On Monday, 20th October 2025, Prof. Dr. Muhammad Usman Ghani Khan, Chairman and Professor, Department of Computer Science University of Engineering and Technology, conducted a lecture on “Artificial Intelligence: Transforming Governance and Public Sector Management” to participants of the 38th Senior Management Course at the National Institute of Public Administration, Lahore.

Dr. Usman opened with the transformative potential of AI for the state, its ability to augment analysis, automate routine decisions, and improve the speed, accuracy and transparency of service delivery. He outlined the policy and institutional framework needed to harness these gains: clear national objectives, interoperable data standards, capacity in line ministries, procurement pathways for digital tools, and independent safeguards for audit and accountability.

Turning to applications, he illustrated use-cases across the public sector: predictive maintenance in energy and transport, risk-based compliance and revenue administration, demand forecasting for social protection, and case-triage in health and education. He highlighted citizen engagement through chatbots, grievance redress portals and personalised service journeys, noting that well-governed data can materially improve citizen experience.

To ground the discussion, Dr. Usman introduced the basics of AI, machine learning and deep learning, explaining data pipelines, model training and validation in accessible terms. He then addressed ethics and responsible AI, fairness, privacy, explainability, safety and human oversight, before mapping the regulatory challenges: bias and exclusion risks, opaque algorithms in high-stakes domains, cybersecurity, vendor lock-in, and public-sector capability gaps.

The session remained interactive throughout, with participants exploring implementation roadmaps, skills and procurement reforms, and mechanisms for continuous evaluation. Dr. Usman closed by emphasising disciplined execution: invest in people and data, start with high-value pilots, measure outcomes rigorously, and embed responsibility by design.