Speaker
Description
Hashim, M.
Federal University of Education, Zaria
mansirhashim57@gmail.com
Track: Digital Transformation in Higher Education
Traditional university venture incubators and entrepreneurship curricula frequently face structural bottlenecks, including delayed market testing, resource constraints, and fragmented mentorship. This study introduces an AI-enabled framework for entrepreneurship education that integrates Generative AI co-pilots and predictive analytics directly into the lean startup lifecycle. Utilizing generative language models for automated value proposition design and predictive machine learning models for synthetic market trend validation, the architecture allows student founders to rapidly iterate low-fidelity prototypes, simulate consumer personas, and assess financial viability in real time. Deployed across a university business incubator network over a two-semester pilot, the efficacy of the framework was evaluated by measuring prototype iteration velocity, market validation accuracy, and early-stage seed funding acquisition rates compared to control cohorts using conventional ideation methods. The findings demonstrate that student ventures utilizing AI-driven tools achieved significantly faster market-fit iteration cycles and developed more robust, risk-mitigated business models. Additionally, the platform democratized access to specialized business development expertise, transforming university incubators into agile, digital-first innovation hubs. This research provides higher education administrators and entrepreneurship educators with a scalable, data-driven blueprint for fostering high-growth student ventures, accelerating technology transfer, and aligning campus innovation ecosystems with regional economic needs.