- Four in five executives say they were less likely to value human employees after using AI
- AI still requires human supervision and many find it difficult to fully trust it
- Poor and even negative ROI continues to plague many
A new study by Globalization Partners has revealed that more than four in five (82%) business executives say they are less likely to value human employees after using artificial intelligence tools, positioning human workers as secondary assets after more capable systems.
This sentiment differs from the current state of affairs, where 60% of 2,850 senior executives surveyed agreed that humans still lead work operations and that AI simply serves as a productivity booster.
The difference could mean that while humans remain integral today, managers could place less emphasis on the human workforce in the future as AI performs more work autonomously.
AI is affecting how senior managers value their human workers
The shift likely positions humans as AI managers, rather than administrative workers, with two in three (69%) now spending more time than ever monitoring and reviewing AI-generated work. The feeling of lack of trust also persists: only 23% have complete confidence in the accuracy of AI and 61% worry about legal accuracy when using AI on confidential documents.
However, while some executives see AI as a substitute for humans, many others are still dissatisfied with its returns. Three-quarters (73%) say ROI has not lived up to expectations, with 16% even reporting negative ROI. As a result, about seven in 10 executives say they are willing to cut AI budgets this year if goals are not met.
On the other hand, Gartner vice president analyst Padraig Byrne explained: “AI is everywhere, but most organizations are still figuring out how to monitor and trust these systems.”
Giving a sneak peek at where companies might be going wrong, the research firm hinted that those who build AI agents without solid foundations of semantic and contextual data are more likely to see hallucinations, unreliable results, and biases.
Together, the two reports indicate that while executives increasingly see AI as inevitable, many still struggle to trust it.
Looking ahead, Gartner calls for the implementation of model monitoring policies to provide high-quality metrics and a greater focus on infrastructure to handle high-volume model telemetry.
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