At a recent salon event held in Beijing, titled "Token Inclusivity: Delivering Visible Value, Reimagining AI Efficiency," insights were shared on the evolving economic model of AI. Lenovo Group Vice President, Chief Strategy Officer for China, and Executive Chairman of the China Technology Management Committee, Abulikemu (Amu), highlighted a critical trend. He noted that enterprise demand for AI tokens is surging rapidly. According to Amu, the cost efficiency and value return of tokens will adhere to three fundamental principles: the Law of Inertia, the Law of Acceleration, and the Law of Singularity. Lenovo aims to foster a virtuous cycle where enterprise investment in tokens leads directly to tangible value returns, thereby making the value delivered by tokens clearly visible.

Amu elaborated on the concept during the discussion, introducing these three laws of token economics and outlining Lenovo's comprehensive strategy to help businesses achieve demonstrable value. He pointed out that while enterprise token demand is exploding, a decrease in the unit cost of a token does not automatically translate to an increase in the value created.

The Three Foundational Principles

The first principle is the Law of Inertia. This law states the inevitability of a continuous decline in the cost per token. Amu attributed this trend to three key drivers: foundational innovations in chips, energy, and models; the integrated optimization of models, computing, and power; and the dynamic scheduling of tokens during operation.

The second is the Law of Acceleration. This principle describes how the value derived per token accelerates with the depth of its application. Amu emphasized the importance of "effective tokens." He argued that AI's value is not solely dependent on the model itself but is equally influenced by three other factors: the integration density of carbon and silicon systems, the depth of harness engineering, and the maturity of AI governance and supporting infrastructure.

The third principle is the Law of Singularity. This law reveals the dynamic tipping point where total token cost and total token value intersect. Amu provided a forward-looking perspective, explaining that as enterprise token consumption increases, the total cost will inevitably rise. Concurrently, the value manifested by AI agents is also increasing and being released. The moment when the curves of total token cost and total token value cross represents the point of massive AI value explosion.

Current Industry Landscape

Amu assessed the current AI industry as exhibiting a distinct "dumbbell-shaped" polarization. On one end, top-tier enterprises with extremely high levels of digitization and AI-native startups are poised to be the first to cross this singularity threshold. On the other end, the vast majority of traditional enterprises in the middle segment, due to weaker digital foundations, are at high risk of falling into a "cost black hole" of computing expenditure before they can realize any "innovation dividend."