AI tools are meant to help employees get more done. For managers, though, the polished work those tools produce can make it harder to judge individual contributions, while the growing collection of software and AI agents adds new oversight tasks.
Polished work makes performance harder to assess
More than half of senior leaders surveyed said evaluating employees’ work became harder after their organizations adopted AI. The Nielsen survey covered 1,700 directors and senior managers across seven countries and was commissioned by work-management company Monday.com.
When an employee’s work arrives in a manager’s inbox already polished, it may be difficult to distinguish the employee’s contribution from AI’s. Nearly half of managers said they now spend more time reviewing and guiding their teams’ output.
Managers are also changing what they look for in employees. Seventy-eight percent of respondents said they had changed how they evaluate staff after adopting AI, giving more weight to skills such as writing prompts, deciding what to delegate to AI, and experimenting with new ways of working.
That shift raises a practical question: how can reviews fairly measure employees when managers cannot readily see how AI contributed to the work? The challenge grows when AI also helps make or prepare the assessments. The survey found that 46% of managers use AI to inform decisions, while 39% of leaders use it to draft performance reviews.
AI enthusiasm meets questions about fairness
Managers are not rejecting AI. In the survey, 94% said they were excited about improving work with it, and many felt confident about where it could add value. Michal Miller Levi, Monday.com’s head of market research and customer insights, compared that excitement with the early days of the internet in the 2000s, when people saw a similar kind of “magic” in the technology.
Levi told TechCrunch that organizations are struggling to adapt at the pace AI is developing. AI may work well for an individual manager, she said, but managers also have to guide the organization. The difficulty is that AI is moving faster than organizational processes.
Using AI to assess people brings a further concern: bias. The article notes that large language models can repeat patterns in their training data. Research from the Luxembourg Institute of Socio-Economic Research earlier this year found that, without clear objective standards and when people are rated independently, language models tend to rate performance similarly to humans. A research paper in early 2025 found that AI models can be biased against black male candidates and show biases that vary across social groups.
Asked whether AI could bring outside bias into performance decisions, Levi said companies have not yet worked out how to handle such issues. The survey does not resolve how organizations should use AI in reviews; it highlights the need for managers to consider how the tools shape decisions about people.
More tools mean more coordination
AI is changing managers’ daily work as well as how they assess teams. Someone has to decide which tasks to hand to AI agents, review what they produce, and intervene when something goes wrong. The report describes this supervision as a possible new layer of “invisible labor.”
The software environment is also becoming more complicated. Fifty-seven percent of managers said their organizations now have more tools in circulation than before, and about 51% said those tools had become more interdependent and clustered since adopting AI. Just 29% described their AI infrastructure as fully optimized and centralized.
That growth runs against the expectation that AI would help companies reduce the number of software tools they use. Levi said businesses instead face more apps and integrations, as well as shadow AI use when employees adopt tools outside approved systems. She described managers entering 2025 expecting to consolidate software, then finding that tool use had increased and was continuing to grow.
AI agents bring control and accountability concerns
As companies introduce AI agents that can act on their own, managers expect their oversight responsibilities to expand. The survey found that 58% expect to oversee more AI agents than human employees within the next year. Another 46% worry about losing control over what those agents do.
Accountability is another concern: 35% of respondents feared being held responsible for decisions made by AI. Levi said managers do not want agents to be fully autonomous. For crucial tasks and decisions, they want people involved and consulted.
Together, the findings frame AI adoption as both a productivity opportunity and a management challenge. Evaluating work, overseeing tools, and keeping people involved in consequential decisions all depend on processes that organizations are still working out. Without suitable processes and infrastructure, managers are left trying to keep work moving while the systems around it continue to change.