The artificial intelligence industry is entering a watershed moment that could redefine its business model. After years of rapid growth, heavy investment, and relatively cheap access to advanced AI tools, companies like OpenAI and Anthropic are now facing a harsh reality: They need to start making money or risk the collapse of their own model.
As The Verge reports, the year 2026 represents a kind of “monetization cliff” moment for the AI industry, where the gap between costs and revenues can no longer be ignored.
AI giants under pressure
The main actors of this story are precisely the companies that led the AI revolution. OpenAI and Anthropic built businesses around large language models and API infrastructure, but at the same time they spent billions of dollars developing and, more importantly, running those models in real time.
The problem is that the use of AI, the so-called inference, became more expensive than his training.
In other words, every time a user asks a question or starts an AI agent, the company spends money. And as AI is used more and more, costs rise exponentially.
The explosion of the token economy
At the center of this problem is the so-called token economy – the way in which the use of AI models is measured and charged.
Modern AI systems, especially agents, spend huge amounts of tokens to complete tasks. However, these processes are often not optimized, which means that resources are spent inefficiently, while revenues do not keep pace.
To achieve a minimal return on huge infrastructure investments, companies would need to generate trillions of dollars in revenue in the coming years, a figure that clearly shows the scale of the challenge.
2026 as a turning point
This pressure comes at a time when potential IPOs (Initial Public Offerings) of the largest AI companies are expected. Investors are no longer satisfied with user growth or technological advances and are now looking for profitability.
It changes the behavior of companies in real time. We are seeing the elimination or limitation of certain features, the transition from subscriptions to “pay-as-you-go” models, and the reduction of the availability of advanced tools at no additional charge.
These changes are not cosmetic, but are a direct consequence of economic pressure.
The end of “free AI”
One of the clearest signals of change is the gradual abolition of free or cheap options.
Anthropic has already begun restricting access to certain tools and moving users to more expensive billing models, while OpenAI is experimenting with new revenue streams, including enterprise packages and additional services.
This marks the end of the first phase of the AI industry, which was characterized by availability and experimentation. The next phase will be much more focused on monetization and efficiency.
Industry between growth and sustainability
What makes this situation particularly interesting is the contradiction at the very heart of the AI industry. On the one hand, demand has never been higher. AI tools are becoming essential for programming, business, education and everyday work. On the other hand, the economic model that supports them is still not stable.
Estimates show that computing costs could reach hundreds of billions of dollars a year, meaning that even the most successful companies can operate at huge losses if they don’t find a sustainable model.
Who will win
At this point, it is not clear whether the market will support more big AI players or consolidate around a few dominant platforms. There is a real possibility that only the companies with the greatest resources, infrastructure and access to capital will manage to survive in the long term.
At the same time, open models and local solutions could become an alternative for a part of the market that cannot or does not want to pay for increasingly expensive AI services.
The time when advanced models were available to almost everyone at a low price is apparently coming to an end, writes TheVerge.