Accepting generative artificial intelligence in consulting services

: an analysis of success factors

Abstract

The present study examines the success factors that influence the acceptance of Generative Artificial Intelligence (GenAI) among business consultants. While numerous research studies have developed and expanded models for general technology acceptance, there are still few studies that address the acceptance of GenAI in specific professional contexts such as the consulting industry. This work fills this research gap by developing a new model to investigate the acceptance factors of GenAI among business consultants. The model is based on established theories such as the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Task-Technology Fit (TTF) model, which have been combined into a new conceptual framework. For empirical verification, a quantitative study was conducted with 147 business consultants to identify key success factors on the intention to use and acceptance of GenAI. The results show that the fit between technology and tasks (Task-Technology Fit, TTF), the expected performance improvement (Performance Expectancy, PE) and the Behavioural Intention (BI) play a crucial role in the acceptance of GenAI in the business consulting context. The study highlights the need amongst companies for targeted training, practical use cases, and a strategic integration of GenAI into existing workflows to promote sustainable acceptance. The results provide both theoretical and practical implications for consulting firms to support the successful implementation of GenAI

Date of Award	28 Apr 2025
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Filipa Serpa Pinto (Supervisor)