Pakistan’s National Artificial Intelligence Policy promises scale: one million trained professionals, thousands of trainers and scholarships, new centres of excellence, an AI fund, and wider use of the technology across government and industry. The federal cabinet’s July 30 approval gives the country an opportunity to set a standard that matters more than the number of courses, systems or pilot projects launched. Pakistan should require every consequential public-sector AI deployment to produce a simple public-service evidence record.
The need is immediate. The government recently launched an AI-based Prime Minister Office System designed to record, communicate, monitor and track directives from issuance through completion. That could make administration faster and more accountable. It could also create a new layer of automated opacity if officials cannot explain which recommendations came from software, who reviewed them, what information shaped them, and who remained responsible for the final action.
A public-service evidence record would answer those questions without publishing sensitive data or proprietary code. For each consequential AI-supported workflow, an agency should record five things: the task assigned to the system; the data categories it used; the official responsible for review; any material change made after human review; and the result, correction or incident that followed.
This is not a demand for another thick compliance manual. It is a compact operational record that can be adapted to risk. A low-stakes tool that sorts meeting notes may need only an internal owner and review rule. A system influencing benefits, procurement, hiring, policing, taxation, education or access to public services should require a stronger record, an appeal path and periodic independent review.
A system influencing benefits, procurement, hiring, policing, taxation, education or access to public services should require a stronger record.
Pakistan’s own AI direction supports this approach. The Islamabad AI Declaration calls for trusted governance, human accountability and measurable public value. The National AI Policy also links AI to better public services, employment and economic inclusion. Those goals cannot be evaluated through training totals or procurement announcements alone. They require evidence from the workflow.
Consider a government system used to prioritize citizen complaints. A dashboard might show that the system processed thousands of cases quickly. That does not show whether urgent complaints were identified correctly, whether some languages or regions were disadvantaged, or whether officials routinely accepted recommendations without checking them. A workflow record would make those questions answerable.
The same principle applies to the Prime Minister Office System. Tracking every directive can improve follow-through, but only if the system also makes responsibility clearer. Each directive should have a named human owner, a defined completion test, a record of material automated changes, and an explanation when the system’s status conflicts with facts on the ground. Otherwise, digital tracking may simply give weak implementation a more polished interface.
Evidence records would also protect public servants. Employees often become the hidden shock absorbers of new technology. When a system produces a bad recommendation, the person at the end of the process is expected to fix it, often without time, authority or a clear escalation route. A documented workflow establishes who must review outputs, when an employee may override them, and where recurring failures should be reported.
This matters for trust. Citizens are unlikely to be reassured by a generic statement that AI was used responsibly. They need understandable answers: What did the system do? Did a qualified person review it? Can a mistake be corrected? Who is accountable? A short evidence record can provide those answers more effectively than a broad ethical pledge.
It would also improve investment decisions. Pakistan is committing major resources to AI skills and infrastructure. Ministries need to distinguish tools that genuinely improve public value from tools that merely generate impressive demonstrations. Comparable records can reveal whether a system reduces delays, improves accuracy, broadens access, or simply moves work and errors elsewhere. The Pakistan Digital Authority could publish a model template and sector-specific examples. Procurement contracts could require vendors to support logging, human override, incident reporting and data-quality review. Agencies could publish aggregate findings while protecting personal and security-sensitive information. Parliament, auditors and citizens would then have a factual basis for evaluating performance.
The standard should be developed with public servants, not imposed on them after procurement. Frontline employees know where exceptions occur, which data is unreliable, and which apparent efficiencies create extra work downstream. Their participation would make the record useful rather than ceremonial.
Pakistan has already articulated an outcome-driven vision for AI. The next step is to turn that vision into routine administrative practice. Every important deployment should leave a traceable chain from system input to human judgment to public result. The country will not become an AI leader because it counts the most trainees or installs the most dashboards. It will lead when it can show that AI-supported decisions are more effective, more explainable and more accountable than the processes they replaced.