Professional and Digital Agency in AI‑Driven Work: Multilevel Factors Shaping Adoption and Engagement

Abstract

The rapid proliferation of artificial intelligence (AI) is reshaping work structures, task content, and skill requirements across contemporary organization levels, altering how agency is exercised in everyday work. This study investigates perceived enablers and barriers to generative AI adoption and engagement in knowledge work, interpreted through the lenses of professional and digital agency. The analysis is grounded in Self-Determination Theory, focusing on competence, autonomy, and relatedness as foundational mechanisms through which agency emerges and evolves. The study draws on survey data from 1,131 knowledge workers in public and private sectors, using ranked enablers and barriers related to generative AI adoption. The results suggest that the prioritization of enablers and barriers was associated primarily with personal motivation and time resources rather than with broad organizational relationships or psychological contracts. Lack of time was the most frequently top-ranked barrier and showed the most differentiated pattern of associations across respondent groups. The findings contribute to understanding AI-mediated agency by indicating that localized, practice-based conditions differentiated the rankings more than generalized organizational factors.