Public sector leaders across the globe are moving from exploring artificial intelligence (AI) toward implementation, with agentic AI becoming an increasing area of focus. A study commissioned by Dell Technologies and conducted by International Data Corporation found that 71% of government decision-makers believe agentic AI could accelerate AI adoption in government operations.
The findings come as public sector organisations address workforce shortages, skills gaps, and ongoing modernisation efforts. As a result, decision-makers are placing greater emphasis on the conditions and requirements surrounding AI deployment.
Agentic AI and Workforce Operations: The study found that 51% of leaders plan to invest in agentic AI within the next 12–18 months, with organisations considering autonomous systems for administrative and analytical tasks alongside existing workforce responsibilities.
Skills Gap Challenges: Around 66% of public sector organisations reported that technology is evolving faster than workforce capabilities, contributing to operational and skills-related pressures.
Conditions for AI Adoption: Approximately 44% of respondents said stronger safeguards, including data security, privacy, and sovereignty protections, would influence the pace of AI adoption.
Public-Private Partnerships: The research found that 61% of leaders view public-private partnerships as important for accessing the expertise and technology required for AI implementation.
From Exploration to Deployment: The findings suggest governments are increasingly focused on the practical requirements for deploying AI systems at scale. The study indicates that confidence in infrastructure, governance, and operational readiness may influence adoption timelines.
The report also found that 58% of government leaders identified sovereign data governance, data quality, and control as among the most important platform requirements for sovereign AI deployments, highlighting the role of data management and governance in implementation strategies.
For public sector organisations, AI deployment may require data sovereignty measures, privacy protections, governance frameworks, and supporting infrastructure from the outset. The study suggests these factors are likely to influence how governments approach agentic AI implementation at scale.
The findings indicate that agentic AI is becoming a near-term consideration for governments, with adoption shaped by infrastructure, governance, data sovereignty, and partnership requirements alongside broader operational objectives.
