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AI adoption across government is accelerating, with organizations moving beyond experimentation and exploring a wider range of use cases. However, scaling remains a challenge.

The Capgemini Research Institute’s latest report, Data and AI in government 2026, explores what successful public sector organizations are doing to transition from fragmented AI pilots to enterprise-wide data and impactful AI.

Key insights:

  • Only 28% of public sector organizations have successfully scaled AI initiatives
  • One in four organizations is now an AI front-runner with advanced AI maturity capabilities
  • Governments recognize that data readiness is critical to achieving AI ambitions
  • Digital sovereignty is becoming a top strategic priority for governments worldwide
  • Organizations are improving their data maturity, but further progress is needed to unlock AI at scale

The report examines trends in government AI adoption, data strategy, and digital transformation. It is designed to help public sector leaders make decisions around modernization, service delivery, workforce transformation, and responsible adoption of AI. Its findings are based on a global survey of 600 senior public sector organizations and interviews with government leaders.

How governments are scaling AI adoption

Governments are expanding AI adoption but struggling to operationalize it at scale.

Adoption of AI in a range of forms is growing, but only 28% of organizations report successfully scaling their initiatives, with governance not keeping pace. Growth has been mainly in measurable, lower-risk operations such as fraud detection, administrative automation, citizen engagement, and decision support.

Why data readiness matters for government AI

Governments recognize that fulfilling AI ambitions depends on data readiness.

Organizations increasingly view data as a strategic asset underpinning modernization, service delivery, and organizational resilience. However, data quality and accessibility continue to be constrained by legacy systems, siloed architectures, and poor interoperability.

AI front-runners in the public sector

A small group of organizations demonstrates greater AI maturity.

One in four organizations (“AI front-runners”) exhibits advanced capabilities, while the proportion of data front-runners has increased compared with 2025. These organizations align leadership, governance, workforce strategy, and data modernization to achieve operational readiness and public value.

Digital sovereignty and government data strategy

Digital sovereignty is rising as a strategic priority.

As digital sovereignty becomes increasingly important, governments are reassessing how capabilities are built, governed, and controlled. Data and cybersecurity are emerging as the leading concerns as organizations seek to balance innovation, resilience, security, and trust. Dependence on foreign technology providers remains significant.

Key recommendations for public sector leaders to scale data and AI

The report outlines five priorities for public sector leaders:

  • Drive mission-led transformation, citizen-centric services and public value.
  • Enable data quality, governance, sharing, interoperability, and enterprise trust.
  • Provide the architectures, platforms, infrastructure, and resilience required for scale.
  • Embed AI into operations through governance, reuse, evaluation, and outcome-driven scaling.
  • Embed cybersecurity, privacy, resilience, and AI risk management across data, platforms, and AI systems.

Learn how government organizations are advancing from AI pilots to scale deployment through stronger data governance, AI readiness, digital transformation, and operational maturity.

Download the Data and AI in government 2026 report to discover actionable strategies for building an AI-driven public sector.

Download your copy of the research brief

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Many public sector organizations aspire to be AI-driven, but AI can only be as effective as the data foundations beneath it.

Marc Reinhardt
Public Sector Global Industry Leader, Capgemini
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