Abstract

Generative AI is reshaping how organizations operate, introducing new complexities into employees’ cognitive, emotional, and behavioral patterns. To capture the nuances of this transformation, we introduce Digital Embodied and Extended Presence (DEEP)—a process theory that explains how individuals regulate Generative AI use over time. Rather than focusing on static adoption, DEEP emphasizes how employees engage in ongoing metacognitive negotiation of trade-offs, such as productivity versus identity. These negotiations are neither linear nor uniform but involve recalibrations shaped by internal regulation mechanisms that evolve with experience. Understanding these dynamics is crucial for strengthening information assurance at the individual level, where secure and ethical use of AI ultimately begins. The acceleration of Generative AI adoption has created a dual imperative for information assurance in the workplace: defending data while enabling responsible engagement. Employees are not only tasked with safeguarding sensitive information and complying with governance protocols but also with verifying the accuracy of AI-generated outputs and ensuring their ethical use. These responsibilities demand more than policy compliance; they call for adaptive, process-driven regulation of AI use. Thus, this study asks a timely and practical question: How do employees, over time, regulate Generative AI use to balance its productivity gains with the demands of ethical and secure application? To answer this question, we conducted a one-year, three-wave longitudinal interview study. Participants included financial analysts, compliance officers, and risk assessors—roles characterized by high autonomy and data sensitivity. Each interview wave combined structured assessments of behavior change with open-ended reflections to explore the motivations and contextual factors influencing those changes. Findings reveal that employee engagement with Generative AI unfolds in a continuous cycle of appraisal, emotional regulation, and behavioral adaptation. Employees do not merely adopt or reject Generative AI; they regulate it through five interdependent mechanisms. First, they confront attentional challenges, initially experiencing cognitive overload and distraction but gradually learning to direct attention strategically through metacognitive scaffolding. Second, they recalibrate how they process information. While early reliance on Generative AI often introduces bias and misinformation, employees eventually develop structured verification habits that foster critical engagement. Third, emotional regulation plays a key role. Employees must manage anxiety and apprehension, especially surrounding AI’s ethical or legal implications, before they can integrate it confidently. Fourth, they refine data handling approaches. While Generative AI aids workflow continuity, it introduces security risks that employees meet with increased procedural awareness. Finally, meaning-making shifts as individuals transition from fearing deskilling to co-evolving with Generative AI tools, using them to strengthen their professional identity and agency. This regulatory evolution unfolds across three distinct phases. The first phase, emotional adjustment, is marked by volatility, uncertainty, and ethical hesitation. The second, strategic competence development, reflects growing procedural familiarity and validation heuristics. The final phase, integrated regulation, involves stabilized, self-directed use patterns that align Generative AI augmentation with professional norms and information assurance practices. The DEEP framework captures this transformation by conceptualizing Generative AI not just as a tool but as a cognitive extension. Embodied Presence captures the tactile, immersive engagement that arises from employees’ task-oriented interactions with AI, where experimentation and adaptation unfold in real time. In contrast, Extended Presence denotes a more internalized integration of AI into one’s cognitive repertoire and evolving professional identity. This dual presence—simultaneously experiential and existential—offers a conceptual foundation for the secure, responsible, and meaningful deployment of Generative AI in complex organizational settings.

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