The Adoption and Organisational Impact of AI-Driven Cybersecurity Solutions: A TOE–Trust Integrated Model with Evidence from Business Organisations and Listed Companies

Abstract

The adoption of Artificial Intelligence (AI)-based cybersecurity is becoming an essential component of organisational resilience, but evidence on the drivers and impacts of AI-based cybersecurity adoption is limited and largely composed of primary or secondary data sources only. This study combines the Technology–Organisation–Environment (TOE) framework with Trust theory to investigate the adoption of AI in the context of cybersecurity in ten top Indian listed financial organizations. A structured questionnaire was sent to managers, IT security experts, and employees who provided 200 responses from which 164 were obtained after data screening. The results indicate that Technological Readiness (β=.291, p<.001) and Organisational Capacity (β=.256, p<.001) both significantly and positively affect organisational performance, whereas Environmental Pressure (β=.111, p=.057) has a positive but non-significant effect. Organisational Trust partially mediates the TOE–Performance relationship (indirect effect=.202, 95% CI [.116, .304]). A mean score analysis was conducted to compare the extent of disclosure of private banks with NBFCs and the sampled insurer based on a scorecard using an AI-Driven Cybersecurity Disclosure Index (ADCI) derived from their Annual Reports and BRSR filings, and the private banks scored higher at 6.6/20 compared to the NBFCs and sampled insurer. Notably, environmental/regulatory factors impacted corporate disclosure but not individual level perceptions of adoption, pointing to technological capability, organisational support and trust as key factors in successful adoption of AI in the cybersecurity space.