KPMG tracks employee AI use
- KPMG rolled out an internal dashboard in its US advisory arm that tracks employee AI use, covering about 10,000 workers and surfacing peer comparisons. - The sharpest detail is the target: many consultants are expected to use AI on roughly 75% of working days, though staff say metrics can be gamed. - This matters because AI use is turning into a managed operating metric — not a perk — as big companies track costs, access, and payoff.
Consulting firms are turning AI into something they can count. Not just buy, not just praise in town halls — count. KPMG’s latest move makes that plain: it built an internal dashboard for its US advisory business that shows how often employees use AI tools, how that stacks up against targets, and how they compare with peers. That sounds like a small workflow tweak, but it’s really a sign that AI has moved from pilot project to managed labor input. ### What did KPMG actually build? KPMG’s dashboard tracks AI use across its US advisory division, which covers roughly 10,000 workers. Employees can see their own usage, compare it with colleagues, and check it against internal benchmarks. Reports on the rollout say the system came online late in 2025 and is meant to push “frequent and sophisticated” use, not just casual experimentation. ### What’s the number everyone noticed? The standout detail is the target. Many workers are being pushed toward using AI on 75% of working days. That matters because it turns AI from an optional helper into an expectation with a measurable threshold. Once a company sets a number like that, adoption stops being cultural and starts being operational. ### Why would a firm want this? Basically, AI now costs real money at enterprise scale. Seats, tokens, model access, security controls, internal tooling — all of that has to be justified. A dashboard helps management answer simple but expensive questions: who is using the tools, where are they being used, and are those licenses paying at a company or individual level. ### Is this about productivity or surveillance? It’s both, and that’s the tension. KPMG frames the dashboard as a way to improve work quality and understand where AI actually helps. But from the employee side, once usage is visible and comparable, it also becomes a performance signal. Even if a company says it is measuring adoption rather than judging workers, people will read a leaderboard like a leaderboard. ### What’s the catch? The catch is that “AI use” is a messy metric. Employees quoted in coverage said the dashboard can be inaccurate or easy to game. That makes sense. If the system rewards frequency, workers can optimize for touches instead of outcomes — a bit like counting gym check-ins rather than actual fitness. A bad metric can still change behavior, and sometimes it changes the wrong behavior fastest. ### Why is consulting a natural place for this? Consulting firms sell leverage. If AI helps a consultant draft faster, summarize better, or prep client work more cheaply, the firm has a direct reason to measure that. But consulting also runs on utilization, comparability, and internal ranking. So once AI enters the workflow, it was almost inevitable that firms would try to benchmark it the same way they benchmark everything else. ### Is KPMG unusual here? Probably not. The bigger pattern is that large employers are no longer asking whether staff have tried AI. They’re asking how often, at what cost, and with what return. CNBC’s reporting says almost every Fortune 500 company is tracking AI usage in some form. KPMG just made the trend unusually visible. ### Bottom line? The important shift isn’t that one firm built a dashboard. It’s that AI use at work is becoming a managed metric, like software spend or sales activity. Once that happens, the conversation changes — from “should we use AI?” to “why aren’t you using it more?”
