Page 1: 第1页 Welcome. Today, we embark on an intellectual journey to dissect a critical phenomenon in modern business: The Generative AI Divide. This report, a product of rigorous research, will serve as our foundational text. Our objective is to move beyond the popular hype and develop a structured, evidence-based understanding of why the promise of AI is realized by so few, and what separates them from the rest. Let us begin. Page 2: 第2页 Imagine a nation investing billions to construct a magnificent new highway system. Yet, upon completion, it is discovered that 95% of existing roads have no on-ramps to access it, rendering the investment inert for the vast majority. This is the paradox of the GenAI Divide. We see immense capital allocation, but a near-total failure to connect this new capability to the actual operational "roads" of the business. Our inquiry begins here: understanding this profound gap between investment and value. Page 3: 第3页 Like a physician diagnosing an illness, we must first examine the symptoms. We observe two critical signs of stagnation. First, a "pilot-to-production chasm," where promising AI projects perish before they can be implemented—only 5% of custom tools survive. Second, a thriving "shadow economy," where employees, dissatisfied with official tools, use their personal AI subscriptions for work. This demonstrates a clear disconnect between corporate strategy and the practical needs of the workforce. These symptoms point to a deeper, underlying pathology. Page 4: 第4页 We have now arrived at the root cause. Consider a brilliant student who possesses vast knowledge but suffers from complete amnesia. Each day, every lesson must be retaught from the beginning. This is the state of most enterprise GenAI. It can perform a task, but it cannot learn from experience, remember user preferences, or adapt to context. This "learning gap" is the central reason why users trust AI for simple, fleeting tasks but turn to human colleagues for any work that requires continuity and accumulated knowledge. It is the core of the GenAI Divide. Page 5: 第5页 If the learning gap is the chasm, what then is the bridge? Our research reveals clear blueprints for crossing it. The most crucial strategic choice is to "buy" rather than "build." Organizations that partner with specialized vendors see double the success rate of those who attempt to develop AI internally. Successful buyers behave not like software shoppers, but like firms hiring a specialist service; they demand customization and measure success by real-world results. This symbiotic relationship between a discerning buyer and an adaptive builder is the primary mechanism for bridging the GenAI Divide. Page 6: 第6页 Having diagnosed the problem and outlined the current solution, we now turn our gaze to the horizon. The resolution of the learning gap gives rise to "Agentic AI"—systems that remember, learn, and act. The logical endpoint of this evolution is the "Agentic Web." Imagine an ecosystem where these autonomous agents can discover, negotiate, and coordinate with each other across the entire internet. This is not merely an improvement; it is a paradigm shift from today's static, human-mediated workflows to a dynamic, self-optimizing network of intelligent systems. This is the landscape that will be shaped by those who successfully cross the divide today. Page 7: 第7页 We have traversed the GenAI Divide, from the paradox of failed investment to the root cause in the learning gap, and finally to the strategies for success. The conclusion is clear and prescriptive. The path forward requires a fundamental change in approach: a shift from building to buying, from centralized labs to empowered line managers, and from static tools to adaptive systems. The divide is not a permanent feature of the landscape, but a chasm that can be bridged. However, the opportunity to do so is finite. The choices made today will determine which side of this divide organizations will find themselves on in the emerging AI-driven economy.