OpenAI Built a Tool for Everyone. Then Enterprise Money Changed Everything.

There was a version of ChatGPT that felt like a gift.

Not because it was perfect. But because it felt like it was genuinely trying to help you think. It met you where you were. It was patient, curious, and surprisingly humble about what it didn't know. Everyday people discovered they could use it to draft a letter to their landlord, understand a medical diagnosis, help their kid with homework, or finally articulate something they'd been struggling to say for years.

That version of ChatGPT changed something real for millions of people.

Then the enterprise contracts came in.

I was at OpenAI early enough to understand what the founding mission actually felt like from the inside. There was a genuine belief that artificial intelligence, done right, could be the most democratizing technology in human history. The goal was never to build a better enterprise software suite. It was to give every person on earth access to the kind of thinking partner that used to be reserved for people with resources, connections, and expensive advisors.

That mission didn't disappear overnight. It eroded gradually, the way most missions do, under the weight of revenue targets, enterprise feature requests, and the compounding pressure of competing with well-funded rivals.

The result is a product that has quietly reoriented itself around its highest-paying customers while the everyday user is left wondering why the thing they loved seems to have gotten worse.

They are not imagining it.

When a product serves two masters — the enterprise buyer and the individual user — it eventually has to choose. Enterprise buyers have procurement teams, legal requirements, compliance needs, and six-figure contracts. They get dedicated support, custom features, and a seat at the product roadmap table. Individual users get a pricing page and a waitlist for the good model.

This is not a criticism unique to OpenAI. It is the inevitable physics of venture-backed technology companies. The seed round funds the dream. The Series B funds the pivot. The enterprise contract funds the company. By the time you reach scale, the product that exists and the product that was promised are rarely the same thing.

What makes this moment different is that the stakes are higher than they have ever been.

We are not talking about a social media algorithm that shows you worse content. We are talking about the infrastructure layer of human cognition. AI is becoming the system people use to make decisions, understand the world, and navigate complexity. When that system optimizes for enterprise revenue over individual utility, the consequences are not just commercial. They are civilizational.

The everyday user who feels like ChatGPT has gone backwards is not being irrational. They are observing something real. The product has been repositioned around them, not for them.

I have spent my career inside the rooms where these decisions get made. At OpenAI. At Spotify, where I led AI for 675 million users and watched firsthand what happens when you have to balance individual experience against institutional pressure. At Coinbase during the FTX collapse, when the gap between what a technology promised and what it actually delivered became impossible to ignore.

The pattern is always the same. The mission is real at the beginning. The drift is gradual. And by the time the everyday user notices, the people making the decisions have already moved on to the next problem.

The question worth asking now is not whether OpenAI has drifted from its original mission. It clearly has. The question is whether that drift is reversible, or whether we are watching the permanent institutionalization of a technology that was briefly, genuinely, trying to serve everyone.

I am not optimistic. But I am watching closely.

That is what The Looming Horizon is for.

Andrew Quillen is a principal AI strategist, former Head of AI at Spotify, and founder of AndMaverick LLC. He advises enterprise and government clients on AI systems architecture and the long-term implications of artificial intelligence. His book and podcast, The Looming Horizon, explore what happens when transformative technology concentrates power without moral architecture.