The rapid proliferation of Generative Artificial Intelligence (Gen AI) has
created an intriguing paradox in organizations: while employees
increasingly recognize Gen AI's potential to enhance productivity and
innovation, many use these tools covertly. Drawing on dual-process
theory, we introduce and validate the concept of Stealth Use of
Generative AI Resources (SUGAR)—employees' hidden use of Gen AI
tools within professional settings. Through rigorous scale development
across multiple samples in the UK and China, we establish SUGAR as
distinct from related constructs including AI usage and attitudes.
Analysis of multi-wave data from 207 employees reveals that SUGAR
undermines task performance by disrupting employees' natural learning
processes and triggering feelings of professional inadequacy.
Specifically, while general AI usage positively relates to performance,
concealing such usage reduces reflective learning opportunities and
increases impostor feelings, ultimately reducing performance. Our
findings advance organizational theory by revealing how AI concealment
creates unique cognitive demands that cannot be overcome by
motivational factors, while also demonstrating how employees' well
intentioned efforts to leverage AI capabilities through covert use may
ultimately impair their performance. This research initiates important
theoretical conversations about the unintended consequences of
undisclosed AI usage in organizations and provides practical insights for
developing more nuanced approaches to AI governance that balance
productivity with transparency.

Note: This study is collaborated with colleagues from China, New
Zealand and Netherlands.

Lin Ma
Beihang University (BUAA)

Niannian Dong
University of Science and Technology Beijing

Lu (Lucy) Xing
University of Auckland

Shuai Yuan
University of Amsterdam