Public financial management (PFM) is the backbone of effective governance. It encompasses how governments raise revenue, allocate resources, and control expenditure. A failure in PFM—whether through inefficiency, misallocation, or corruption—directly undermines public trust and service delivery. As governments contend with increasingly complex budgets and heightened scrutiny, artificial intelligence is emerging as a potent tool for Supreme Audit Institutions (SAIs) and finance ministries. However, its value is conditional not merely on predictive accuracy but on a less celebrated quality: explainability.

The integration of artificial intelligence into government is no longer a speculative future but a present-day operational reality. From optimizing public transit routes and triaging social welfare applications to assisting in judicial risk assessments, algorithms are increasingly mediating the relationship between citizens and the state. Yet the adoption of these tools remains fragmented. For every celebrated pilot project, there are many more that stall before achieving institutional scale. The challenge for policymakers, therefore, is not simply to procure AI but to build the governance architecture that allows for its safe, effective, and legitimate integration.