This study aims to examine how three dimensions of generative artificial intelligence (GenAI), namely, capability, application and knowledge modelling, are associated with entrepreneurial innovation, and whether innovation mediates their associations with entrepreneurial performance and entrepreneurial success in startups and small and medium-sized enterprises (SMEs).
Survey data from 317 startup and SME owners, partners and employees were analysed using confirmatory factor analysis followed by AMOS-based structural path analysis in IBM SPSS analysis of moment structures (AMOS) 20.0 with maximum likelihood estimation. Specific indirect effects were assessed using bias-corrected bootstrapping with 5,000 resamples and 95% confidence intervals.
All three GenAI dimensions were positively associated with entrepreneurial innovation, with knowledge modelling showing the largest reported association. Entrepreneurial innovation was positively associated with performance and success, and all six specific indirect associations were significant. The largest reported indirect associations were observed for knowledge modelling.
The cross-sectional, single-source design supports associations rather than causal claims.
Entrepreneurs should prioritise knowledge-related practices, verification of AI-generated information and human judgement rather than treating tool use alone as evidence of innovation. Policy and support programmes should develop these practices alongside access to GenAI tools.
The study distinguishes GenAI capability, application and knowledge modelling within one entrepreneurial model and examines entrepreneurial innovation as a mediating knowledge-conversion pathway linking these dimensions with performance and success.
