The convergence of artificial intelligence and blockchain technology is reshaping how startups raise capital, build products, and generate sustainable revenue. This book provides a rigorous and accessible examination of token-based financing models specifically designed for AI-native companies — those that place machine learning and automated intelligence at the core of their business. Readers will learn how utility tokens, governance tokens, and revenue-sharing mechanisms can replace or complement traditional venture capital, enabling founders to align early users with the long-term success of the platform. The book explores the economic architecture behind recurring revenue in decentralized environments, explaining how AI products that charge in tokens can create compounding network effects while reducing reliance on advertising or data monetization. It also covers regulatory considerations, due diligence frameworks for token investors, and practical case studies from projects that have successfully navigated the transition from prototype to scaled AI service. Whether you are an entrepreneur designing a token structure, an investor evaluating AI token projects, or a strategist studying the future of tech finance, this book offers the analytical tools and conceptual grounding needed to participate confidently in this emerging market.
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