Artificial intelligence (AI) is becoming a much more accessible resource, driven by cost reductions, more efficient models, and greater availability of computing power. While this trend benefits users and corporations, it represents a significant challenge to the financial sustainability of industry leaders like OpenAI and Anthropic.
AI Heading Towards Commodity Status
An analysis published by The Wall Street Journal points out that AI is moving from being a scarce asset toward becoming a commodity. This shift could diminish the competitive advantage of companies currently leading the development of the most sophisticated models.
Factors Driving AI Democratization
One of the main reasons for this transformation is the drastic drop in costs for AI capable of performing most daily tasks. This is facilitated by the emergence of lighter models, operable both in the cloud and directly on devices, including solutions from Google, Apple, and Chinese AI companies.
Additionally, China has reinforced its strategy. In a speech delivered in Shanghai on Thursday (16), Chinese President Xi Jinping advocated for maintaining the release of 'open-weights' AI models, allowing for free modification and use. This tactic aims to counterbalance US hegemony in the sector. Chinese models, such as GLM 5.2 and Kimi K3, are narrowing the gap with advanced systems developed by American companies.
The Rise of Competition
Meta has also made considerable advances in developing programming-focused models, demonstrating the ability to compete directly with OpenAI and Anthropic in the lucrative code generation niche. It is expected that the current computational capacity bottleneck will be mitigated by activating new data centers and developing more efficient methods for running AI models. In certain applications, the supply of tokens, the basic unit of consumption, already matches demand.
Impact on the Market and Leaders
These advancements are seen as positive for consumers and businesses. About a year ago, Sam Altman, CEO of OpenAI, expressed a desire to make artificial intelligence so cheap that it would be difficult to measure. AI has the potential to boost productivity across various professions and reduce digital friction, rather than simply replacing workers.
However, the scenario raises uncertainties about the financial future of OpenAI and Anthropic, both candidates for initial public offerings. Since they rely on maintaining technological superiority over established giants, they may suffer if AI is treated as a general-purpose technology comparable to electricity or the automobile.
Decline in OpenAI's Share
Data from Sensor Tower, cited in the analysis, indicates that in March, ChatGPT accounted for less than 50% of the global consumer user share, considering web and mobile device access. This decrease was mainly attributed to competition from Google Gemini and Anthropic's Claude.
In the corporate sphere, Chinese models have also begun competing with major American systems, showing similar performance in some metrics but at substantially lower costs. The OpenRouter ranking shows that the five most used enterprise models are currently Chinese, and approximately 45% of the tokens monitored by the platform are consumed by these models.
Intensified Battle for Free Models
The analysis also highlights the launch of an open-weights model by Thinking Machines Lab, a company led by Mira Murati, former CTO of OpenAI. This system aims to balance performance and operational cost, summarizing the change with the analogy: 'Who needs an AI Ferrari to go to work when an AI Honda Civic is right there?'
Faced with growing competition, OpenAI and Anthropic are increasing their investments in engineers and data center access, even if it affects profitability. Both companies are committing hundreds of billions of dollars to preserve technological leadership. Simultaneously, enterprise clients are scrutinizing the necessary investment in AI more rigorously and which premium models justify their costs.
Dissemination of AI Knowledge
Another accelerating factor in the transformation of AI into a commodity is the widespread dissemination of knowledge on how to build advanced models. Although companies continue to protect their trade secrets—such as the lawsuit filed by Apple against OpenAI for alleged intellectual property theft—researchers continuously publish scientific studies detailing new advancements. Chinese labs and companies, such as Thinking Machines Lab, also regularly make open-source models available with complete documentation of their creation.
Distillation Technique Sparks Controversy
The text also addresses the technique known as 'distillation,' which involves training one model using another as a reference. OpenAI and Anthropic accuse Chinese companies of using this method to create competing systems based on private information. However, the industry itself uses the technique legitimately; large models are often employed to generate smaller and more agile versions.
The new model supporting Apple's updated Siri, for example, was distilled from Google models, according to an agreement between the parties. In a recent essay, Microsoft CEO Satya Nadella described it as 'ironic' that companies training models with internet data and customer information try to block third-party use of distillation. He argued: 'If learning flows in only one direction, economic value converges to the owners of the learning infrastructure, not to the creators of the knowledge itself.'
Search for New Competitive Advantages
Previously, the main competitive advantage of OpenAI and Anthropic lay in offering models notably superior to competitors. With the popularization of systems considered 'good enough'—and in some cases, highly advanced—available to both iPhone users and large corporations, these companies need to find new differentiators.
While Google relies on its search engine, Meta possesses its social media base, and Microsoft and Amazon dominate enterprise infrastructure, while Apple controls a vast ecosystem of devices.
Energy as a Future Differentiator
Eric Zhao, a professor at the University of Oxford and co-author of a mentioned study, suggests that access to electrical energy may become the primary future competitive advantage for AI companies. As electricity supply becomes constrained and communities oppose the construction of new data centers, energy efficiency will be crucial. He stated that 'frontier labs will need to compete for intelligence per watt.'
Revenue Diversification
OpenAI is expanding its revenue streams, counting over three million corporate clients and developing proprietary hardware to create a direct link with consumers. Meanwhile, Anthropic recently achieved its first profitable quarter and filed an application for a public offering in the Northern Hemisphere autumn (September-December). If the IPO occurs, the company could raise funds to acquire new customers, develop other income sources, or increase data center rentals.
Questions Regarding AI Growth
The analysis concludes that the AI market may be robust enough to sustain multiple winning companies, potentially allowing OpenAI or Anthropic to become tech giants. However, the text cites an assessment by the Bank for International Settlements (BIS), according to which the volume of investments in AI already exceeds any peaceful economic expansion cycle, including railway construction and the late 1990s internet bubble.
In this context, critics are growing who doubt whether companies will be able to justify current and future investments. Without a lasting competitive advantage, the companies leading the AI boom could face a considerable downturn in the future.
