An Explorative Study on the Adoption of Explainable Artificial Intelligence (XAI) in Business Organizations

Artificial Intelligence (AI), particularly Deep Learning (DL), is expanding across industries, raising concerns about data processing opacity. This has increased the demand for Explainable Artificial Intelligence (XAI) solutions. Despite its growing relevance, understanding XAI adoption drivers and its potential business impact is still limited. This study employs an exploratory qualitative approach, conducting eleven in-depth interviews to identify key factors influencing XAI adoption in business. These factors include perceived benefits, technological readiness, organizational and business factors, leadership, strategy, industry and governmental pressures and user needs. Furthermore, we use the Technology Organization and Environment model (TOE) to develop a theoretical framework that highlights technological readiness, impacts on the core business and consumer influence, determining the business value of XAI. Moreover, this paper provides managerial implications on navigating XAI adoption, by engaging stakeholders and balancing technological maturity with competitive pressures.