Factors affecting customer adoption of AI digital agents in service operations: an assessment of relative importance
Aman Pathak, Veena Bansal · Behaviour and Information Technology · 2025
AI digital agents have emerged as transformative tools that enhance customer service experience while reducing operational costs. Existing studies on AI digital agent adoption have utilised various Information Systems (IS) theories and models. However, no prior research comprehensively integrates an extensive set of factors from multiple IS models to determine their relative significance in influencing adoption. This study identified 17 factors, including six sub-factors, based on a thorough review of extant literature and discussions with experienced users. These factors were categorised in a novel framework comprising four dimensions: AI service experience (S), personal dimension (P), users’ technology perception (T), and social dimension (S). Rankings from 15 experts were analyzed using the Rough Step-Wise Weight Assessment Ratio Analysis (Rough-SWARA) method to evaluate the relative importance of the factors. Results indicate that AI service experience is the most influential dimension, followed by the personal dimension. Key factors driving adoption include AI quality features, data privacy, trust, price-value, hedonic motivation, usefulness, and social influence. This study contributes to the literature by introducing the first comprehensive model to organise and study the relative importance of the adoption factors. These insights will assist managers in prioritising strategies for developing and deploying AI digital agents.