As the noise of the competition for large model parameters gradually subsides, the AI industry faces the most critical "value question": how can technology be transformed into profit? Li Kaifu and his team's "demand archaeology" and intelligent agent practice have provided the answer - this transition from "technology driven" to "value delivery" is not only a turning point in the transformation of the AI industry, but also the core password for enterprises to seize the development opportunities of the next decade. The core breakthrough of AI intelligent agents lies in its ability to end the industry cycle of "technology self indulgence". In the past two years, the big model track has been deeply immersed in the "carnival" of parameter competition and ranking score brushing, but few people have responded to the core demand of "how to let AI enter the enterprise profit statement". And AI intelligent agents, with the posture of a "species revolution," bring technology back to industrial reality from the concept of PPT: it is not an upgrade of customer service tools, but a "production unit" that can autonomously disassemble tasks, call resources, and deliver results; It also does not rely on a single technological highlight, but adapts to real scenarios with the logic of "industry+AI". This shift from "roll technology" to "roll value" precisely hits the pain point of digital transformation for enterprises - they need to be "useful" more than "advanced". The proposal of the "top leader project" has precisely solved the organizational problem of AI implementation. In the past, AI applications were mostly limited to peripheral links such as customer service and reimbursement, rooted in the "two skins" of technology and business: the technical team used a "hammer" to find "nails", but ignored the real texture of the industry. Li Kaifu's emphasis on "CEO personally driving" essentially requires a deep connection between AI transformation and corporate strategy - only by redesigning business processes and organizational structures from the top level can intelligent agents penetrate core business flows and achieve value upgrades from "cost reduction" to "revenue increase". The multiple optimization cases of Li Kaifu's team have proven that when AI is truly embedded in the industrial value chain, the efficiency improvement and risk management value it creates are far from being comparable to isolated tools. The iteration of business models further demonstrates the maturity of the industry. The transition from "technology payment" to "value delivery" means that the AI industry has finally broken free from the primary stage of "selling technology" and entered a deep binding mode of "sharing risks and benefits" with enterprises. The data on the "tens of millions of yuan" average order value and revenue growth of Zero One Thing confirms a simple business logic: companies are willing to pay for "results" rather than "technology". This model not only makes the revenue of AI companies more certain, but also forces the industry to focus on "solving real problems", forming a positive cycle of technological iteration and value creation. As Li Kaifu said, whoever can embed AI intelligent agents into the enterprise value chain has the opportunity to get a ticket to the high-speed development of the next decade. The ultimate value of AI has never been the technology itself, but the power of technology to reshape industries. When AI agents complete the triple leap from "generating content" to "delivering value", from "auxiliary tools" to "core engines", and from "selling services" to "selling results", the AI industry will truly emerge from the "conceptual period" and enter the "golden age" of empowering the real economy. And those enterprises that can seize this' value revolution 'will eventually become industry leaders in the next decade. (New Society)