A Technical Blueprint For Zero-Trust AI Access To Public-Sector Data

Gopichand Mannava, a Forbes Councils member, proposes a zero-trust technical blueprint for AI access to public-sector data, emphasizing that agencies transitioning from AI-assisted reporting to AI-initiated action require a more defensible access-control architecture. The framework integrates identity verification, continuous monitoring, and least-privilege principles to secure sensitive government datasets.