Firms are providing staff with artificial intelligence tools to boost output, yet these technologies are generating fresh difficulties for their supervisors.
More than half of senior leaders report that assessing employee performance has grown harder following the integration of artificial intelligence, according to a Nielsen poll of 1,700 directors and senior managers across seven countries, commissioned by work-management company Monday.com. Staff submissions now arrive in inboxes fully polished, making it difficult to determine the extent of human versus artificial intelligence contribution. Consequently, nearly half of supervisors state they spend extra time reviewing and directing team output than previously.
This does not mean supervisors dislike artificial intelligence. In fact, 94% of polled supervisors expressed excitement about enhancing work through artificial intelligence, and many feel certain about where to apply it for maximum value. Michal Miller Levi, head of market research and customer insights at Monday.com, likened the enthusiasm to the early internet era during the 2000s, noting that people perceive a similar sort of magic in artificial intelligence.
However, the difficulty, she explained to TechCrunch, is simply that artificial intelligence evolves faster than businesses can adapt. "Artificial intelligence works very well for them 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 artificial intelligence is just moving faster than the organizational processes," Levi said.
Supervisors are also rethinking how they assess their teams, with 78% of respondents reporting changes in their evaluation methods after adopting artificial intelligence, placing greater emphasis on prompt creation skills, task delegation choices, and experimentation with new work methods.
Yet questions remain regarding fairness when supervisors struggle to identify how much work stems from artificial intelligence, and whether supervisors themselves increasingly depend on the technology for those judgments. The survey revealed that 46% of supervisors use artificial intelligence to inform decisions, while 39% of leaders apply it to draft performance reviews.
Such practices carry the danger of adding further bias into the review process, given that large language models are fundamentally prediction mechanisms that tend to replicate human patterns found within training data. Research 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 similarly to humans. An early 2025 research paper also found that artificial intelligence models can show bias against Black male candidates and "demonstrate significant biases, varying in terms of the directions and magnitudes across different social groups."
When asked whether using artificial intelligence to weigh in on employee performance might introduce external bias, Levi responded that companies have not yet determined how to manage such challenges.
Artificial intelligence is likewise altering the daily routine of supervisors, who must decide which tasks to assign to artificial intelligence agents, inspect outputs, and intervene when errors occur. The report indicates this supervision could represent a new form of invisible labor.
Managing the software itself is proving more difficult. Fifty-seven percent of supervisors report their organizations now maintain more active tools than previously, and about 51% noted that their applications became more interdependent and clustered after adopting artificial intelligence. Only 29% characterized their artificial intelligence infrastructure as fully optimized and centralized.
Levi noted that businesses anticipated artificial intelligence would help shrink their software collections. Instead, organizations face an increase in applications, integrations, and shadow artificial intelligence usage as employees use tools outside official company systems.
"Managers completed 2025 with the feeling that they will consolidate tools, actually, that they'll reduce the number of software. But what happened is that the number of tools that they're using increased," Levi said. "More than 50% are saying that they're using more tools now than they did last year, and it's not stopping."
The demand for control appears increasingly urgent as firms deploy autonomous artificial intelligence agents. The survey showed that 58% of supervisors expect to supervise more artificial intelligence agents than human staff within the coming year, while 46% fear losing command over agent actions.
Fears also persist regarding liability for choices made by artificial intelligence, with 35% of respondents expressing concern since large language models remain largely unpredictable. "They don't want their agents to be fully autonomous," Levi stated, explaining that supervisors prefer human involvement and consultation for critical tasks and decisions.
Ultimately, the report highlights that adopting artificial intelligence is increasingly becoming a governance challenge alongside its potential for raising productivity. Without adequate processes and infrastructure to manage it, supervisors appear to be rushing to maintain operations.
