What We Know About Managers Struggling With AI-Driven Work

Artificial intelligence tools are supposed to make employees faster and more productive. For their managers, the technology is mostly creating more work.

More than half of senior leaders say they find it harder to evaluate employees' work after their companies adopted AI, according to a Nielsen survey of 1,700 directors and senior managers across seven countries, commissioned by work-management company Monday.com, TechCrunch reported. The culprit, according to the survey, is that employee output now arrives polished in a manager's inbox, making it difficult to tell how much came from the worker and how much came from a chatbot.

What did the survey find?

• More than 50% of managers say AI has made evaluating employee work harder, according to the Nielsen survey for Monday.com.
• Nearly half of managers say they now spend more time reviewing and guiding their teams' output than before AI adoption.
• 94% of managers said they are excited to improve work using AI, per the same survey.
• 78% said they have changed how they evaluate employees since adopting AI tools.
• 46% of managers use AI to help inform personnel decisions, and 39% use AI to draft performance reviews, the survey found.

Why are managers finding AI output harder to evaluate?

Michal Miller Levi, head of market research and customer insights at Monday.com, told TechCrunch that enthusiasm for AI resembles the early internet era of the 2000s, when workers saw a similar sense of "magic" in new tools. The friction, she said, comes from a mismatch in speed: "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," Levi said.

How are managers changing performance reviews?

The 78% of managers who say they've altered evaluation practices are placing more weight on how well staff write prompts, decide which tasks to hand off to AI, and experiment with new workflows, according to the survey.

What risks does AI introduce into evaluations?

Using AI to help write or inform performance reviews carries its own hazards. Research from the Luxembourg Institute of Socio-Economic Research found that large language models tend to rate performance similarly to humans when clear objective standards are absent. Separately, a research paper from early 2025 found that AI models can be biased against Black male candidates and "demonstrate significant biases, varying in terms of the directions and magnitudes across different social groups," TechCrunch reported.

Timeline of the evidence

• Early 2025: A research paper documents bias in AI hiring and evaluation models against specific demographic groups.
• 2026: The Luxembourg Institute of Socio-Economic Research publishes findings on how LLMs rate performance absent clear standards.
• October 2026: Nielsen's survey for Monday.com, covering 1,700 managers in seven countries, finds more than half struggle to evaluate AI-assisted work.

What's next for companies adopting AI tools?

The survey suggests the gap between individual enthusiasm for AI and organizational readiness to manage it remains wide. Levi's comments to TechCrunch frame the issue as a pacing problem rather than a tooling problem — one that companies will likely keep confronting as AI use spreads deeper into daily workflows.

AlterEgo — A keyboard for character voices. Five free persona rewrites a day.