The AI-Enhanced Opportunity Nexus: How Artificial Intelligence is Reshaping Entrepreneurial Problem Ideation

Entrepreneurs increasingly adopt artificial intelligence (AI) tools during the earliest stage of venture

creation—problem ideation. To clarify how AI reshapes this stage of opportunity identification, this

study conducts a systematic scoping review of emerging literature. Searches were performed in Google

Scholar and Scopus using Boolean queries combining “artificial intelligence,” “entrepreneurship,”

“opportunity identification,” and “ideation.” After removing duplicates and screening records against

predefined inclusion and exclusion criteria, 17 studies were included. Data were extracted using a

structured coding framework capturing the entrepreneurial stage, AI’s functional role, reported benefits

and risks, and boundary conditions. Findings show that AI expands entrepreneurs’ cognitive search

space, accelerates pattern recognition, and supports reframing of problem domains, but also introduces

risks of convergence, reduced contextual judgment, and overreliance. Synthesizing these patterns, the

review develops the AI-Enhanced Opportunity Identification Framework: Human–AI Co-Evolutionary

Extension, a refinement of a foundational opportunity identification model. The framework identifies

three cross-stage AI roles—Inspirer, Analyst, and Organizer—and situates ideation within iterative

human–AI collaboration shaped by institutional enablers such as AI-integrated incubators. This review

contributes by mapping empirical evidence on AI’s influence on entrepreneurial ideation, clarifying

mechanisms of human–AI co-creation, and outlining future research opportunities on judgment, novelty,

and ecosystem-level effects.