen digital autonomy, from national cloud strategies to proposals such as the EuroStack initiative, which envisages €300bn of investment over a decade. Third, a data-driven culture. This is a critical pillar of AI readiness. True data mastery requires more than tools – it demands leadership, collaboration, and trust in data-based decisions. Setting clear targets, aligning strategy with operational reality, and encouraging collaboration and shared behaviors across teams helps embed data use into everyday work, rather than treating it as an added burden. Fourth, data infrastructure. Robust, cloud-based data infrastructure is essential for storing, processing and analyzing data at scale, while respecting sovereignty requirements. Today, the lack of such infrastructure is the primary obstacle to effective data use. Only 41% of public sector executives say they can access data at the speed required for decision-making. Budget constraints are a real barrier, but they need not be paralyzing. By focusing on gradual, outcome-driven improvements rather than costly overhauls, organizations can demonstrate value and secure further investment. Public sector organizations such as the City of Tampere illustrate this four-pillar approach. By building data foundations gradually and strategically, while addressing data sharing, sovereignty, culture and infrastructure together, Tampere has shown how thoughtful investment can deliver tangible results without losing sight of long-term ambition. From ambition to execution AI can transform the public sector, but only if data readiness becomes the true measure of digital maturity. The next phase of public sector modernization in Europe will be defined not by who announces the boldest AI strategy, but by who builds the strongest data foundations. By investing in governance, interoperability, culture, and infrastructure today, Europe can lead the world in responsible AI, turning ambition into impact and delivering smarter, more trusted public services for every citizen. Disclaimer POLITICAL ADVERTISEMENT The sponsor is Capgemini The ultimate controlling entity is Capgemini More information here. The above column is sponsor-generated content. To learn more about our advertising solutions, click here.