The Impact of Generative AI on IT Consultants’ Perceived Autonomy and Competence: A Paradoxical Reality

Sammanfattning

Background: Generative Artificial Intelligence (Gen-AI) is increasingly integrated into knowledge-intensive work, including IT consulting, where value creation depends on technical expertise, problem-solving, contextual judgment, and client trust. Existing research has largely examined Gen-AI through productivity, efficiency, and organisational adoption perspectives. Less attention has been given to how individual consultants experience Gen-AI psychologically, particularly in relation to perceived autonomy and perceived competence. Purpose: The purpose of this study is to examine how the integration of Gen-AI into daily consulting practices shapes IT consultants’ perceived autonomy and competence. Drawing on Self-Determination Theory, the study explores how consultants experience changes in control, professional capability, learning, and responsibility when Gen-AI becomes part of their work. Method: The study adopts a qualitative, interpretive research design based on a single case study of a Swedish IT consulting firm. The study conducts five semi-structured online interviews and one written email-based response with participants from technical, managerial, and commercial roles. The data were analysed using thematic analysis, supported by an abductive approach that combined theoretical sensitivity to autonomy and competence with openness to emergent themes. Conclusion: The findings suggest that Gen-AI shapes IT consultants’ perceived autonomy and competence through a layered paradox. At the surface level, Gen-AI supports autonomy and competence by enabling consultants to retain final decision authority, work more efficiently, and expand their task capacity. However, repeated reliance on Gen-AI may weaken cognitive autonomy and experienced mastery by reducing independent problem formulation, hands-on learning, and perceived ownership of expertise. The study further identifies seniority as an emergent boundary condition, as experienced consultants appear better positioned to validate AI outputs and use Gen-AI critically, while junior consultants’ vulnerability remains an important concern for future research. The thesis contributes to research on Gen-AI in knowledge-intensive work, Self-Determination Theory, and the automation–augmentation paradox by showing that Gen-AI’s impact cannot be evaluated only through productivity outcomes, but must also be understood through its effects on agency, mastery, learning, and professional responsibility