Artificial intelligence in entrepreneurship: a comprehensive review of adoption patterns, challenges, and strategic implementation in early-stage ventures

Artificial intelligence (AI) is reshaping entrepreneurship, especially in pre-incubation, incubation and early growth stage ventures. This review examines how entrepreneurs adopt and strategize around AI across early venture stages. It has three objectives: assess adoption patterns, identify barriers, and study strategic frameworks. Insights show that adoption paths vary by stage. Barriers exist at technological, organizational, and environmental levels. Integration frameworks like APSS and the Three perspectives model guide implementation. These findings help entrepreneurs, incubators, and policymakers match AI readiness with venture growth. @A comprehensive review was conducted using Scopus (2021–2025) to target peer-reviewed articles on AI adoption in entrepreneurship. Search terms included “AI adoption,” “entrepreneurial AI barriers,” and “AI strategy.” Studies not related to ventures or without empirical or theoretical value were excluded. AI Adoption patterns: entrepreneurs use AI for ideation, validation, efficiency, and scalability across various stages of ventures. Barriers: Challenges span technological (e.g., infrastructure, skill gaps), organizational (e.g., resistance, funding), and environmental (e.g., regulation, ethics). Strategic integration: Frameworks like “AI for/in/as strategy,” AI Strategy framework, APSS, and OKRs guide integration, shaped by venture size and maturity. Entrepreneurs, incubators, and policymakers can use these insights to enhance AI readiness and strategic alignment in ventures. Research should study how AI works in each business sector. It should check ethical issues, local rules, and how people and AI can work together to build new things. This review maps adoption trajectories, barriers, and strategies, offering a foundation for AI-driven entrepreneurial innovation.