When AI Surveillance Turns to Watch the Boss
AI that watches managers for toxic behaviour sounds responsible, but it risks flagging the wrong people and fixing nothing about broken workplace culture.
AI surveillance has spent the last decade pointed downwards, watching workers for productivity, keystrokes, time spent away from the screen. So there is something genuinely surprising in the latest pitch from companies like Smarsh: the camera has swung round to face the boss. Their software promises to scan workplace messages and behaviour, then flag managers whose conduct is turning sour. The selling line is striking. Smarsh says its systems ensure "bad conduct is spotted and escalated instantly", allowing companies to locate "patient zero" before a "contagion" of toxic culture takes hold.
Read that pitch carefully, because the metaphor is doing a lot of work. Toxic culture is being framed as a disease. The bad manager is the infected host. The fix is early detection and containment. It sounds responsible, almost caring. And for anyone who has worked under a manager who belittles people in meetings or quietly freezes someone out, the instinct to catch that early is completely understandable. I have sat with frontline teams who endured exactly this for years while HR looked the other way. So I am not here to mock the intention.
But I want to be honest about what is actually being sold, because the gap between the promise and the reality is where leaders get into trouble.
First, the disease metaphor hides a decision. Calling a manager "patient zero" makes the software sound neutral, like a thermometer. It is not. Someone has to define what toxic looks like in data: which words, which patterns, which tone counts as a symptom. That definition reflects the values and assumptions of whoever built the model. Sarcasm reads differently across cultures. Directness that lands as rude in one team is respected as honesty in another. A neurodivergent manager who communicates bluntly might trip the same flag as a genuine bully. The machine does not know the difference. It only knows the pattern it was trained to find.
This is not a hypothetical worry. We have watched the older version of it play out for years in psychometric testing. Someone I know is partially deaf and partially blind. In a busy room with lots of voices, they struggle to work out which direction a sound is coming from, so when a test asked whether they preferred to work alone or in a team, they answered "alone". That is a preference shaped by a disability, not a measure of whether they can work with others. The two are not the same thing. David Beckham kicks a ball with his right foot and so do I, (when my ankle isn't broken like it is now). Same preference, wildly different ability. The test could not tell the difference, and the person was turned down for the promotion because the employer wanted "team players" and the data said they were not one. A flag had been raised. Nobody asked what it actually meant.
Second, watching for bad behaviour is not the same as building good culture. This is the trap I see organisations fall into again and again. You can automate detection. You cannot automate trust. If your culture is poor, a tool that flags toxic managers is treating the symptom while leaving the cause, which is usually how power, pressure and incentives flow through the business, completely untouched. Plenty of "toxic" managers are ordinary people crushed by impossible targets and zero support. Flag them, remove them, and the next person in the role inherits the same broken conditions. Automating a broken process just helps you fail faster.
Third, there is the quiet shift in who gets watched. Selling surveillance as protection for staff is clever, because it feels like the tool is on the worker's side. But the same system that reads a manager's messages reads everyone else's too. Once the infrastructure is installed, the question of what it monitors, and for whom, is a governance choice, not a technical fact. The honest test is the one I keep coming back to with leaders: can responsibility be traced when this system gets it wrong? If a manager is flagged, sidelined or sacked partly on the say-so of a model nobody can fully explain, who is accountable for that call?
None of this means the technology is worthless. Early signals about a deteriorating team can be genuinely useful when a human being uses them to start a conversation rather than to build a case. The difference is leadership. A flag should open a door, not close one.
If you are weighing up a tool like this, here is one thing worth doing before you sign anything. Ask the vendor to show you exactly how their system defines toxic behaviour, who chose that definition, and what happens to a person once they are flagged. If they cannot answer plainly, you are not buying a culture solution. You are buying a liability with a friendly metaphor wrapped round it.
Frequently Asked Questions
What does AI workplace monitoring software that flags toxic bosses actually do?
It scans workplace communications and behavioural data to detect patterns it has been trained to read as toxic, then alerts the organisation to managers showing those signs. Smarsh, for example, says its system spots and escalates bad conduct instantly to find "patient zero" before toxic culture spreads. In practice it flags people for human review, it does not judge culture on its own.
Could AI monitoring discriminate against disabled or neurodivergent employees?
Yes, because these systems read patterns, not people, and a pattern can reflect a disability rather than a problem. Someone partially deaf who answers that they prefer working alone may be describing how they cope with noise, not their ability to work in a team. A blunt neurodivergent manager can trip the same flag as a bully. Without a human asking what a flag means, the tool can screen out the very people it should protect.
Is monitoring managers a good way to fix a toxic workplace culture?
Detection alone does not fix culture, because most toxic behaviour grows from how pressure, targets and incentives flow through a business. A tool can flag a struggling manager, but if you remove them without changing the conditions, the next person inherits the same broken role. Surveillance treats the symptom while leaving the cause untouched.
Who is held accountable if the AI wrongly flags a manager?
Accountability must sit with the humans who act on the flag, not the software, which is exactly why traceability matters before you buy. If a manager is sidelined or dismissed partly on the say-so of a model nobody can fully explain, the organisation still owns that decision. Always ask a vendor what happens to a person once the system flags them.
What should leaders ask before buying workplace monitoring tools?
Ask the vendor to show exactly how the system defines toxic behaviour, who set that definition, and what happens to someone once they are flagged. If those answers are not plain and clear, you are not buying a culture solution, you are buying a liability. The same system that watches managers can watch everyone, so treat its scope as a governance choice.