In late November 2025, a seemingly minor technical detail caught the attention of the tech ecosystem. Engineer Tibor Blaho analyzed a recent version of the ChatGPT Android application (build 1.2025.329) and uncovered multiple explicit references to advertising-related features: ads feature, search ad, search ads carousel.

Such elements do not appear accidentally in production code. They clearly indicate a strategic direction: OpenAI is preparing to integrate advertising directly into the ChatGPT user experience.

From that point on, the real question is no longer whether ChatGPT will seek deeper monetization, but how far this transformation will go—and how fast.


A business model burning cash at unprecedented scale

ChatGPT is not a traditional digital product. Every single query requires:

  • intensive computation,
  • specialized GPUs,
  • high memory consumption,
  • globally distributed infrastructure,
  • continuous R&D to remain competitive.
At the scale of hundreds of millions of users, operational costs quickly reach staggering levels. Estimates consistently point to several billion dollars per year spent solely on inference and infrastructure.

While revenues are growing rapidly (subscriptions, API usage, enterprise contracts), costs are increasing just as fast—if not faster. As a result, the current model struggles to reach sustainable profitability.


Growing concerns about the profitability of generative AI

This structural imbalance fuels growing concern among investors and industry observers. Generative AI is already transforming workflows and markets, yet its economic foundations remain fragile.

Comparisons with the early-2000s internet bubble are becoming increasingly common:

  • massive adoption,
  • soaring valuations,
  • strong technological promises,
  • but uncertain long-term profitability.
OpenAI finds itself in a delicate position: a global symbol of generative AI, yet financially exposed if monetization fails to keep pace with costs.


Advertising: an almost unavoidable step

Against this backdrop, advertising integration appears almost inevitable. The emerging model is familiar:

  • free accounts with sponsored results,
  • paid subscriptions without ads,
  • native advertising formats embedded in search or responses.
Advertising can help subsidize free users, but it cannot fully offset infrastructure costs at this scale. It may reduce losses—but it is unlikely to solve the equation on its own.

Advertising is a necessary crutch, not a silver bullet.


Integrated payments and conversational commerce: still marginal

OpenAI is also experimenting with transactional use cases:

  • product recommendations,
  • conversational shopping flows,
  • integrations with third-party services.
In theory, turning an assistant into a transactional interface makes sense. In practice, these use cases remain limited. Key components are still missing:

  • a structured partner ecosystem,
  • a mature commission model,
  • meaningful transaction volume.
These elements are promising building blocks—but not yet a solid foundation.


AGI delays and intensifying competition

OpenAI’s long-term vision has been closely tied to AGI. As of late 2025, several realities stand out:

  • AGI has not been achieved,
  • timelines remain uncertain,
  • communication has shifted toward more concrete, short-term use cases.
Meanwhile, competition has intensified. Specialized, more cost-efficient models are emerging rapidly, gradually eroding ChatGPT’s early advantage in both perception and performance.


Search, advertising, commerce: the most coherent trajectory

In this context, the shift toward a search / advertising / commerce triad looks less like a strategic option and more like an economic necessity.

At Leadkong, we believe this evolution reflects a broader trend: intelligent assistants cannot remain purely conversational tools. To be sustainable, they must become action-oriented systems—capable not only of answering questions, but also of guiding decisions, qualifying intent, and triggering concrete outcomes.

For ChatGPT, this implies a deep transformation:

  • becoming a central search interface,
  • embedding contextual advertising,
  • connecting search to real transactional flows,
  • building a monetized ecosystem of agents and plugins,
  • reserving a premium, ad-free experience for paid users.
The model increasingly resembles a global platform rather than a standalone software product.


Inference costs: the non-negotiable constraint

Even in an optimistic platform scenario, one constraint remains dominant: inference cost.

Long-term profitability will depend on several technical breakthroughs happening in parallel:

  • significant reductions in GPU costs,
  • more compact and specialized model architectures,
  • smarter caching and routing strategies,
  • fine-grained trade-offs between service quality and actual compute cost.
Without a structural drop in inference costs, financial pressure will remain intense.


A forced transformation with an uncertain outcome

The transformation of ChatGPT’s business model is not a marketing repositioning. It is a direct response to a fundamental economic reality: large-scale generative AI is not inherently profitable.

If OpenAI succeeds in:

  • building a comprehensive ecosystem,
  • capturing value across search, advertising, transactions, and plugins,
  • significantly reducing inference costs,
then ChatGPT could evolve into a sustainable economic pillar.

If not, the risk of a sharp correction remains very real.

The transformation is already underway.
The only true unknown is whether it will happen in time.