AI Promises Productivity, but Managers Say It Makes Their Jobs Harder
A Nielsen survey for Monday.com finds more than half of senior managers now struggle to judge employees' work since adopting AI tools
By AXY AI Desk ·
Key points
- A Nielsen survey of 1,700 directors and senior managers in seven countries, commissioned by Monday.com, found more than half find it harder to evaluate employees' work since adopting AI.
- Nearly half of managers say they spend more time reviewing and guiding team output than before.
- 46% of managers use AI to inform decisions and 39% use it to draft performance reviews, raising bias concerns.
- 57% say their organizations now have more tools, and only 29% describe their AI infrastructure as fully optimized and centralized.
More than half of senior managers say they now find it harder to evaluate their employees' work after adopting AI, according to a new survey. The findings suggest that the tools companies hand to staff to make them more productive are creating a new set of problems for the people who manage them.
The survey was carried out by Nielsen among 1,700 directors and senior managers across seven countries. It was commissioned by Monday.com, a company that sells work-management software used to plan and track projects. The problem, according to the survey, is that much of employees' output now lands in a manager's inbox already polished. When a report, slide deck or memo arrives looking finished, it becomes difficult to tell how much of it came from the employee and how much came from an AI tool. Nearly half of the managers said they now spend more time reviewing and guiding their teams' work than they did before.
Managers Are Excited, Not Hostile
The survey does not paint managers as skeptics. In fact, 94% of those polled said they were excited about using AI to improve work, and many said they were confident they knew where it would add the most value. That enthusiasm is part of what makes the findings notable. The people being asked to supervise a new kind of work are, for the most part, eager to adopt the technology in the first place.
Michal Miller Levi, head of market research and customer insights at Monday.com, compared the mood to the early days of the internet in the 2000s. She said people see a similar kind of "magic" in AI today. Levi's explanation for the strain was less about enthusiasm and more about speed. In her view, the technology is moving faster than the way organizations are built to operate. "AI works very well for [managers] individually, but they also have a different role as managers. They need to drive the organization as well," she said. Her conclusion was that the struggle comes from the fact that "AI is just moving faster than the organizational processes."
How Managers Are Changing the Way They Judge Staff
The survey found that 78% of respondents had changed how they evaluate employees since adopting AI. Many now place more weight on skills that barely existed in most job descriptions a few years ago. Those include how well staff can write instructions for AI tools, which is often called prompt writing, and how well they can decide which tasks should be handed to an AI system instead of done by a person. Managers also said they now value willingness to experiment with new ways of working.
That shift raises an obvious question about fairness. If a manager cannot easily tell how much of an employee's work came from the employee's own skill, how can that manager judge the employee's performance accurately? A worker who produces strong output with the help of a well-designed AI tool may look more capable than a colleague who works more slowly by hand. Whether that counts as a skill or as an advantage is not something most companies have settled.
Managers Are Using AI to Judge Performance Too
The judgment problem goes further. The survey found that 46% of managers use AI to help inform their decisions about staff, and 39% of leaders say they use AI to draft performance reviews. In other words, the same technology that makes employee output harder to read is also being used to write the verdict on that output.
This is where researchers have raised concerns. Large language models, the systems behind most popular AI chat tools, work by predicting likely words and patterns based on huge amounts of text. Because they learn from human writing, they can also pick up and repeat human biases. A review written with help from such a tool could therefore carry more bias than a review written by a person alone, which is a risk for workers whose careers depend on those reviews.
Research cited in the survey coverage points in the same direction. A study from the Luxembourg Institute of Socio-Economic Research earlier this year found that, "in the absence of clear objective standards and when individuals are rated independently," large language models tend to rate performance in ways similar to humans. That finding suggests the models do not escape human judgment. A separate research paper from early 2025 found that AI models can be biased against Black male candidates, and that the biases varied in direction and size across different social groups. Those studies were not about performance reviews specifically, but they raise the same underlying question about whether a machine trained on human records can be trusted to be neutral about people.
When asked whether using AI to weigh in on employees' performance could bring outside bias into the process, Levi said companies have yet to work out how to handle such issues. For now, there appears to be no widely accepted standard that tells managers how much AI assistance is appropriate in a review.
A New Kind of Work for Managers
AI is also changing what a manager's day looks like. Someone has to decide which tasks to hand over to AI agents, which are programs that can carry out several steps of a job with limited human input. Someone then has to check what those agents produce and step in when something goes wrong. The report suggests this oversight could amount to a new layer of what it calls "invisible labor." It is work that rarely shows up in a job title or a performance score, yet it takes time and attention away from other responsibilities.
For employees, that means the manager who reviews their work may be spending more hours on checking and correcting than on coaching. For managers, it means their own role is expanding into areas that were never part of their training.
The Software Stack Is Getting Harder to Manage
The tools themselves are adding to the strain. Fifty-seven percent of managers said their organizations now have more tools in circulation than before. About 51% said their tools had grown more interdependent and clustered since adopting AI, meaning that one system's output often feeds into another. Only 29% described their AI infrastructure as fully optimized and centralized.
That last figure matters. A company that has bought many separate tools without a clear plan can end up with systems that do not work well together, duplicate each other's functions, or make it unclear who is responsible when something goes wrong. Managers are left to sort out the mess while also being asked to judge the people who depend on it.
What to Watch Next
The survey is a snapshot of managers' views rather than a measure of how well AI is actually improving output, and it was commissioned by a company that sells workplace software. Its results should be read with that in mind. Still, the picture it describes is one that many workers and managers will recognize. Companies that want to get real value from AI may need to set clearer rules for how work is produced, disclosed and reviewed, including whether employees should say when AI helped with a task and how much weight a review should give to that help.
Analysts expect the questions raised here to grow as AI tools spread into more routine work. Watch for whether companies begin to publish written policies on AI use in performance reviews, and whether regulators or employers set limits on automated assessment of staff. Also watch for follow-up research that measures whether AI-assisted reviews are more or less accurate, and whether they treat different groups of workers differently. Until those answers arrive, the managers in the middle are likely to keep carrying the weight of a technology that promised to make their jobs easier.
Questions and answers
Why are managers finding it harder to evaluate employees since adopting AI?
According to the survey, much of employees' output now arrives polished, making it hard to tell how much came from the employee and how much from AI. More than half of senior leaders say this makes evaluation harder.
How many managers use AI to write performance reviews?
The survey found that 39% of leaders are using AI to draft performance reviews, and 46% use AI to help inform their decisions about staff.
Who conducted the survey on managers and AI?
The survey was carried out by Nielsen among 1,700 directors and senior managers across seven countries and was commissioned by work-management company Monday.com.
What could AI-assisted performance reviews mean for workers?
Researchers cited in the coverage warn that large language models can repeat human biases from their training data, so AI-assisted reviews could introduce more bias than usual into the process.
Topics: artificial intelligence, workplace AI, middle management, performance reviews, Monday.com, Nielsen, workplace productivity
Sources: TechCrunch AI