The market is currently overflowing with hype about Artificial Intelligence. You hear it everywhere: AI is the new revolution, the new internet, the new electricity. Alongside this hype, there’s a palpable fear, especially among software developers and creators, that their jobs are on the verge of disappearing.
You’ve seen the headlines. The CEOs and founders of the world’s largest tech companies are championing this new age, investing billions of dollars into AI development.
But here is the critical fact that gets lost in the noise: The very companies pioneering this revolution are seeing almost no return on their massive investments.
Before you pivot your entire business or career around this new wave, you need to understand the economics of the current AI boom.
The Multi-Billion Dollar Burn Rate
Let’s look at the biggest names in the game: OpenAI (the creators of ChatGPT), Google (with Gemini), and Anthropic (with Claude). All of these companies are in a race, but it’s not a race to profitability—it’s a race for capability.
The reality is, these services are running at a massive loss.
The computational power required to train and run these large language models is astronomical. These companies are spending millions of dollars every single day just to keep the lights on. The revenue they generate from subscriptions and API access is negligible in comparison to their daily operational costs.
Right now, the entire AI industry is not a profitable business; it’s a monumentally expensive research and development project, subsidized by the other profitable arms of these tech giants (like Google’s search advertising) or by burning through billions in venture capital.
The Founder’s Fallacy: Building on an Unprofitable Foundation
If you are a tech CEO, founder, or entrepreneur thinking, “I will use AI to become a millionaire,” you are walking down a very dangerous path.
Why? Because the core services you are building your “next big thing” on are not financially stable. You are basing your business model on another company’s product that is currently losing money.
This isn’t a proven, successful venture capital play. It’s a gamble. We are in a bubble where the cost of the service is artificially low because the providers are willing to lose money to gain market share. What happens when they decide they need to actually make a profit?
This is Not a “Battle-Tested” Method
A core problem is that we are confusing capability with viability.
Yes, AI can write code. But we have no real-world, long-term data on what happens when a company replaces its human developers entirely with AI. How will users react to a product that is built and maintained by an algorithm? What will the user experience be like when the inevitable, strange AI-generated errors appear?
This is not a “war-tested” methodology. We are all part of a live experiment. We simply do not know how the market or the end-user will truly accept a fully AI-driven operation.
The Cost You Don’t See Coming
Right now, an AI-powered startup might seem to have a low initial cost. You can tap into a powerful API without building the model yourself.
However, the long-term integration of this technology is likely to become exponentially more expensive.
The current low prices are temporary. As these AI companies face pressure from their investors to stop losing money, they will have no choice but to dramatically increase their prices. The cost to run your AI-dependent service could skyrocket overnight, making your business model unworkable.
Before you rush into any decisions, understand the reality. AI is a powerful tool, but the current ecosystem is built on hype and unsustainable economics. The “future” everyone is selling you hasn’t figured out how to pay for itself yet.