Survey: 94% of Managers Enthusiastic About AI, But 51% Struggle With Tool Bloat

Executive Overview

A new survey conducted by Nielsen and commissioned by Monday.com, covering 1,700 managers and executives across 7 countries, reveals a striking paradox in enterprise AI adoption: 94% of managers are enthusiastic about improving work with AI, yet more than half (51%) find it increasingly difficult to evaluate employee output. The survey, published via TechCrunch on October 21, 2026, also found that 46% of managers use AI to help make decisions and 39% of leaders use AI to draft performance reviews. Meanwhile, 57% report having more tools than before, and 58% expect to supervise more AI agents than human employees within the next year—signaling that AI is shifting from a productivity tool into a governance challenge.

Deep-Dive Features & Architecture

The Nielsen survey commissioned by Monday.com found that more than half of executives find it increasingly difficult to evaluate employee work after AI adoption, because outputs arrive polished in the manager's inbox, making it hard to distinguish between employee effort and model effort. As a result, nearly half of managers say they spend more time reviewing and guiding their teams' outputs than before. Nevertheless, 94% of managers expressed enthusiasm for improving work with AI, with high confidence in knowing where to use it for maximum value.

78% of participants changed their approach to evaluating employees after AI adoption, placing greater weight on prompt engineering skills and the employee's ability to identify which tasks to delegate to AI and experiment with new work methods. Paradoxically, 46% of managers use AI to assist with their decisions, and 39% of leaders use AI to draft performance reviews, raising concerns about compounded bias in the evaluation process.

On the infrastructure front, 57% of managers said their organizations now have more tools than before, and 51% said their tools have become more interconnected and clustered after AI adoption, while only 29% described their AI infrastructure as fully optimized and centralized. Michal Miller Levy, Head of Market Research at Monday.com, noted that companies expected AI to help shrink the software stack, but the opposite happened: more apps, more integrations, and more Shadow AI usage.

Benchmark & Competitive Performance

The survey reveals a clear governance gap: 58% of managers expect to supervise a greater number of AI agents compared to human employees over the next year, 46% are concerned about losing control over those agents' actions, and 35% fear accountability for AI decisions. These figures intersect with prior research from the Luxembourg Institute of Socio-Economic Research, which found that large language models evaluate performance similarly to humans in the absence of objective criteria, and with an early 2025 paper that revealed significant biases against Black candidates that varied in direction and magnitude across social groups.

Industry Impact & Enterprise Adoption

For enterprises adopting AI, these findings underscore the need for robust AI governance frameworks. The data shows that while enthusiasm is high, the operational reality is messy: tool sprawl, shadow AI, and evaluation ambiguity are creating new managerial headaches. Organizations must invest in centralized AI infrastructure, clear policies for AI-assisted decision-making, and human oversight for critical tasks. The survey also highlights a shift in managerial skills: evaluating employees now requires assessing how well they delegate to AI, craft prompts, and experiment—skills that are not yet standardized in performance reviews.

As AI agents become more autonomous, the supervisory burden will increase. Managers will need tools to monitor, audit, and control AI agents, and clear accountability frameworks to address the 35% who fear being held responsible for AI decisions. The survey suggests that without proper governance, AI could exacerbate existing biases and create new risks. Companies that proactively address these challenges will be better positioned to harness AI's productivity benefits while mitigating its governance risks.

Conclusion

The Nielsen/Monday.com survey paints a picture of a workforce enthusiastic about AI but struggling with its practical implications. The 94% enthusiasm is tempered by the 51% who find evaluation harder, the 57% facing tool bloat, and the 58% anticipating more AI agents than humans to supervise. These numbers signal that AI adoption is outpacing governance. To realize AI's promise, enterprises must invest in centralized infrastructure, clear evaluation metrics, and robust oversight mechanisms. The alternative—a fragmented, shadow-AI-driven landscape—risks undermining the very productivity gains that make AI so attractive.

Media Source: TechCrunch AI | Fact Verification & Analysis: AI Tools Oasis