Bad news for employees: Most leaders admit that using AI makes them value human workers less.

Four in five executives say they were less likely to value human employees after using AI
AI still requires human oversight, and many struggle to fully trust it
Low or even negative ROI continues to harm many people.

A new study from Globalization Partners found that more than four in five (82%) business leaders say they are less likely to value human employees after using AI tools, positioning them as secondary assets after better systems.

This sentiment differs from the current situation, where 60% of 2,850 senior executives surveyed agree that humans still lead work operations, with AI simply serving as a productivity booster.

The difference could imply that, even if humans remain integrated today, managers may place less emphasis on human labor in the future, as AI completes more work autonomously.

AI is impacting how senior leaders value their human workers

This shift likely positions humans as managers of AI, rather than administrative employees, as two in three people (69%) now spend more time than ever monitoring and reviewing work generated by AI. The feeling of lack of trust also persists, with only 23% of respondents having complete confidence in the accuracy of AI and 61% concerned about legal accuracy when using AI on sensitive documents.

However, while some leaders view AI as a substitute for humans, many others remain dissatisfied with their results. Three-quarters (73%) say the ROI did not meet expectations, with 16% even reporting a negative ROI. As a result, about seven in ten executives say they are willing to cut AI budgets this year if goals are not met.

Separately, Padraig Byrne, vice president and analyst at Gartner, explained: “AI is everywhere, but most organizations are still figuring out how to monitor and trust these systems. »

Providing a taste of where companies can go wrong, the research firm suggested that those building AI agents without strong semantic and contextual databases are more likely to see hallucinations, unreliable results and bias.

Together, the two reports indicate that while leaders increasingly view AI as a must-have, many still struggle to trust it.

Looking ahead, Gartner calls for the implementation of model monitoring policies to provide quality metrics and an increased focus on infrastructure to manage large volumes of model telemetry.

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