AI monitoring at work: what it is and what workers can ask

AI is increasingly used not only to help people work but to watch how they work: tracking activity, scoring performance, flagging behavior or allocating tasks based on data about each worker. This is often called algorithmic management. It can make management more consistent, and it can also make work more intense and less private. This page explains what it involves, what the research finds, what EU rules say, and what to ask.

This is a general guide, not legal advice. Rules on workplace monitoring differ widely by country, sector and contract.

The short answer: AI monitoring at work means using AI systems to collect and analyze data about workers in order to evaluate, direct or manage them. Research from the OECD finds it can increase consistency but also work intensity and privacy concerns. In the EU, AI used to monitor and evaluate workers' performance and behavior is listed as high-risk under the AI Act, and AI that infers workers' emotions is prohibited except for medical or safety reasons. Whatever the rules where you are, workers and managers can ask what is collected, why, who sees it, and how decisions can be challenged.

What AI monitoring can involve

• Activity tracking: keystrokes, applications used, time active, calls handled.
• Performance scoring: automatic ratings of speed, quality or targets, sometimes ranking workers against each other.
• Conversation analysis: analysis of calls, chats or emails for quality or compliance.
• Location and movement: in warehouses, deliveries and field work.
• Task allocation: deciding who gets which work, shifts or routes based on data about them.
• Flags and alerts: notifying managers about behavior the system judges unusual.

Not every tool that produces data about work is monitoring in this sense. The line is crossed when the data is used to judge, rank or direct individual people.

What the research finds

The OECD Employment Outlook 2023, drawing on its surveys of employers and workers in manufacturing and finance, notes that AI used for managerial tasks such as monitoring workers, allocating tasks or deciding who should receive training or promotion can lead to more data-driven and consistent management, but if not designed and implemented well can reinforce biases, harm privacy, increase work intensity and reduce autonomy. It reports that AI-enabled monitoring and feedback can be more pervasive than human monitoring, that workers report higher work intensity after AI adoption, and that when employers' use of AI involves data collection on workers, the majority of workers are worried about their privacy. Workers subject to algorithmic management reported the least positive effects on job quality (OECD Employment Outlook 2023). For the wider picture, see AI and job quality.

What EU rules cover

Several EU texts are relevant. They are quoted or summarized here with links to the source; how they apply to a specific case depends on the facts and on national law.

• High-risk use: Annex III of the AI Act lists AI systems intended to be used to make decisions affecting terms of work-related relationships, promotion or termination, to allocate tasks based on individual behaviour or personal traits or characteristics, or to monitor and evaluate the performance and behaviour of persons in such relationships (EU AI Act, Annex III, point 4(b)).
• Emotion recognition: Article 5 prohibits AI systems that infer the emotions of a person in the workplace, except where intended for medical or safety reasons (EU AI Act, Article 5(1)(f)).
• Telling workers: under Article 26(7), employers deploying a high-risk AI system at the workplace must inform workers' representatives and affected workers before putting it into service or use (EU AI Act, Article 26(7)).
• Explanations: Article 86 gives people affected by certain decisions based on high-risk AI output a right to clear and meaningful explanations, subject to its conditions and exceptions (EU AI Act, Article 86).
• Data protection: the GDPR applies to workers' personal data, and its Article 88 allows Member States to set more specific employment rules, which must include safeguards with particular regard to transparency and monitoring systems at the work place (GDPR, Article 88). See AI agents and personal data.

The Digital Omnibus on AI, Regulation (EU) 2026/1744, published in the Official Journal on 24 July 2026 (NI Assembly EU law tracker), moved the date the Annex III high-risk rules apply, including those for employment, to 2 December 2027 (European Commission). Before relying on a date, check the current text. Our page on AI at work and workers' rights covers the Act's workplace provisions in more detail. Outside the EU, rules vary; for US state notice laws, see employee monitoring laws in the US, and for the UK, see monitoring workers in the UK. For gig and app-based work, the EU Platform Work Directive adds specific rules on algorithmic management, to be applied by EU countries by 2 December 2026.

Questions workers can ask

1. Which AI systems collect or analyze data about my work?
2. What data is collected, how often, and how long is it kept?
3. What is it used for: feedback, pay, scheduling, discipline, promotion?
4. Does a person review decisions based on it, and who?
5. Can I see the data and scores about me, and correct errors?
6. How can I question a decision or score I think is wrong?
7. Were workers or their representatives consulted before it was introduced?

Questions managers should ask before using it

• What problem does it solve, and could it be solved with less data? In the EU, check the legal basis and whether an impact assessment is needed first; see GDPR duties for employers using AI.
• Is it accurate and fair? Test it on real work and check whether it treats groups differently. The NIST AI RMF lists fairness with harmful bias managed and privacy among the characteristics of trustworthy AI (NIST AI RMF 1.0).
• Who reviews its outputs before they affect someone's job? See human in the loop and accountability, and for scores that feed into reviews, AI in performance reviews.
• Can workers see what it holds on them? In many places they have a legal right to ask; see how to request the data AI systems hold on you.
• Have workers been told and involved? People accept systems they understand and helped shape.
• What happens to trust and to work intensity once it is running? Measure it.
• Does it stop outside working hours? See AI and the right to disconnect.
• Is it covered in your AI policy? See AI policy for employees.
• Can staff report a problem with it safely? See raising concerns about AI at work.

The digital collar view

AI at work can be a tool people direct, or a system that directs people. Monitoring sits at the second end. Used with transparency, human review and limits, data about work can support fairer feedback; used without them, it can make work more intense and less autonomous. Who supervises the system, and whether workers can question it, makes the difference. For what EU-OSHA has found about AI management, stress and safety, see AI and workplace safety.