Practitioners Stay, Storytellers Leave | Let Collaboration Happen Now!
The AI industry is transitioning from technical parameter competition to addressing industrial practical needs, reshaping the entire value chain and business model.
Practitioners Stay, Storytellers Leave | Let Collaboration Happen Now!
The AI industry is undergoing a quiet revolution. Over the past two years, the spotlight has primarily focused on the technical side—parameters, computing power, and leaderboard rankings. But today, the winds are shifting: decision-making power is moving toward industrial players, those companies with real needs, real scenarios, and real business pressures, who are beginning to call the shots.
From Showcasing Technology to Practical Application: Deep Restructuring of AI Value System
In 2026, the AI industry is in a period of value system reconstruction. This transformation isn't a technological breakthrough but a shift in thinking. Like an experienced director shifting focus from special effects to the script, the AI industry is moving from "What can I do?" to "What should I do?"
The most pressing questions for the industry have become concrete and urgent: Where results must be delivered, can AI really be relied upon? This isn't theoretical discussion in a lab but a practical issue关乎企业生存和发展的实际问题 (related to corporate survival and development).
Shifting Decision-Making Power: From Tech Providers to Industrial Players
In the past, the AI industry's rules were mainly set by technology providers. They defined what was "advanced" or "leading," while industrial players passively accepted these standards. This situation is now being disrupted.
Companies with real needs, real scenarios, and real business pressures are beginning to assert their power to define. They are no longer satisfied with "what AI can do" demonstrations but are questioning "what AI should do" in terms of practical value. This shift marks the transformation of the AI industry from a "seller's market" to a "buyer's market."
Scenarios Reign Supreme: The Key to AI Implementation
At the 2026 AI Partner Conference, the theme "Taking AI to the Frontlines" revealed the industry's latest trends. AI is no longer just a laboratory darling but is moving to the front lines to solve practical problems.
Traditional industries such as healthcare, finance, manufacturing, and logistics are becoming the main battlegrounds for AI applications. Baidu Health has provided its own answer over six years: moving from point intelligence to holistic collaboration, from technology empowerment to value creation. AI isn't about showing off but making every link more professional.
From Data to Value: The Evolution of AI Business Models
The AI industry's business models are also undergoing profound changes. From the past "technology licensing" model to today's "value co-creation" model, AI companies are seeking win-win partnerships with industrial players.
The seven-year partnership between Jinzhiwei and Galaxy Futures, evolving from a 100,000-level RPA project to a million-level intelligent process reconstruction, proves one thing: the value of enterprise AI lies not in answering questions but in getting things done. Today, digital employees have been implemented in over 50 scenarios at Galaxy Futures, executing more than 3,000 business processes daily with 99.97% accuracy.
Challenges and Opportunities Coexist
This transformation is not without challenges. AI implementation faces practical issues such as "top heat, bottom cold" (enthusiasm at leadership level but resistance at implementation level), over-pursuit of full intelligence, and data governance shortcomings. As one industry expert put it: "Don't wait to align everyone's understanding before starting, nor try to achieve everything at once. Use small processes to deliver results, and use results to build consensus—that's the most stable path for AI transformation."
The Future is Here: Deep Integration of AI and Industry
As AI and industries integrate more deeply, we will see more inspiring cases. Shenmou, through extreme low-power chip design, has freed cameras from wire constraints, opening up a future with trillions of intelligent vision terminals. Aidipu, with 22 years of experience, tells us: the first battle in the AI era is the data governance battle.
The future of the AI industry doesn't lie in how high its parameters are or how strong its computing power is, but in how many practical problems it solves and how much real value it creates. As one industry leader said: "Practitioners stay, storytellers leave." This is not just an industry wake-up call but a redefinition of AI's value.
In this value reconstruction of the AI industry, those companies that can truly understand industrial needs and solve practical problems will win the future. Those immersed in technical parameters while ignoring practical value will be mercilessly eliminated by the market.