When Every Company Becomes an AI Company, Nobody Wins

There's a pattern emerging in the AI industry that should make anyone uncomfortable: every major player is trying to do everything, all at once.

Meta is reportedly building its own cloud business to compete with AWS and Google Cloud. Not because Meta has any particular expertise in enterprise cloud services, but because it has AI infrastructure sitting around and figures it might as well monetize it. Google, meanwhile, is stuffing AI agents into Gmail, its macOS app, and apparently every other product that will hold still long enough. And OpenAI? According to recent reports, it's in talks to give the US government equity stakes in itself and its competitors—a move that reeks of regulatory capture dressed up as public benefit.

This isn't innovation. It's panic.

The underlying problem is that AI development has become so capital-intensive that companies feel compelled to extract value from every possible angle. When you've spent billions building data centers and training models, the temptation to become a cloud provider, a SaaS vendor, a hardware manufacturer, and a platform operator all at once becomes overwhelming. The result is a tech landscape where strategic focus has given way to sprawling, unfocused expansion.

Consider what this means in practice. Meta has no competitive advantage in cloud services. Its core competencies are in consumer social platforms and advertising technology. Building a cloud business means competing with Amazon, Microsoft, and Google—companies that have spent decades refining their enterprise offerings. But when you've invested heavily in AI infrastructure, the sunk cost fallacy becomes irresistible.

Google's approach is equally problematic, just in a different direction. By embedding AI agents into every product—from Gmail to file management to document organization—the company is creating a user experience where AI mediation becomes mandatory rather than optional. The $100 per month price tag for Gemini AI Ultra subscribers suggests Google sees this as a premium feature, but the aggressive integration strategy suggests otherwise. This is about lock-in, not user choice.

And then there's the OpenAI government equity proposal, which deserves its own category of concerning. If accurate, this represents an attempt to preemptively negotiate regulatory frameworks by giving the government a financial stake in the industry's success. It's regulatory capture as a business model—ensuring that the government's interests align with AI companies' growth rather than with public safety or competitive markets.

The common thread? None of these moves are about building better AI or solving real problems. They're about protecting market position and maximizing return on massive infrastructure investments. That might make sense from a quarterly earnings perspective, but it's creating an AI ecosystem that's increasingly baroque and user-hostile.

We've seen this pattern before. In the late 1990s, every company wanted to be a portal. In the 2010s, everyone needed a social network. Now, everyone needs to be an AI company with vertical integration across the entire stack. History suggests this ends badly—with a market shakeout, regulatory intervention, or both.

The irony is that the most successful AI applications we've seen so far have been focused, not sprawling. Luxonis's OAK cameras for physical AI perception. Built Robotics' autonomous construction systems. These companies identified specific problems and built targeted solutions. They're not trying to own the entire stack or insert themselves into every possible revenue stream.

Maybe that's the lesson here: the AI companies that survive the next five years won't be the ones trying to do everything. They'll be the ones that actually know what they're for.