When Productivity Becomes Surveillance (Thanks, AI)

Something tells me that this is going to become a very contentious topic that is going to tweak how many of us think about work and our responsibilities.

“The future of work will be based on trust.” We’ve heard this in business books, podcasts and articles on what makes a business shift from good to great. “Employee experience is now equally/more important than customer experience.” Another trope that landed hard during Covid and has been pushing harder since then. It’s also true that remote work gave people more flexibility… that leaders now focus less on presenteeism and more on outcomes… that employees are judged by the quality of their contribution instead of the number of hours they spent sitting at a desk. We talk about autonomy… culture… empowering people to do their best work wherever they happen to be… so it’s fascinating (and terrifying) to watch where some organizations now seem to be heading.

According to a recent CBC story, workers are raising concerns about software that tracks screen activity, browser usage, meeting participation and other digital signals as a way of measuring productivity.

This feels like a very different vision of the future of work… and while this isn’t really a story about workplace monitoring software… it is very much a story about management. Of course organizations should measure performance (KPIs are still a huge deal). And, yes, they should absolutely care whether people are productive and contributing. The question isn’t whether companies should measure work… the question is what they’re actually measuring… and what happens next. So, if you read the article and think this sounds more like 1984 than 2026… you are not wrong. The danger isn’t that your employer knows you spent 47 minutes in Excel. It’s that an AI system will soon interpret what those 47 minutes say about your value as an employee (and how you compare to everyone else).

Big idea (that seems simple enough): Screen time is not productivity.

A green Teams dot… mouse movement… time spent in a browser… none of these are indicators of value created/delivered. Some of the most valuable work any knowledge worker does leaves almost no digital trail at all. Reading… thinking… connecting ideas… solving problems… having difficult (or creative) conversations… walking around the block because you’re stuck… sitting quietly taking notes until something clicks. None of that is going to light up the software productivity dashboard. Screen tracking is creepy enough. Add AI, and suddenly the system isn’t just monitoring activity… it’s creating a theory of you. And that “theory” can quickly become a score… a prediction… a comparison… and eventually a decision.

And that’s where this story gets interesting/terrifying.

When companies don’t know how to measure outcomes, they start measuring behaviour. That’s not really a technology problem… it’s a management problem. The software simply makes it easier to “quantify” activity… so activity becomes the proxy for value. I made exactly this point during my radio conversation on iHeartRadio this week (listen in below): When leaders struggle to evaluate outcomes, they often default to measuring behaviour instead… and technology makes that temptation even stronger.

What do you think happens next?

Better employees… massive productivity gains? Nope. Once people know they’re being watched, they begin optimizing for what the system rewards. Stay online a little longer… keep the Teams status green… join one more meeting… wiggle the mouse… use AI tools to respond immediately. That’s performative work… not productive work. Plus, it’s really starting to stress them out (understandably). The risk becomes obvious (and immensely problematic)… we teach employees to optimize for appearances instead of impact (the wrong wrong thing).

The AI layer makes this even more interesting.

Today we’re talking about software that measures activity. Tomorrow those same systems will score employees… compare them… predict performance… recommend interventions (positive/negative) based on behavioural patterns. Once enough workplace data exists… AI won’t simply observe work, it will increasingly interpret it. That’s where my concerns really begin. Because now we’re not just asking whether the data accurately captures what someone did. We’re asking whether an AI can accurately infer what that activity means. It’s more than possible that organizations adopt surveillance because it’s easier than developing better managers and culture. But here we are… potentially building a future of work measured by how long someone’s laptop looks awake… and then synthetic agents manufacturing an opinion on what that must mean. We’ve spent years worrying about AI replacing workers… maybe we should also be worrying about AI becoming the manager that decides which workers are worth keeping.

Does anyone believe that this technology will be great at measuring the work that actually mattered?

This (and some other topics) is what Trudie Mason and I discussed on CJAD 800 AM.

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