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How many chatbot conversations took place? How many AI prompts were generated? How many hours were saved? According to Snowflake Field CTO Fawad Qureshi, none of those questions really matter if public services themselves are not improving.
Posted 21 July 2026
Imagine renewing your passport online. You probably don’t care whether AI helped process the application. You care whether it arrived before your holiday.
The same is true when booking a GP appointment, applying for planning permission or waiting for a benefits decision. Citizens rarely judge public services by the sophistication of the technology behind them. They judge them by whether those services are fast, reliable and easy to use.
As governments accelerate their adoption of AI, however, there is a danger that organisations begin measuring success by the technology itself rather than the outcomes it delivers.
“People want to talk about the number of copilots, the number of prompts, summaries, documents generated or AI adoption rates,” said Fawad Qureshi, Field CTO at Snowflake. “So what? Is the citizen’s life improved? That’s the outcome that needs to be there.”
Instead of asking how much AI the government is using, he believes public sector organisations should ask a much simpler question: are citizens receiving better public services?
Technology has always had its own language for measuring success. Software developers were once judged by how many lines of code they wrote. Later came metrics such as GitHub pull requests and story points. Today, AI has introduced a new set of numbers to celebrate, from chatbot conversations and prompt volumes to token consumption.
But bigger numbers do not necessarily mean better outcomes.
Qureshi points to reports of one organisation allegedly spending hundreds of millions of dollars on AI tokens after encouraging widespread use without sufficient controls as an example of how quickly activity can become disconnected from business value. The problem was not AI itself, but measuring success through consumption rather than outcomes.
Economist Charles Goodhart famously observed that “when a measure becomes a target, it ceases to be a good measure.”
Qureshi believes the same principle increasingly applies to AI. Once organisations begin rewarding activity rather than results, people inevitably find ways to optimise the metric instead of the outcome.
For government, that could mean reporting impressive adoption statistics while missing the question that matters most: has the service actually improved?
Government departments understandably need ways of measuring digital transformation: cloud migrations completed, services moved online, AI assistants deployed or documents summarised. Each provides evidence that change is taking place.
The problem, said Qureshi, is that citizens never experience those metrics directly.
“When I want to renew my passport, I want it immediately. I want the ambulance to arrive on time. I want my taxes refunded without problems. I want benefits processed,” he said. “That’s what matters.”
He illustrates the point with an Urdu proverb: “Eat the mangoes, don’t count the trees.”
In other words, citizens care about the outcome – not the process used to deliver it.
The NHS already offers useful examples of what meaningful measurement looks like.
AI is increasingly being used to help clinicians identify conditions such as cancer and stroke from medical images. Yet the number of scans processed tells only part of the story.
“If AI is processing one million scans in a year, fantastic,” said Qureshi. “But the outcome is whether patients receive faster diagnosis, earlier treatment and better care. Were there fewer false positives and fewer false negatives?”
The same principle applies across government. Rather than measuring chatbot conversations, organisations could measure first-contact resolution. Rather than celebrating automated case handling, they could track how quickly planning applications are approved. Rather than reporting AI adoption rates, they could focus on citizen satisfaction, consistency, fairness and waiting times.
These measures are undoubtedly harder to collect than technology statistics, but they reflect the experience of the people public services exist to serve.
Governments around the world are under pressure to demonstrate progress on AI. New pilots, new assistants and new digital services all provide visible evidence of innovation.
But Qureshi believes AI should remain firmly in the background.
“Government should not compete on how much AI it is using,” he said. “It should compete on how well citizens are served.”
The distinction matters because AI is not the objective of digital transformation – better public services are.
“AI is a means to an end, not the end,” he said.
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