Based on extended technology, organization and environment (TOE) theoretical framework, the purpose of this study is to investigate the influence of generative artificial intelligence (AI) enablers (GAIEs) and generative AI readiness (GAIR) constructs on the generative AI adoption intention (GAII). This exploration is facilitated through the mediation of top management support and moderation of environmental factors (EFs).
To empirically validate the framework, this study uses PLS-SEM technique. Data is collected from 425 owners and managers from IT companies in Pune, India ensuring adherence to recommended sample size guidelines.
This study brings light to the intricate relationships between GAIEs, GAIR and GAII, considering the impact of MS and EF. It is found that GAIEs and GAIR factors significantly impact GAII.
This study contributes to theoretical understanding by expanding existing literature using extended TOE framework considering generative AI adoption. This research also holds significance for practitioners seeking insights into the readiness to GAII. However, the data were collected from respondents in Pune (India), which hinders generalizability of the results. The study results depend on cross-sectional data which could have causality and endogeneity defects.
Previous studies have mainly focused on AI or related technologies, leaving a noticeable gap in the literature concerning readiness specifically for generative AI which the present study fills.
