3 6 Ke·2025-06-20 10:29Core Insights - The deployment of AI in enterprises has transitioned from experimental projects to strategic actions, with budgets becoming normalized and applications being systematically implemented [2][51] - A16z's report highlights the shift in focus from "whether to try AI" to "how to scale AI deployment" [4][5] Group 1: Budget - AI budgets have significantly exceeded expectations, with an average increase of approximately 75% anticipated for the coming year [10][11] - The proportion of AI spending from innovation budgets has decreased from 25% to 7%, indicating that AI is now considered a core part of IT and business budgets [13] Group 2: Model Selection - The use of multiple models has become mainstream, with 37% of enterprises using five or more models, up from 29% the previous year [15][17] - OpenAI, Google, and Anthropic have emerged as the leading players in the market, with OpenAI maintaining a significant market share [17][18] Group 3: Procurement - The procurement process for AI models is becoming more standardized, with cost sensitivity increasing as a key consideration [27][29] - Trust between enterprises and model vendors has improved, leading to a shift towards direct partnerships with model providers [29][31] Group 4: Application - Enterprises are increasingly moving from self-developed AI solutions to purchasing third-party applications, with over 90% of CIOs testing third-party applications in customer support scenarios [35][42] - Software development has emerged as a leading application area for AI, with significant adoption rates reported [42][45]