80% of governments will deploy AI agents for routine decisions by 2028
At least 80% of government agencies will use AI agents to automate routine decision-making by 2028, according to Gartner Inc. The shift reflects pressure on government technology leaders to embed AI into operations while maintaining public trust.
The expansion of multimodal AI systems has widened what public organisations can automate and anticipate. But adoption faces real obstacles. A Gartner survey of 138 government respondents found 41% cited siloed strategies as a barrier, while 31% pointed to legacy systems as key challenges.
"Technology modernisation alone has not resolved these issues," Gartner said in its analysis.
Decision intelligence replaces model governance
As AI moves from pilot projects into core operations, how governments oversee these systems must change. Traditional AI governance focused on managing models, data and algorithms. Decision intelligence (DI) shifts that focus to governing decisions themselves-how they are designed, executed, monitored and audited.
This matters in government because public legitimacy depends on transparency and fairness. When citizens cannot see how a decision was made, trust erodes.
Gartner predicts that by 2029, 70% of government agencies will require explainable AI and human-in-the-loop mechanisms for all automated decisions affecting citizen services. These safeguards let humans inspect decision logic, handle exceptions and appeals, and maintain accountability as automation expands.
Citizen trust drives investment
Efficiency remains important, but citizen trust is becoming the primary driver of digital transformation in government. Half of survey respondents listed improved citizen experience as a top three priority.
As AI for Government automates more services, direct contact with staff may decrease. That makes the reliability, fairness and transparency of automated systems even more critical to public confidence.
Decision intelligence allows governments to shift from reactive, process-driven interactions to proactive, personalised engagement. This approach reduces delays, improves consistency and builds perceived fairness-strengthening public trust even when direct human contact becomes less frequent.
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