Applying the Technology Acceptance Model to AI decisions in the Swedish Telecom Industry

Abstract: · Purpose Artificial Intelligence is one of the trend areas in research. It is applied in many different contexts successfully including Telecom sector. The purpose of this study is to replicate the study done in application of AI in the medical sector to understand the similar challenges of using AI in the Telecom sector. · Design/Methodology/approach Online questionnaire-based empirical study is used, and 190 responses were collected. First authors compare the general Technology acceptance model framework used in the medical sector and compare it with the non-AI users. Afterwards, this study proposes the improved TAM model that best fits into the Telecom sector. Later, this study uses the proposed improved model to compare the AI and non-AI users to understand the acceptance of AI-technology tools application in the Telecom sector. · Findings Confirmatory Factor analysis revealed that the general TAM model fit is adequate and applicable in Medical sector as well as in the Telecom sector. Also, hypothesis testing using SEM concluded that the general supported paths between the constructs and variables related to PU, PEU, SN, ATU, and BI in the medical sector is not same as in the Telecom sector. · Research limitations Results are based on the limited datasets from one of the larger companies in Telecom sector which could leads to inherent biases. Authors not sure if “AI-technology tools” in the questions have common understanding across all the respondents or not. · Results TAM model cannot be generalized across the sectors. An improved model has been developed used in the Telecom sector to analyze the user’s behavior and acceptance of AI technology. An extended model has been proposed which can be used as a continuation of this study. Keywords: Medical, Telecom, Artificial Intelligence, Network Intelligence, Technology acceptance model (TAM), Confirmatory Factor analysis (CFA), Structural equation modeling (SEM), Perceived usefulness (PU), Perceived Ease of Use (PEU), Subjective Norms (SN), Attitude Towards AI Use (ATU), Behavioural Intention (BI).