AI business applications training and business outcomes: an inclusive intervention for underrepresented entrepreneurs

This study investigates the associations between university-led training in AI business applications and business outcomes among small firms, with a focus on underrepresented entrepreneurs in England, Wales, and Scotland. A total of 121 non-native, disabled, and non-heterosexual entrepreneurs participated in a four-month training programme covering AI applications for communication, finance, project management, and other key business functions. Data were collected before the training (2023) and one year later (2024). Using panel data estimates, the findings indicate that, post-training, firms experienced an increase in digital competencies, which were positively associated with customer satisfaction, entrepreneurs’ empowerment, and revenue growth. Notably, interaction effects showed that these associations were significantly strengthened following the training. Additional results reveal that, after the training, firms not only adopted a greater number of AI business applications but also used them more frequently. These behaviours were found to be associated with improvements in business outcomes. The study demonstrates how innovative educational interventions can support entrepreneurs in developing digital competencies within technology-driven environments, thereby enabling more inclusive access to tools and fostering equitable participation in the digital economy. The findings suggest that structured, application-focused training, when clearly aligned with business operations, can accelerate firms’ technological adoption and effective use. Continued investment in AI training, sector-specific courses, and practitioner-led learning communities can therefore support small firms and underrepresented entrepreneurs in enhancing their digital competencies and achieving meaningful improvements in performance. The study contributes by developing the AI Business Applications Training Model, reflecting upon theoretical pathways, empirical patterns, and policy implications.<p></p>