AI的瓶颈不是算力，而是…

Core Insights - The discussion around AI has established a narrative framework where computing power determines limits, models dictate capabilities, and data defines intelligence levels. However, the real challenge lies in organizational adaptation to AI, which is often linear compared to the exponential growth of AI capabilities [1] Group 1: AI Implementation and Organizational Change - A seemingly reasonable figure, such as 30% of code being generated by AI, may mask a more conservative reality. If the potential was close to 100%, then 30% indicates organizational restraint rather than efficiency issues [2] - A practical experiment revealed that when organizational boundaries were removed, nearly all code could be generated by AI, highlighting the importance of organizational willingness to change [2][12] - Traditional organizational structures, rooted in the industrial era, create high collaboration costs that can hinder AI's potential [3][4] Group 2: New Collaborative Models - The shift towards AI-native workflows resembles 3D printing rather than traditional bricklaying, allowing for more integrated and efficient collaboration [4] - As AI raises the baseline for delivery standards, the value of human input shifts from execution to defining what excellence looks like and taking responsibility for it [5][12] Group 3: Organizational Transformation Initiatives - The company transformed management meetings into "AI promotion meetings," focusing on how AI can create value rather than merely reviewing performance metrics [6] - A training and certification program named "ABC+" was introduced to empower non-technical staff to utilize AI tools, identifying potential future leaders within the organization [7][8] - A hackathon for non-technical employees resulted in a project that streamlined communication between sales and development, reducing organizational friction and enhancing efficiency [9][10] Group 4: Leadership and Organizational Structure - As AI capabilities are integrated into workflows, the minimum deliverable unit within the organization shrinks, leading to a reduced need for coordination and a shift in the role of middle management [10][11] - AI serves as a consensus tool for driving long-term organizational change, making it a compelling reason for CEOs to advocate for transformation [11] Group 5: The Bottleneck of AI Adoption - The true bottleneck for AI is not technological but rather the readiness of people and organizations to embrace change and redesign themselves [12][13]