AI-enabled human capital management (HCM) software adoption using full consistency method (FUCOM): evidence from banking industry

Purpose: Artificial intelligence (AI)-based human capital management (HCM) software solutions represent a potentially effective way to leverage and streamline a bank’s human resources. However, despite the attractiveness of AI-based HCM solutions to improve banks’ effectiveness, to the best of the authors’ knowledge, there are no current studies that identify critical success factors (CSFs) for adopting AI-based HCM in the banking sector. This study aims to fill this gap by investigating CSFs for adopting AI-based HCM software solutions in the banking sector. Design/methodology/approach: Full consistency method methodology and technology–organization–environment, economic and human framework are used for categorizing and ranking CSFs. Findings: The study identifies the technological and environmental dimensions as the most and least important dimensions for AI-based HCM adoption in banks. Among specific CSFs, compatible technology facilities, sufficient privacy and security and relative advantages of technology over competing technologies were identified as the most important. Implementation of AI-based HCM solutions requires significant outlays of resources, both human and financial, for banks. Originality/value: The study provides bank administrators a set of objective parameters and criterion to evaluate the feasibility of adopting a particular AI-based HCM solution in banks.