80% Governments to Use AI Agents by 2028: Gartner

Gartner predicts that at least 80% of governments will deploy AI agents by 2028 to automate routine decision making, marking a major shift in public sector operations. The move is expected to improve efficiency, consistency, and service delivery at scale.

According to analyst Daniel Nieto, governments are under increasing pressure to embed AI into decision making processes. Advances in multimodal AI, conversational systems, 

and agentic frameworks are expanding what public institutions can automate and anticipate.

However, adoption challenges persist. A Gartner survey found that 41% of government organisations face siloed strategies, while 31% struggle with legacy systems, limiting the effectiveness of digital transformation efforts.

A key insight from the report is the transition from traditional AI governance to Decision Intelligence (DI). Instead of focusing only on models and data, DI emphasizes governing how decisions are designed, executed, monitored, and audited.

This is particularly critical in government, where transparency and fairness directly impact public trust. By making decision pathways explicit and auditable, DI ensures accountability in automated systems.

Gartner predicts that by 2029, 70% of government agencies will mandate Explainable AI (XAI) and Human-in-the-Loop (HITL) mechanisms for all citizen-impacting decisions. This ensures that automated decisions can be reviewed, challenged, and corrected when necessary.

The report highlights a shift in focus from efficiency to citizen trust and experience. Around 50% of respondents identified improved citizen experience as a top priority. As AI automates services, direct interaction with government may reduce, making trust in systems even more critical.

The findings signal a fundamental transformation in public sector technology. Governments are moving from process-driven systems to decision driven ecosystems, where AI augments human judgment rather than replacing it.

However, success will depend on balancing automation with accountability. Without strong governance, AI risks becoming opaque and eroding public trust.

Ultimately, the future of government AI will not be defined by how much it automates, but by how transparent, fair, and trustworthy its decisions are.