"If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace

2026-02-01

AI Summary

This study addresses the empirical gap in understanding how knowledge workers develop generative AI literacy through social interaction in the workplace. Drawing on semi-structured, in-depth interviews with 19 knowledge workers across diverse industries and employing qualitative thematic analysis, the research uncovers a dynamic process wherein individuals construct AI literacy through peer knowledge sharing and practices such as concealing AI usage traces. While such concealment is often perceived as a marker of professional competence, it simultaneously undermines transparency and limits opportunities for collective learning. Challenging the prevailing individual-skills-centered paradigm of AI literacy, this work advocates for fostering open dialogue, enhancing the visibility of AI-related knowledge, and institutionalizing collaborative learning mechanisms to support more effective organizational integration of generative AI.

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Philosophy and Ethics of AI: AI & Epistemology
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Generative AI (GenAI) tools are rapidly transforming knowledge work, making AI literacy a critical priority for organizations. However, research on AI literacy lacks empirical insight into how knowledge workers'beliefs around GenAI literacy are shaped by the social dynamics of the workplace, and how workers learn to apply GenAI tools in these environments. To address this gap, we conducted in-depth interviews with 19 knowledge workers across multiple sectors to examine how they develop GenAI competencies in real-world professional contexts. We found that, while knowledge sharing from colleagues supported learning, the ability to remove cues indicating GenAI use was perceived as validation of domain expertise. These behaviours ultimately reduced opportunities for learning via knowledge sharing and undermined transparency. To advance workplace AI literacy, we argue for fostering open dialogue, increasing visibility of user-generated knowledge, and greater emphasis on the benefits of collaborative learning for navigating rapid technological developments.

Problem

• Generative AI
• AI literacy
• workplace social dynamics
• knowledge work
• collaborative learning

Innovation

• Generative AI literacy
• workplace social dynamics
• knowledge sharing
• AI transparency
• collaborative learning