BREAKING BARRIERS: THE IMPACT OF CHALLENGES ON AI ADOPTION IN HRM WITHIN BENGALURU’S IT SECTOR

Abstract

Purpose: In the study, the researcher explores how critical obstacles, including people, organizational, technological, and environmental, affect the implementation of Artificial Intelligence (AI) in Human Resource Management (HRM). Although AI has a great potential to enhance recruitment, training, performance management, and workforce analytics, its implementation is limited by multidimensional barriers. The proposed study should be based on empirical data in the Indian IT industry, where implementing AI in HR functions is becoming more and more topical and yet is often limited due to internal and external barriers.

Methods: The research strategy was a quantitative one and was based on the analysis of 120 HR professionals with experience in IT organizations. Perceptions of barriers and AI adoption were captured with the help of a structured questionnaire, which was premised on a five-point Likert scale. The instrument validity was determined by Exploratory Factor Analysis (KMO = 0.876, p < .001, Bartletts Test) and reliability was validated via Cronbachs Alpha values more than 0.70. The hypothesis regarding the relationships between variables was tested using SPSS and AMOS through descriptive statistical analysis, exploratory and confirmatory analysis factor, and Structural Equation Modeling (SEM).

Findings: The findings showed that the most significant negative impact on the adoption of AI is the organizational barriers that include the unavailability of the resources, the poor decision-making framework, and unreceptive culture. There were also technological issues such as poor IT infrastructure and lack of compatibility with HR strategy that proved to be very limiting. Barriers related to the environment like the reliability of the vendors and readiness of the policies were identified to have a smaller but significant influence, and the people related barriers like the gaps in communication and training were important but seemed to be easier to deal with in comparison to the structural and technological constraints.

Implications: The research reveals that organizations need to enhance the commitment of the leadership, resource allocation, and IT infrastructure and promote vendor collaboration and clarity of regulations. Training and awareness programs should also be of priority to the managers in order to handle workforce-level issues.

Novelty: This research provides contribution to the body of literature by combining four types of barriers into one empirical model and testing their comparative influence with the help of SEM in the Indian IT sector. It provides a timely contribution to the HRM in terms of AI usage, especially during the post-pandemic era of digital transformation.