Hu Xiu·2025-06-03 10:12Core Insights - A new wave of AI-native companies is emerging globally, defined as those that integrate AI as a core product or service from inception, driving value creation and business innovation [1] - The research focuses on three key questions regarding the technologies, applications, and structural changes brought about by AI-native enterprises [1] Group 1: Overview of Global AI-native Ecosystem - The global generative AI landscape has formed three main foundational model ecosystems centered around OpenAI, Anthropic, and Google [2] - OpenAI's ecosystem is the largest, with 81 startups and a total valuation of approximately $63.46 billion, showcasing a diverse range of applications [2] - Anthropic's ecosystem consists of 32 companies valued at around $50.11 billion, focusing on enterprise-level applications with high safety and reliability requirements [3] - Google's ecosystem is the smallest, with 18 companies valued at about $12.75 billion, but it is growing rapidly due to its technological integration and vertical innovation [3] Group 2: Multi-model Access Strategy - Many AI-native companies are adopting multi-model access strategies to leverage the strengths of different foundational models and reduce dependency on a single ecosystem [4] - Companies like Anysphere and Jasper support multiple model integrations, enhancing their competitive edge [4] - These companies typically follow a B2B2B model, focusing on sectors like data, marketing, and finance, which allows them to cater to diverse client needs [4] Group 3: Self-developed Models - A growing number of companies are focusing on developing their own models, categorized into two types: unicorns targeting general models and those specializing in vertical markets [5][6] - Companies like xAI and Cohere aim for breakthroughs in foundational models, while others like Midjourney and Stability focus on niche applications [6] Group 4: Differentiated Ecosystem Strategies - The competition in generative AI has shifted from model capabilities to ecosystem building, with OpenAI, Anthropic, and Google each pursuing distinct strategies [8] - OpenAI emphasizes platform attractiveness, Anthropic focuses on safety, and Google leverages its integrated ecosystem for comprehensive solutions [9][10][11][13] Group 5: Developer and Channel Strategies - OpenAI provides a general development platform with a plugin ecosystem, incentivizing developers to innovate [14] - Anthropic emphasizes a B2B integration strategy centered on safety, using protocols to connect its models with external systems [15] - Google offers a full-stack AI development environment, integrating its models deeply into its product ecosystem [16][19] Group 6: Pricing Strategies - OpenAI employs an API billing model with subscription options, gradually lowering prices to expand its user base [23] - Anthropic uses a flexible pricing strategy, focusing on value for high-value clients while maintaining competitive pricing [24] - Google combines low pricing with cross-subsidization strategies to rapidly expand its market share [25] Conclusion - The ecosystem barriers and user stickiness in the AI industry are still in the early stages of formation, with significant potential for change as technology evolves [26]