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AI startup strategy : a blueprint to building successful artificial intelligence products from inception to exit

By: Publication details: Berkeley Apress 2023Description: 428 pISBN:
  • 9781484295014
Subject(s): DDC classification:
  • 658.4038 MAH
Summary: AI Startup Strategy: How to Build an Enterprise AI Start-up" by Dr. Andy Chun. The book is a guide to help entrepreneurs and innovators create and grow successful AI-powered businesses for the enterprise market. The book covers various topics such as identifying the business need and value, validating the market and technology, designing the AI product and architecture, developing and operationalizing the AI solution, building and managing the AI team, and attracting and retaining customers and users. The book also provides insights and tips on the best practices and challenges of building an enterprise AI start-up, such as choosing the right business model, registering and valuing the AI intellectual property, and complying with the ethical and legal standards.
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1. Fundamentals of AI Startup 2. AI Startup Landscape 3. Product Market Validation for AI-First SaaS 4. Product Market Validation for AI as a Service (AlaaS) 5. AI Product Strategy 6. Human-Centered AI-Experience Design 7. Human-Centered AI Developer Experience Design 8. Building AI Platform 9. Go-To-Market Strategy for AI Startup 10. AI Startup Exit Strategy

AI Startup Strategy: How to Build an Enterprise AI Start-up" by Dr. Andy Chun. The book is a guide to help entrepreneurs and innovators create and grow successful AI-powered businesses for the enterprise market. The book covers various topics such as identifying the business need and value, validating the market and technology, designing the AI product and architecture, developing and operationalizing the AI solution, building and managing the AI team, and attracting and retaining customers and users. The book also provides insights and tips on the best practices and challenges of building an enterprise AI start-up, such as choosing the right business model, registering and valuing the AI intellectual property, and complying with the ethical and legal standards.

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