The price of artificial intelligence has collapsed to zero in 30 months — a historic record of deflation
The AI market is experiencing an unprecedented phenomenon: the cost of running neural networks has practically dropped to zero in just 30 months. This is the fastest price deflation among all technological cycles in history. For comparison, personal computer prices fell by 90% over 15 years, while language models have gone through the same trajectory in less than three years.
This rapid depreciation is reshaping the entire software economy. Investors valued SaaS businesses based on the assumption that development would remain expensive, but this calculation is collapsing five times faster than during the PC era. Deflation is splitting the market in two: on one hand, it destroys the pricing power of technology creators; on the other, it creates enormous benefits for consumers.
Companies that sell intelligence are losing control over pricing, while companies that use it are receiving a gift. Every business simply needs to figure out which side of the graph it stands on.
Where the trillions are going: USA vs China
Deflation is accelerating amid record investments. U.S. private AI investments reached $285.9 billion in 2025, while in China they amounted to only $12.4 billion. However, the formal 23-fold gap is deceptive. Chinese AI companies have also received about $184 billion through government channels since 2000.
Analysts at Societe Generale also do not believe in the 23-fold gap. In their view, China's actual AI spending is much closer to that of the U.S.—authorities are simply hiding it from conventional calculation methods. U.S. statistics distort the picture for another reason: the impressive $285.9 billion does not fuel the entire competitive industry but instead accumulates with a few companies. The number of mega-rounds from $1 billion has jumped from 15 to 28. OpenAI's $40 billion round is the most striking example, while Google has spent over $150 billion on AI infrastructure.
My expert conclusion: The U.S. and China are pouring hundreds of billions into AI, but the technology itself is becoming cheaper so quickly that the beneficiaries are not the creators but the users. Money is piling up with a few model developers, while cheap intelligence strengthens the rest of the economy—this is the main paradox of the current cycle. For the crypto industry, this is a signal: projects built on expensive AI will either have to drastically reduce costs or disappear under the pressure of newer, more efficient solutions.