The Janus Face of Artificial Intelligence Feedback: Deployment Versus Disclosure Effects on Employee Performance

Abstract

Companies are increasingly using artificial intelligence (AI) to provide performance feedback to employees, by tracking employee behavior at work, automating performance evaluations, and recommending job improvements. However, this application of AI has provoked much debate. On the one hand, powerful AI data analytics increase the quality of feedback, which may enhance employee productivity (“deployment effect”). On the other hand, employees may develop a negative perception of AI feedback once it is disclosed to them, thus harming their productivity (“disclosure effect”). We examine these two effects theoretically and test them empirically using data from a field experiment. We find strong evidence that both effects coexist, and that the adverse disclosure effect is mitigated by employees’ tenure in the firm. These findings offer pivotal implications for management theory, practice, and public policies.

Keywords: Artificial Intelligence, Employee Productivity, Employee Performance Feedback, Employee Perceptual Bias, Field Experiment, New Technology in Management