Companies are giving employees AI tools to raise productivity, but the tools appear to be creating new management problems. A Nielsen survey of 1,700 directors and senior managers across seven countries, commissioned by Monday.com, found that more than half of senior leaders now find it harder to evaluate employees’ work after adopting AI. The reason is that much of employees’ output arrives polished in managers’ inboxes, making it hard to tell how much came from the employee and how much from AI. Nearly half of managers say they spend more time reviewing and guiding their teams’ output than before.

Managers remain enthusiastic on the whole: 94% of those polled said they are excited to improve work using AI, and many are confident about where to apply it. Michal Miller Levi, Monday.com‘s head of market research and customer insights, compared this to the early internet era, but explained the core difficulty is that AI is moving faster than organizational processes. “AI works very well for [managers] individually, but they also have a different role as managers. They need to drive the organization as well […] Their struggle is [due to] the fact that AI is just moving faster than the organizational processes.”

Adoption is also changing how performance is judged. 78% of respondents say they have changed how they evaluate employees, placing more weight on prompt-writing ability, deciding which tasks to delegate to AI, and experimenting with new ways of working. At the same time, managers can’t always see how much of an employee’s work came from AI, and some are turning to AI to judge employees: 46% use AI to help inform decisions, and 39% of leaders use AI to draft performance reviews. The survey report and related research highlight a risk of bias — research from the Luxembourg Institute of Socio-Economic Research found LLMs tend to rate performance similarly to humans when objective standards are absent, and an early 2025 paper found AI models can be biased against black male candidates. Levi acknowledged companies have not yet worked out how to handle such issues.

AI is also reshaping the manager’s daily workload and the company tool stack. Someone has to decide which tasks go to AI agents, check their output, and step in when things go wrong; the report frames this as a new layer of “invisible labor.” On the technology side, 57% of managers say their organizations now have more tools than before, and about 51% say their tools have become more interdependent and clustered. Only 29% describe their AI infrastructure as fully optimized and centralized. Levi said businesses expected AI to shrink their software stacks, but instead they’re facing more apps, integrations, and shadow AI usage as employees adopt unsanctioned tools. “More than 50% are saying that they’re using more tools now than they did last year, and it’s not stopping […].”

Control is becoming more urgent as autonomous AI agents enter the workplace. 58% of managers expect to oversee more AI agents than human employees within the next year; 46% worry about losing control over those agents’ actions; and 35% fear being held responsible for AI-made decisions, given that LLMs are still largely unpredictable. Levi said managers do not want agents to be fully autonomous, and instead want people kept involved and consulted on crucial tasks and decisions.

At heart, the findings show AI adoption is becoming as much a governance problem as a productivity opportunity. Without proper processes and infrastructure, managers appear to be scrambling to keep things running.