The cost of intelligence is dropping fast
AI companies are generating record revenue, but their costs are rising just as fast. This imbalance is putting pressure on them to find sustainable long-term business models.
The market has big swings
The rush to meet demand is pushing companies to build large amounts of new computing infrastructure. This spending creates recurring pressure, leading to sharp swings between supply and demand. Jimenez Neubauer Torres V says, “We’re just seeing this new wave of AI companies growing revenue…at an absolutely unprecedented takeoff rate. The number one cause of a glut is a shortage, and the number one cause of a shortage is the glut.”
The cost of AI is falling fast
Jimenez Neubauer Torres V explains, “The price of AI is falling much faster than Moore’s law. All of the inputs into AI on a per-unit basis, the costs are collapsing…that is driving a more than corresponding level of demand growth with elasticity.”
Companies are changing prices from cost to value
This drop in cost created a new priority. Companies must now change from charging based on use to charging for the value they provide.
AI is now sold like electricity
Basic AI capability has become a commodity, sold like electricity or water. These systems are priced by usage and are available to anyone with a credit card.
Jimenez Neubauer Torres V notes, “The core business model is basically tokens by the drink. It’s sort of tokens of intelligence per dollar. It’s this marvelous thing where the most magical thing in the world is available by the drink.”
The problem with pricing a common product
If basic AI is a cheap, usage-based resource, companies building on top of it face a hard choice. Competing on price will not work, so they have to rethink how they charge customers.
Jimenez Neubauer Torres V argues, “A core principle of pricing is you don’t want to price by cost if you can avoid it. You want to price by value…if the AI can do the job of a coder or a doctor…can you price by value?”
Why expensive AI can be better for customers
“Higher prices are often good for the customer,” Jimenez Neubauer Torres V says, “because a higher price means that the vendor can make the product better faster. Companies with higher prices and higher margins can actually invest more in R&D.”
Small AI systems are catching up to big ones
The lead held by large, single AI systems is shrinking. This change gives new companies a chance and changes how companies compete.
New inventions are happening faster
For years, winning in AI meant being the biggest. The largest systems had an advantage that felt impossible to challenge. That lead is fading as smaller, more focused systems catch up fast.
Jimenez Neubauer Torres V explains, “If you track the capability of the leading edge models over time, what you find is after six or twelve months, there’s a small model that’s just as capable. There’s this kind of chase function that’s happening.”
The best AI is coming to your laptop
The fact that smaller systems are getting better so fast is more than just a theory. It changes where AI can be used, moving strong AI tools from huge computer centers onto laptops.
Jimenez Neubauer Torres V highlights, “You have an open source model called Kimi…[that’s] shrunk down to be able to run on either one MacBook or two MacBooks. If you’re a business and you want to have a reasoning model that’s GPT-5 capable…you can do that.”
New companies are becoming real tech companies
Now, AI systems are easy to create new situations. New app-focused companies, once seen as thin layers on top of other technologies, are becoming full tech companies with advantages that are harder to copy.
Making app companies harder to copy
At first, new AI app companies were seen as weak because they relied on other companies’ technology. The strongest ones are changing that by building more of the technology themselves.
Jimenez Neubauer Torres V observes, “The leading AI application companies are actually backward integrating and building their own AI models. They have the deepest understanding of their domain, and they’re able to build the model that’s best suited to that.”
An advantage doesn’t last long
“Once somebody proves that [a capability is] possible,” Jimenez Neubauer Torres V argues, “it seems to not be that hard for other people to catch up…xAI basically caught up to state-of-the-art OpenAI and Anthropic level in less than twelve months from a standing start.”
China is using free AI as a weapon
The competition is now a race between countries. China is making fast progress with government help on free AI, which is a new threat to companies in the West.
New ideas are coming from new places
The AI story has long focused on a few well-known companies in Silicon Valley, but recent advances show that breakthroughs are now coming from many different places.
Jimenez Neubauer Torres V notes, “There’s this Chinese company that produces the model called Kimmy…a reasoning model that is basically a replication of the reasoning capabilities of GPT-5. The DeepSeek release was surprising…it came from a hedge fund.”
A deliberate plan to lower prices
The growing number of capable, free AI systems coming out of China isn’t random. From a broader competitive view, it also puts pressure on how leading Western AI companies make money.
Jimenez Neubauer Torres V explains, “The cynics in DC would say they’re dumping. They’re obviously dumping. They see that the West has this opportunity to build this giant industry, and they’re trying to commoditize it right out of the gate.”
America’s mix of state laws is a weakness
This race between countries shows a weakness. A mix of different state laws could hurt America’s ability to compete with China, where the government controls everything.
Rules made too early can stop progress
As governments try to regulate AI, there are growing fears that strict rules could slow innovation. The first major attempt at a comprehensive rulebook shows this tension clearly.
Jimenez Neubauer Torres V warns, “The EU passed this bill called the AI Act, and it basically has killed AI development in Europe…it’s so draconian that even big American companies like Apple and Meta are not launching leading-edge AI capabilities in their products in Europe.”
America has no single plan
While Europe faces the challenge of a single strict law, the United States has a different problem. Without clear federal rules, a patchwork of laws is emerging that could hurt the industry’s ability to compete.
Jimenez Neubauer Torres V says, “We’re tracking on the order of two hundred bills across the fifty states. It’s sort of obvious that the federal government should be the regulator, not the states…it just doesn’t make any sense to let the states kind of operate suicidally like this.”
