AI adoption across the public sector in the Middle East is accelerating ahead of the global standards.

With organizations moving beyond experimentation and exploring a wider range of use cases, scaling however remains a challenge in some cases.

The Middle Eastern governments are increasingly deploying Gen AI and domain-specific AI applications, alongwith exploring more advanced capabilities in agentic AI and AI-enabled service orchestration. Adoption is strongest in operational and analytical functions where outcomes are measurable and risks are lower. Common applications include fraud detection, administrative automation, citizen engagement, and decision support.

AI investment continues to grow, with the region’s public sector organizations expecting AI to account for 6-7% of annual IT budgets by 2027, up from 3.8-5.7% in 2025. However, governance maturity has not kept pace with deployment, with many organizations lacking standardized frameworks, accountability mechanisms, and benefits-tracking processes.

Despite growing adoption, only 23% of the region’s organizations surveyed report successfully scaling AI initiatives. Long-term success will depend on coordinated operating models, workforce readiness, and robust governance structures – not technology investments alone.

The government recognizes that fulfilling AI ambitions depends on data-readiness

In our 2025 research, we examined how global governments were establishing the necessary foundations for data. This year, we see that these governments are increasingly viewing data as a strategic asset underpinning modernization, service delivery, and organizational resilience. Yet in the Middle East, public sector organizations continue to face foundational data challenges that constrain transformation efforts.

  • These organizations realize investing in data modernization can help enable targeted policy outcomes, make public service delivery efficient and cost-effective, and improve decision making.
  • However, data quality and accessibility issues continue to limit the ability to scale AI and generate trusted insights.
  • Legacy systems, siloed architectures, and poor interoperability increase transformation complexity and slow implementation.

Even so, the region’s public sector continues to strengthen the data ecosystems that support AI adoption.

The Middle East stands out globally as AI and data maturity rises

A sizeable group of organizations are demonstrating that successful AI adoption depends on organizational readiness and execution discipline.

  • Nearly one in four public sector organizations qualify as AI enablers, while nearly one in three have reached front-runner status. Front-runners distinguish themselves through stronger alignment of leadership, governance, workforce strategy, and data modernization efforts.

The Middle East’s public sector has also made measurable progress in its data mastery journey.

  • Nearly two in five organizations now qualify as data front-runners, higher than the global benchmark. AI adoption is acting as a catalyst for improvements in data foundations.

Going forward, AI leadership will increasingly depend on organizational readiness, cross functional coordination, and institutional adaptability. Organizations that fail to strengthen operational readiness risk struggling to translate AI investments into meaningful public value and service transformation

Recommendations – reinventing public services through data and AI mastery

To scale data and AI effectively, public sector leaders should focus on the following priorities:

• Chief Executive Officer (CEO)/Chief digital officer: Drive mission-led transformation, citizen-centric services, trust, and public value.

• Chief data officer: Enable data quality, governance, sharing, interoperability, and enterprise trust.

• Chief information officer (CIO)/Chief technology officer (CTO): Provide the architecture, platforms, infrastructure, and resilience required for scale.

• Chief AI and analytics officer: Embed AI into operations through governance, reuse, evaluation, and outcome-driven scaling.

• Chief information and security officer (CISO): Embed cybersecurity, privacy, resilience, and AI risk management across data, platforms, and AI systems.

Explore the path to data and AI at scale. Download the research brief now.