HKUST Business Review

workers are unlikely to perceive it as actually caring about them— and this lack of perceived benevolence creates a major hurdle to fostering trust. Not Every Job Requires Benevolence Of course, not every job requires a benevolent boss. Through a series of additional studies with over 1,500 U.S. employees, we found that how much workers trust AI management depends on how much empathy a situation demands. In situations where employees seek emotional support, such as crises, personal distress, or moments in which their sense of agency feels threatened, they report a greater need for empathetic engagement. In these situations, workers really want their manager to be able to authentically share their emotional state. As a result, they strongly prefer a human manager to an algorithm—even if the actions that the manager takes are exactly the same. Importantly, our findings demonstrate that people don’t mistrust AI because it actually acts in ways that are less benevolent than humans, but simply because it is perceived as less benevolent. In our studies, we were able to hold managers’ actions and communications constant, enabling us to measure the impact of just knowing that the same exact email or policy decision is coming from an AI versus a human. Conversely, in contexts that require more practical problem- solving than empathy (e.g., coordinating routine delivery orders or processing typical time-off requests), an AI manager’s lack of perceived benevolence is less of an issue. In such an environment, AI systems can reach comparable trust levels as their human counterparts simply by demonstrating reliability and competence. That said, even if a specific situation demands less empathy, we found that if you ask employees whether they would generally prefer a manager who is empathetic or one who is not, they (unsurprisingly) say that they would prefer the empathetic one. In other words, while there are some cases in which an AI boss may still be able to foster trust, people generally still tend to prefer a human. Bridging the AI Trust Gap So, what does this mean for leaders? The answer isn’t to abandon AI entirely. After all, when leveraged effectively, these tools can provide incredible value to workers and employers alike. But to start to bridge the trust gap between AI and human management, there are several steps organizations should take: Use AI for Execution, and Humans for Empathy Our research demonstrates that it’s best to use human managers for tasks that require empathy, but AI bosses can work well for more execution-focused work. For example, AI can optimize schedules by analyzing calendars, meeting patterns, and resource availability, or use real-time data to identify workflow bottlenecks and improve productivity. In contrast, organizations should stick to human managers for tasks such as coaching employees through personalized career development plans, mediating conflicts by interpreting nonverbal cues and cultural nuances, and providing support during crises and other emotional, high-pressure situations. Create Feedback Loops Between AI and Human Management Another important way to foster trust is to build feedback loops in which AI and human bosses provide continuous input on each other’s work. In this way, organizations can leverage both AI’s strengths in processing large volumes of data and identifying patterns and human strengths in contextual understanding and emotional intelligence. For example, IBM uses its Watson analytics platform to analyze employees’ project completion rates, collaboration patterns, goal achievement metrics, and even internal training data to generate detailed reports. Then, human managers review these reports, adding their own observations about each employee’s growth, challenges, and qualitative contributions. This collaborative approach to performance reviews has helped IBM increase employee engagement and satisfaction by offering clearer insight into growth opportunities. Moreover, creating feedback loops like these also helps refine AI systems over time, as human insights are fed back into the algorithm to improve its future analyses. It’s best to use human managers for tasks that require empathy. 1 2 Insight 6 HKUST Business Review