① 2026 may become the “year of billion-intelligent agents,” when the focus of AI competition will completely shift from “parameter comparison” to “industrial implementation.” ② The explosion in the AI application field is the result of industry inflection points, capital catalysis, market sentiment, and the resonance of capital flows. The industry’s focus is shifting from an “arms race” of underlying models to commercial implementation, indicating that an industry tipping point has arrived.
STAR Market Daily News, January 18 (Reporter Huang Xinqi) Competition in the global large-scale model application market continues to intensify.
Not long ago, tech giant Meta completed its acquisition of Manas for tens of billions of dollars, making it the third largest acquisition in Meta’s history. It also reveals a fundamental shift in how capital markets value AI.
At about the same time, domestic large model manufacturers Chipu Huazhang and Minimax were listed on the Hong Kong Stock Exchange and received high praise, further confirming the market trend. These events collectively point to a trend. The AI industry’s focus is rapidly shifting from a “parameter race” of underlying models to application layers that can solve real-world problems and create commercial value. The “value discovery” process of large-scale AI models is being comprehensively accelerated.
Industry insiders have pointed out that 2026 could become the “year of 100 million intelligent agents,” and the core of AI competition could completely shift from “parameter comparison” to “industrial implementation.” There is a clear logic of industrial evolution behind this decision. Until now, much of the investment and attention has been focused on building algorithms and computing infrastructure for large-scale models, often facing the dilemma of “no critical acclaim without box office success.” Now, as large-scale model technology gradually matures, the main conflict in industrial development has shifted to how to translate technical capabilities into a scalable commercial closed loop.
In its 2026 outlook, Morgan Stanley made it clear that the market’s criteria for evaluating AI has completely shifted from expectations for pure technological advancement to a rigorous assessment of return on invested capital (ROIC). The only measure of company value is whether a company can achieve measurable revenue growth, efficiency gains, and profit generation through AI. This means that the AI industry is moving from the “wild growth” stage of technological concepts to the “rational maturity” stage of commercial value realization, and 2026 will undoubtedly be a critical watershed in this “value reassessment.”
All signs point to the central driver of this revaluation being in capital markets, which are beginning to systematically favor AI applications that can integrate deeply into industries and create substantial economic value.
Guojin Securities pointed out that the explosive growth in the AI application field is the result of industry inflection points, capital catalysis, market sentiment, and capital flow resonance. The industry’s focus is shifting from an “arms race” of basic models to commercial implementation, indicating that an industry tipping point has arrived. In what follows, we will focus on two main themes:
First is the battle for the C-end super entry point and ecological dividend. Domestic internet giants are striving to capture entry points for AI users. Pay attention to internet platforms and their ecosystem partners that are deploying AI, especially AI marketing service providers.
The second is breakthroughs in vertical applications and value discovery at the B-end. Vertical software companies with industry expertise, deep integration of AI into workflows, and real revenue generation will encounter structural opportunities.
Take, for example, the DreamMaker platform released by Fubo Group, which is aimed squarely at the video creation space. Its value lies not in its use of cutting-edge models, but in its innovative integration of AI video generation tools with industry-leading copyright protection and content monetization solutions. The platform directly addresses the core challenges faced by independent creators when it comes to content compliance and commercialization, building a unique commercial moat within the vertical scenario by providing end-to-end services from ideation to revenue generation.
Successful AI applications no longer represent individual technological advancements, but comprehensive solutions that connect data, business workflows, and monetization. Whether it’s Manus achieving nearly $100 million in annual revenue through a subscription model, demonstrating the willingness of users to pay for AI agents, or the “AI + Manufacturing” initiative where companies like Sany Renewable Energy are significantly increasing production efficiency through AI platforms, these examples prove that only by forming a closed loop of “technology iteration – application implementation – profit reinvestment” can companies earn recognition in the new evaluation framework.
Indeed, Meta’s acquisition of Manus, coupled with capital markets’ enthusiasm for the concept of AI applications, jointly initiated a reassessment of the value of large-scale models. Industry players noted that by 2026, as investment logic firmly shifts to applications and revenue, AI companies that can deeply understand the industry and build robust commercial closed loops will stand out in this profound “value discovery” and steadily move the industry from the “cloud” of technology to the “ground” of economic reality.
