This paper surveys ten studies relevant to AI-assisted entrepreneurship and synthesizes their findings into a proposed intelligent framework for startup ideation, business planning and entrepreneurial growth. The reviewed work spans AI adoption, ChatGPT-based idea evaluation, intellectual-property strategy, natural-language processing, startup initiative analysis, sentiment modeling, lean software practices, retrieval-augmented blueprint generation and knowledge-graphbased risk assessment. A qualitative comparison identifies complementary capabilities and persistent concerns involving evidence quality, data availability, privacy, bias and generalizability. Building on these findings, a venturestage-aware advisory architecture and methodology flowchart are proposed for both aspiring and existing entrepreneurs. The design separates user facts, retrieved evidence and generated assumptions, and supports human validation and iterative revision. This is a literature review and conceptual methodology; no implementation results or startup-success predictions are claimed.

Ajay Chopra, Vedanti Patil, Sannidhi Shetty, Sumayya Shaikh, Prof. Sandeep More, "A Survey of an Intelligent Framework for Startup Ideation, Business Planning, and Entrepreneurial Growth" International Journal of Computer Science and Engineering Development, V1(4): Page(200-207) September - October 2026. ISSN: 3139-0862. www.ijcsed.com. Published by Scientific and Academic Research Publishing.