Managers face new AI oversight and performance review challenges

AI adoption complicates management oversight

Companies are rolling out AI tools to improve productivity, yet a Nielsen survey commissioned by work-management company Monday.com finds that many managers are facing new oversight problems. The survey covered 1,700 directors and senior managers across seven countries, with more than half saying employee work has become harder to evaluate after AI adoption.

The central issue is visibility into authorship. Work can arrive in a manager’s inbox already polished, making it difficult to distinguish an employee’s own contribution from AI-generated or AI-assisted output. Nearly half of respondents said they now spend more time reviewing and guiding their teams’ work than before.

That friction has not diminished enthusiasm. Some 94% of the managers surveyed said they were excited about improving work with AI. Michal Miller Levi, Monday.com’s head of market research and customer insights, said the technology is moving faster than organizations can adapt their processes. AI may work well for an individual manager, but management also involves driving the wider organization.

Performance reviews are changing alongside the tools

Seventy-eight percent of respondents said they have changed how they evaluate employees after adopting AI. Managers are putting more weight on prompt creation, decisions about which tasks to delegate to AI, and experimentation with new ways of working.

The survey also shows AI entering the evaluation process itself. Forty-six percent of managers use AI to help inform decisions, while 39% of leaders use it to draft performance reviews. The source notes that this can create concerns about bias, particularly where objective standards are unclear and large language models reproduce patterns in their training data.

Research cited in the report from the Luxembourg Institute of Socio-Economic Research found that, without clear objective standards and when people are rated independently, LLMs tend to rate performance similarly to humans. A separate early-2025 paper found that AI models can show significant biases against different social groups, including black male candidates.

Tool sprawl and agent supervision add to the workload

AI is also changing the daily work of managers. They must decide which tasks can be handed to AI agents, check the resulting work and intervene when an agent fails. The report characterizes this supervision as a potential new layer of invisible labor.

Rather than shrinking software stacks, AI adoption has often expanded them. Fifty-seven percent of managers said their organizations have more tools in use than before, and around 51% said those tools have become more interdependent and clustered. Only 29% described their AI infrastructure as fully optimized and centralized, while shadow AI use adds another control challenge.

Autonomous agents make accountability more urgent. Fifty-eight percent expect to oversee more AI agents than human employees within the next year, 46% worry about losing control of agent actions, and 35% fear being held responsible for AI decisions. The practical implication for businesses is to establish clear rules for AI use, human review, evaluation standards and responsibility before AI-generated work becomes routine in management decisions.