Organisations around the world are spending heavily on artificial intelligence tools, trusting that those investments will make their employees faster, smarter, and more productive. But the people actually sitting at those desks tell a more complicated story. This paper critically examines how employees measure the effectiveness of AI tools they use in their day-to-day organisational roles, and why trust in those tools is far from automatic. Drawing on the technology acceptance literature, automation trust research, and documented workplace cases, the paper shows that employee judgments of AI effectiveness are shaped by perceived usefulness, transparency of outputs, past errors, and the degree to which a tool genuinely reduces cognitive load rather than adding to it. The paper also identifies the conditions under which AI tools erode rather than build employee trust, and it concludes with a set of practical advisories for workplace managers who want to close the gap between what AI promises and what it actually delivers.
Xin Yue (Fri,) studied this question.