Should businesses use AI to monitor employee productivity or is that digital surveillance? | AI Insights | Lumman.ai

Here's a weird thought: if your company needs AI to tell you whether your employees are working, you don’t have a productivity problem. You have a trust problem disguised as a dashboard.

But let’s back up.

There’s been a gold rush lately around “AI productivity tools.” And on the surface, the promise sounds reasonable enough—use machine intelligence to help teams work more efficiently. Cool. Helpful. Maybe even necessary.

But peel back that promise and you'll find something much darker underneath.

Because in far too many cases, “AI productivity” doesn’t actually mean helping people do better work. It means watching them more closely.

Behind the glossy vendor decks, what we’re actually building is a digital panopticon—a workplace where software silently logs every keystroke, idle minute, tab switch, and Teams huddle, pretending that all this ambient surveillance adds up to a meaningful image of “performance.”

It doesn’t.

It adds up to paranoia.

When AI Becomes a Corporate Hall Monitor

Let’s be precise with terms here. Measuring productivity is not the same as measuring presence. But the most common AI-powered tools treat them as interchangeable.

Take Microsoft’s now-infamous “Productivity Score” — it initially tracked how often employees used tools like Outlook, Teams, and OneDrive, right down to the individual. It sounded like progress until privacy advocates (and employees) pushed back hard. Why? Because no matter how it’s framed, tracking tool usage isn’t insight—it’s surveillance dressed in a hoodie.

More time in an app doesn’t tell you anything about output. It gives the illusion of visibility, not understanding.

Same goes for tools that track mouse movements, keystrokes, or “idle time” [read: bathroom breaks]. They all operate on the assumption that physical activity is directly correlated with mental output.

That’s productivity by Fitbit logic. And it’s nonsense.

A brilliant strategist can stare out the window for 45 minutes and have a breakthrough. A mediocre one can look feverishly “active” in spreadsheets and Slack all day while moving nothing forward.

Productivity isn’t motion. It’s outcome.

And here’s where things get dangerous: the more you try to measure productivity via proxies like mouse jiggles and chat volume, the more employees adapt—not by working smarter, but by gaming the metrics.

Just ask any call center agent who’s figured out how to run video tutorials in the background to stay “active.” Or remote workers who discreetly tape something to a mouse to avoid being marked idle.

What you’ve built isn’t a data-driven team. It’s an anxiety playground with KPIs.

Meetings: The Theater of Productivity

Here’s the part nobody likes to admit: AI isn’t solving the real productivity problem because we keep asking it the wrong questions.

We obsess over whether people are working… while wasting hours in meetings that should’ve been a 4-sentence Slack post.

Let’s do the math:

A weekly “status update” meeting with 15 people costs 15 hours, every week. Multiply that by 52, and you’re looking at 780 hours of collective time.

If those updates already exist in your project tracker or company OKRs, congratulations—you’ve just donated three months of human potential to the calendar gods.

But the diagnosis shouldn't be “let's monitor who talks the most in meetings.” It’s: why do we keep having meetings that accomplish nothing?

The truth cuts deep—we use meetings to mask organizational insecurity. If you can’t explain your strategy in plain writing, you create rituals. You schedule syncs. You hold “alignment sessions.”

It feels like progress even if nothing changes.

If we actually applied AI to diagnose meeting inefficiency—surface which ones are redundant, flag cards where no new decisions were made, visualize cognitive-load patterns—it might do more for productivity than any mouse-tracking tool ever could.

But that requires a mindset shift: from authoritarian to intelligent.

Surveillance Is a Strategy for Leaders Who Don’t Trust Their Strategy

Let’s zoom out.

The companies most obsessed with productivity surveillance tend to be the ones with vague, interchangeable strategies. Their playbooks hinge on control, not clarity. They keep watch over workers because they don’t know what excellence looks like—or how to communicate it.

If you can’t articulate what success means in a role beyond “reply quickly and attend meetings,” you don’t have performance management—you have vibes.

And when vibes are all you’ve got, AI looks like a lifeline. Dashboards! Heatmaps! Influence scores! But those become a crutch, not a compass.

Some of the most productive people I know spend hours staring into space, connecting dots in their heads. Others disappear for chunks of time and return with a two-pager that reframes how the company thinks.

These moments don’t show up in your productivity analytics.

They’re too quiet to be quantified.

Real leadership isn’t built on the back of surveillance software. It’s built through alignment around meaningful outcomes, giving people the space and trust to get there in their own way—and supporting them when they get stuck.

Surveillance Culture Breeds Performance Theater

There’s this delusion that if you track more, you’ll manage better.

But when employees know they're being constantly observed, a funny thing happens: they don’t become more effective. They become better actors.

They perform “busyness” instead of focusing on results.
They avoid risk because failure becomes scarier with cameras always on.
They game the system, looking for hacks—not because they’re malicious, but because the rules are dumb.

The outcome? Everyone’s putting on a show. From the intern toggling tabs to stay green, to mid-level managers scheduling meetings to look important, to VPs justifying surveillance tools as “optimization.”

Behind the curtain, real progress slows. Innovation dries up. Trust erodes.

Because people don’t do their best work when they’re afraid. They do just enough to not get flagged.

That’s not productivity. That’s learned helplessness.

AI Can Help—But Only if We Use it to Make Work Better, Not Just More Observable

There are ways to use AI that genuinely support productivity.

GitHub Copilot speeds up development by eliminating boilerplate coding.
Notion AI summarizes and synthesizes information so knowledge workers can make faster decisions.
Tools that detect process friction, deadline risk, or redundant communication loops help optimize systems, not surveil the people inside them.

The difference isn’t just technical. It’s philosophical.

Are you using AI to augment your teams?

Or are you using it to babysit them?

That’s the fork in the road. One path builds trust, creativity, and autonomy. The other breeds fear, compliance, and mediocrity.

You get what you optimize for.

Final Thought: Make the Invisible Visible—but Keep the Human in the Loop

AI has an incredible ability to surface patterns humans might miss. How often context switching derails deep work. Where meeting bloat drains focus. Which workflows snarl creativity.

Those are real opportunities.

But productivity isn’t a dashboard problem—it’s a design problem. A culture problem. A clarity problem.

If you need AI to tell you who your best performers are, maybe start by asking: do you know what great work actually looks like? Can you describe it without referring to how many emails were sent or how “green” someone’s Slack dot is?

And if not, your biggest bottleneck isn’t a lazy employee.

It’s a lazy strategy.

Three ideas to take seriously before you install another tracking tool:

If AI is measuring activity, not output, it’s performance theater in disguise. Strip away the metrics and ask: what meaningful business outcomes are we driving?
AI that builds trust beats AI that watches. Always choose augmentation over observation. The ROI of supporting people to do great work beats forcing them to look busy.
Surveillance is a seductive shortcut for unclear strategy. If you need to watch your people to know what they’re doing, fix the direction—not the dashboard.

Because here's the truth: the future of work isn’t just about where or how we work.

It’s about why we work—and whether our tools, our strategies, and our leaders are making that work easier, or just more monitored.