The problem solvers' problem-solver - An exploratory qualitative study of Management Consultants' adoption of Generative AI

Sammanfattning

The management consulting industry, historically resilient to technological disruptions, faces a potential paradigm shift due to rapid advancements in Generative Artificial Intelligence (GenAI). GenAI's ability to perform a broad range of language tasks and achieve complex reasoning distinguishes it from previous technological disruptions. This exploratory study examines what influences management consultants' adoption of GenAI. The extended Technology Acceptance Model (TAM2) is leveraged as a framework to understand the decision-making process. Using a qualitative approach, semi-structured interviews were conducted with 21 management consultants from different firms in Sweden. The empirical results from the inductive thematic coding reveal four themes that influence a consultant's adoption: role-specific aspects, technological factors, social dynamics, and identity threat and opportunity. Key takeaways include the relevance of GenAI in enhancing productivity and cognitive expansion, particularly for junior consultants. Moreover, the chat interface of GenAI increases accessibility, though manual oversight and concerns about sensitive data act as barriers. Furthermore, the perceptions of peers and support from the firm influence individual consultants' adoption decisions. Lastly, consultants perceive threats and opportunities to their identities, striving to stay relevant and competitive while maintaining control over their creative processes. Our analysis shows that TAM2 can effectively explain and enhance our understanding of what influences the adoption of GenAI, providing a robust framework for exploratory qualitative studies. Additionally, our study suggests the contribution of identity as a determinant, which is not addressed by TAM2. This warrants further investigation into how management consultants and, more broadly, knowledge workers perceive threats and opportunities to their identities in the context of GenAI.