「一人公司」不强求，「Copilots 」更能填平 AI 产业落地的「Massive Delta」？

Group 1 - The core viewpoint of the article emphasizes that the explosion of general AI models has ignited a frenzy of investment in AI, while the opportunities in Vertical AI arise from the ability to bridge the gap between general capabilities and industry-specific applications, suggesting that the next generation of winners may not solely rely on "agent employees" but also on auxiliary models that drive process solutions, integration, and value delivery [1] Group 2 - Recent data indicates a significant shift in global venture capital towards the AI sector, with a projected investment of $110 billion in AI for 2024, marking a 62% year-on-year increase, while overall tech sector investments have declined by 12% [5] - By August 15, 2024, AI-related companies had raised a total of $118 billion, with eight companies alone securing $73 billion, accounting for 62% of the total AI funding [5] - Vertical AI companies are showing a growing advantage in transaction volume, with $17.4 billion raised across 784 deals in the U.S. and Canada, representing 57% of related transactions, although only 36% of the total funding has flowed into Vertical AI, indicating selective investment by venture capitalists [5][6] Group 3 - Vertical AI is attracting attention due to its potential for high commercial returns, with McKinsey estimating that GenAI could add $2.6 trillion to $4.4 trillion annually to the global economy, particularly benefiting sectors like banking, high-tech, and life sciences [5] - Emerging Vertical AI companies are demonstrating commercial metrics comparable to traditional SaaS firms, with annual contract values (ACV) reaching 80% of traditional SaaS levels and a year-on-year growth rate of 400%, while maintaining approximately 65% gross margins [5] Group 4 - The market for Vertical AI Agents is projected to be ten times larger than traditional vertical SaaS, as it not only replaces existing software but also integrates software with human operations, eliminating repetitive labor [7] - The transition from general models to specific industry applications faces significant challenges, termed the "Massive Delta," which includes the complexity of industry workflows and the need for close collaboration with domain experts to accurately define and model these processes [7][8] - The application of general models is hindered by data privacy compliance and the need for deep integration with legacy systems, particularly in sectors like healthcare and law, which have stringent data privacy requirements [9][10] Group 5 - To bridge the "Massive Delta," various business models have emerged in the Vertical AI space, categorized into Copilots, Agents, and AI-enabled services, representing different levels of value delivery from auxiliary to replacement [10]