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

The government is increasingly deploying Gen AI and domain-specific AI applications, besides 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 Singaporean organizations expecting AI to account for over 7% of annual IT budgets by 2027, up from 5% 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 20% of the country’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 Singapore, public sector organizations continue to face foundational data challenges that constrain transformation efforts. 

  • These organizations realize investing in data modernization can help improve decision making, enable targeted policy outcomes, and make public service delivery efficient. 
  • 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 Singapore public sector continues to strengthen the data ecosystems that support AI adoption. 

A significant share of Singaporean public sector organizations is already deploying AI 

In parallel, a select group of front-runners is standing out, through stronger alignment of leadership, governance, workforce strategy, and data modernization efforts.  

  • 17% have reached front-runner status, while nearly one in three organizations qualify as AI enablers.  

Singapore’s public sector has also made measurable progress in its data mastery journey. 

  • More than half of organizations now qualify as data front-runners, higher than the global benchmark. Meanwhile the share of data-novices has decreased to 3%. AI adoption is acting as a catalyst for improvements in data foundations. 

Going forward, Singaporean 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.