Paper Number
ECIS2026-2301
Paper Type
CRP
Abstract
While artificial intelligence (AI) is increasingly transforming a wide range of occupations, knowledge workers in particular have been found to be affected by AI’s transformative power. Drawing on self-determination theory, this study examines how AI-driven task transformations affect the three basic psychological needs of autonomy, competence, and relatedness. Based on industry-specific focus groups with knowledge workers, this study captures the impact of AI integration on individuals' self-determination. Our findings show that while AI can enhance autonomy and competence by increasing productivity and supporting learning, it can also undermine these needs through cognitive dependency or perceived skill loss. Similarly, AI can facilitate collaboration and help overcome communication barriers, but also contribute to social friction and reduced interpersonal connectedness, and introduce competence authenticity as a novel lens highlighting how AI decouples performance from perceived mastery. This study offers a conceptual model that illustrates the dynamic interplay of psychological needs in AI-mediated work, providing theoretical and practical insights into the future of self-directed knowledge work.
Recommended Citation
Frenzel-Piasentin, Adeline; Finze, Nikola; and Kosok, Marie-Sophie, ""You Don't Have To Use What The AI Suggests" - A Self-Determination Perspective On Artificial Intelligence In Knowledge Work" (2026). ECIS 2026 Proceedings. 8.
https://aisel.aisnet.org/ecis2026/resp_AI/resp_AI/8
"You Don't Have To Use What The AI Suggests" - A Self-Determination Perspective On Artificial Intelligence In Knowledge Work
While artificial intelligence (AI) is increasingly transforming a wide range of occupations, knowledge workers in particular have been found to be affected by AI’s transformative power. Drawing on self-determination theory, this study examines how AI-driven task transformations affect the three basic psychological needs of autonomy, competence, and relatedness. Based on industry-specific focus groups with knowledge workers, this study captures the impact of AI integration on individuals' self-determination. Our findings show that while AI can enhance autonomy and competence by increasing productivity and supporting learning, it can also undermine these needs through cognitive dependency or perceived skill loss. Similarly, AI can facilitate collaboration and help overcome communication barriers, but also contribute to social friction and reduced interpersonal connectedness, and introduce competence authenticity as a novel lens highlighting how AI decouples performance from perceived mastery. This study offers a conceptual model that illustrates the dynamic interplay of psychological needs in AI-mediated work, providing theoretical and practical insights into the future of self-directed knowledge work.
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