Galaxy Securities: Tokens Become the Value Anchor of the Intelligent Era; It Is Recommended to Position Around Core AI Industry Beneficiary Segments

Background

The report frames tokens as the value anchor of the AI era. That is a meaningful claim because it identifies a common economic denominator for AI activity: tokens are not just a technical unit in model interaction, but a settlement unit for the industry. In other words, token consumption translates directly into measurable demand and monetization.

From the demand side, the report highlights rapid growth in global token usage. This surge is treated as evidence that AI is progressing beyond internal model improvement and into broader commercial application. The implication is that rising token calls are not merely a sign of technical experimentation, but of real-world workloads entering production environments.

Key Points

Tokens as AI’s economic infrastructure

The central insight is that tokens connect technical capability with commercial value. By calling them a “value anchor,” the report implies that they provide a standardized way to price, settle, and scale AI services across use cases. This matters because industries typically commercialize more effectively when there is a clear transactional unit.

That framing also suggests a shift in how AI should be evaluated:

• not only by model parameters or benchmark scores,
• but by token demand, token consumption growth, and token-driven monetization.

Commercialization is replacing pure model iteration

The report explicitly says growing token usage is pushing the AI industry from model iteration toward commercialization. This is a notable transition. Model iteration emphasizes capability-building; commercialization emphasizes deployment, integration, and recurring usage.

The deeper implication is that value creation is moving toward:

• productization,
• user adoption,
• workflow integration,
• and scalable payment models.

So the report is not simply optimistic about AI technology; it is optimistic about AI becoming an operational business system.

Media faces bottom-up reconstruction

One of the strongest claims is that AI may reconstruct the media industry from the bottom layer upward. The report specifies three dimensions of change:

• production factors,
• industrial logic,
• business models.

This suggests a structural rather than incremental transformation.

1. Production factors: AI changes what inputs matter in content creation. Human labor remains important, but AIGC tools alter the cost structure and speed of production.
2. Industrial logic: Traditional bottlenecks in content production and distribution may weaken if AI tools can generate content at scale.
3. Business models: If content becomes easier and cheaper to produce, monetization, differentiation, and competitive advantage may shift away from pure production capacity.

AIGC drives content toward abundant supply

The report argues that the token economy empowers traditional content production industries and, with AIGC tools, pushes them toward “infinite supply.” This is the most transformative economic claim in the piece.

The significance of that idea lies in the contrast with traditional media economics:

• content supply used to be constrained by labor, time, and production cost;
• AI reduces those constraints by automating and accelerating generation;
• token-based AI usage becomes the mechanism through which this new supply is created and scaled.

If supply approaches abundance, the industry could enter a period of prosperity, as the report suggests. But that prosperity is tied to AI-enabled productivity gains, not simply to existing media models expanding unchanged.

Investment Implications

The report recommends focusing on core beneficiaries across the AI industry chain, which reflects a broad but targeted view of where token-driven commercialization may translate into equity value.

Key areas include:

• Major internet platforms increasing comprehensive AI deployment
  These companies are positioned to benefit because they can integrate AI across ecosystems, products, and user bases.

• Vendors with leading AI video tool product strength
  This indicates particular confidence in video as a high-value application area where product capability can create competitive advantage.

• Leading companies in vertical segments benefiting from AI applications
  The report recognizes that AI value will not be captured only by general platforms; specialized leaders in application-heavy niches may also see strong gains.

• Large-model companies advancing through ongoing technological iteration
  Even though the industry is moving toward commercialization, foundational model progress remains important. The report therefore does not treat commercialization and technical advancement as opposites, but as mutually reinforcing.

Significance

The article’s deeper message is that the AI economy is becoming measurable, billable, and industrialized through tokens. That matters because commercialization requires a shared unit of value, and tokens now play that role.

For media and content industries, the report sees AI not as a marginal efficiency tool but as a force that changes the economics of creation itself. Once AIGC lowers production costs and expands output capacity, competition may increasingly revolve around product strength, application depth, and the ability to convert token consumption into scalable businesses.

The investment logic follows this structure closely: back firms that either control large AI-enabled ecosystems, lead in high-impact tools like AI video, dominate AI application niches, or continue improving the large models that generate token demand in the first place.

The core takeaway is not just that AI is growing, but that token growth is the clearest sign AI is becoming a functioning commercial economy.