Beyond the Prototype: An AI-Enabled Framework for Engineering Innovation and Startup Readiness

Engineering institutions generate numerous student projects each year, but many technically successful projects terminate at prototype demonstration without progressing toward user validation, commercialization, startup development, or societal deployment. This paper addresses this practical gap by proposing an AI-Enabled Problem-to-Startup Conversion Framework (PSCF) for transforming engineering student projects into validated innovation and entrepreneurship opportunities. Unlike conventional entrepreneurship approaches that frequently begin with business ideation, the proposed framework begins with an authentic industrial or societal problem and progresses through evidence-based problem validation, AI-assisted ideation, engineering design, prototype development, user validation, techno-economic assessment, business-model development, and societal-impact evaluation. A Startup Conversion Readiness Index (SCRI) is additionally proposed to evaluate projects across five dimensions: problem validation, technical feasibility, user value, commercial feasibility, and societal impact. The framework positions artificial intelligence as an augmentation technology for information exploration, alternative generation, design support, and decision assistance while retaining human engineering judgement and verification. The proposed approach establishes a structured bridge between project-based engineering education and entrepreneurship by identifying whether a student project should remain an academic prototype, progress as a validated innovation, enter incubation, or be considered for startup or social-enterprise development.

Artificial intelligence, engineering education, innovation

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