Professor Zeng Ming: AI Era Demands 'Intelligent Compounding' for Business Growth
At the 2026 World Artificial Intelligence Conference (WAIC) in Shanghai, Professor Zeng Ming, in an exclusive interview with 36Kr, discussed how businesses must adapt to the AI era. He emphasized that the focus in AI development has shifted from model capabilities to practical value creation, with a key challenge being the integration of AI into core business processes to generate tangible results. Professor Zeng argued that AI represents a fundamental technological revolution, akin to the industrial revolution, necessitating a redefinition of business growth, organizational structures, and commercial logic. He introduced the concept of 'intelligent compounding,' where AI systems continuously learn and improve through real-world tasks and feedback loops, leading to sustained growth.
He noted that AI's ability to understand users is evolving from 'thousands of people, thousands of faces' to 'one person, thousands of faces.' Unlike traditional recommendation systems relying on historical data and labels, AI can engage in continuous interaction to achieve deeper, dynamic personalization. For businesses, true AI value lies beyond demonstration projects; AI must be capable of independently completing tasks and taking responsibility for outcomes. The critical competitive advantage in the AI era will be building AI-native businesses that embed AI into workflows, creating self-reinforcing value cycles.
Professor Zeng acknowledged that many companies are experiencing a lag in AI investment returns, which he attributes to the early stage of both AI technology and its adoption. He advised businesses to identify specific business segments that AI can genuinely take over, rather than focusing on superficial applications or grand strategies. The most crucial step for AI to generate 'intelligent compounding' is to achieve an 'independent on-the-job' capability, meaning AI can complete tasks end-to-end and take responsibility for results, thereby enabling continuous learning and improvement.
The discourse surrounding AI's integration into business processes highlights a critical inflection point. As AI capabilities mature beyond mere efficiency gains, the challenge shifts to systemic integration and value realization. Professor Zeng's concept of 'intelligent compounding' suggests that the true competitive advantage will stem not from possessing advanced AI models, but from architecting business systems that facilitate AI's continuous learning and adaptation through real-world operational feedback. This necessitates a strategic reorientation, moving from AI as a tool to AI as an integral component of business operations, capable of independent task execution and accountability. The long-term implication is a potential bifurcation of businesses into those that successfully embed AI for self-reinforcing growth and those that remain reliant on traditional operational paradigms, facing diminishing returns in an increasingly AI-driven market.
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