When Algorithms Watch the Workplace, Who Holds the Power?

AI surveillance is spreading through workplaces worldwide, bringing a new question into daily working life: who gets to watch, measure, and judge employees? Automated systems now rate calls, track movement, assess tone, and interview job applicants, turning ordinary workplace moments into data points.

That shift promises more automation, but it also raises concerns about safety, errors, fairness, and control. As companies adopt AI at speed, workers and regulators are confronting the same problem from different sides: what happens when an algorithm becomes part of the chain of command?

From Phone Calls to Movement Heat Maps

Co-op, a British consumer co-operative, implemented automated listening technology that rates phone calls between agents and customers. The system places conversations under assessment, adding a new layer of monitoring to work that once depended on human judgment.

One Co-op worker captured the pressure in four words: “You are being watched.” The criticism also appeared in the description “‘Dystopian’: Co-op becomes latest firm to put staff under AI surveillance,” a phrase that reflects the unease surrounding automated oversight.

Co-op said it did not recognize the criticism and stated that its probate advisers were highly engaged. That response highlights the divide at the heart of workplace AI: employers can describe monitoring as engagement or quality control, while employees can experience the same system as constant observation.

The issue reaches beyond customer service. Amazon warehouse workers have previously complained about being timed on bathroom breaks, while nurses at Kaiser Permanente, a California hospital chain, said automated systems rated their tone of voice during patient interactions.

These examples show how AI surveillance can enter different parts of working life. A phone call, a movement pattern, a bathroom break, or a nurse’s tone can all become part of an automated assessment.

California Draws a Line as Concerns Grow

California governor Gavin Newsom signed laws into effect last week that prohibit certain types of workplace surveillance. The laws target measures such as heat maps that track employees’ movements and emotional states.

The California action places limits on systems that turn physical activity and emotional signals into workplace data. It also shows how regulators are responding as monitoring tools move from experimental technology into everyday employment.

Yet regulation is only one part of the challenge. Employers are navigating a flood of errors and low-quality work caused by rapid AI adoption, creating pressure to check what automated systems produce instead of accepting their judgments without review.

Meta scaled back plans to axe staff and use more AI agents after employees spent more time cleaning up errors. The decision connects workplace automation with a practical problem: an AI system can reduce one kind of work while creating another when its output requires correction.

That tension matters for workers and companies alike. Automation can change who performs a task, but it does not remove responsibility for mistakes, poor-quality work, or the consequences of an automated decision.

Who Benefits From the AI Economy?

The workplace debate also includes access to opportunity. The AI industry is booming, but women are getting left behind, with the median pay of men $45,000 higher than the median pay of women across AI-related occupations.

Felicia Newhouse, founder of AI Powered Women, said, “We’re talking about who captures a major new source of economic mobility.” She also warned, “The deepest risk is that a participation gap becomes a power gap.”

A female co-founder of an AI startup said she and her male co-founder are more likely to get investment if he does the pitching. That experience adds another layer to the pay gap, showing how workplace power can shape both who receives funding and who gets heard.

AI is also changing the first step into employment. Author Giselle Au-Nhien Nguyen described being interviewed by an AI assistant as dystopian and dehumanising, then asked, “Is the use of AI to interview job applicants a sign of the job losses to come?”

That question links hiring automation to the wider fear surrounding AI at work. If an automated system can judge applicants before they meet a person, the technology may influence not only how people work but who gets the chance to work at all.

Government officials are calling for stronger safeguards as these systems spread. Kanishka Narayan, the UK’s AI minister, will say Britain cannot rely entirely on tech companies and will call for increased safety efforts by companies developing frontier AI.

The next stage of workplace AI will be shaped by more than new tools. It will depend on whether companies explain how systems rate people, correct errors, protect workers, and share the power created by the technology. The machines may be watching, but the bigger question is who watches the machines.

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