2026 To B 生存实录：消失的群体和变异的组织

Core Insights - The To B market in 2026 is exhibiting a pronounced "dumbbell" structure, with tech giants on one end and small, agile startups on the other, leaving mid-sized SaaS companies in a precarious position [1] - The traditional growth equation of "adding people equals adding revenue" is shifting to an exponential model driven by AI leverage, fundamentally altering competitive dynamics [1] Group 1: Entrepreneurial Shift - A group of "rebels" from established tech companies is dismantling the old systems, leveraging their deep understanding of traditional models to create innovative solutions [2] - Entrepreneurs like Lu Yang (PureBlue AI) and Zhai Xingji (Yuhuo Technology) are driven by a profound recognition of pain points within the old frameworks, leading to their technical breakthroughs [3][4] Group 2: Generational Divide - The previous generation of SaaS entrepreneurs focused on building systems and standardizing complex processes, relying on large sales teams for growth [7] - In contrast, the new generation of AI entrepreneurs aims to penetrate processes directly with technology, focusing on measurable business outcomes rather than merely optimizing tool usage [8] Group 3: Organizational Evolution - New AI startups are characterized by minimal organizational structures and elite talent, moving away from traditional growth paths [9] - The absence of large sales teams is notable, with companies like PureBlue AI relying on the inherent value of their products to attract clients [10] Group 4: Pricing and Delivery Models - The pricing logic has shifted from user-based fees to value-based payments, where clients pay for the labor cost saved or business increment generated by AI [15][16] - New AI services must deliver clear, quantifiable business increments, redefining the relationship between clients and service providers [17][18] Group 5: Trust as a Core Asset - New AI entrepreneurs prioritize long-term brand value over short-term profits, rejecting projects that compromise their strategic focus [21][22] - Maintaining ethical standards in AI applications is seen as essential for long-term survival, with a focus on genuine value creation and trust [23][24] Group 6: Conclusion - The stories of these AI entrepreneurs reflect a return to fundamental business logic, emphasizing efficiency, measurable results, and trust accumulation [27]