The study investigates the ways in which gender affects startup adoption of artificial intelligence technology by examining the barriers of female entrepreneurs’ face in the social system. The paper utilizes Social Role Theory along with Gendered Innovation Theory combined with the Resource-Based View as these theoretical frameworks analyze gender effects on entrepreneurial behavior and resource acquisition and innovation potential in AI-powered businesses. The females are nowadays with ongoing funding issues and skill shortages and face discrimination throughout society, which hinders their participation in tech business ventures. Studies on established AI ventures led by female demonstrate that inclusive practices create better innovation outcomes and handle ethical issues while developing flexible and socially aware innovations through their approaches. The recommendations are aimed at all ecosystem stakeholders, who also attract policymakers to create a gender-equitable AI system through adequate funding initiatives and structured networks with mentorship assistance.