According to Sifted, the AI industry is barreling towards a major inflection point in 2026, when the “innocence” of massive capital investment without clear returns will be lost. The sector is described as the biggest freemium product demo in history, fueled by unprecedented investment and recruitment packages reaching eight figures. Companies like Palantir trade on stratospheric multiples, while OpenAI is reportedly seeking a staggering $750 billion valuation despite massive quarterly losses. Currently, most real profits flow to infrastructure players like Nvidia and cloud hyperscalers, not the AI application companies themselves. The core problem is that the aggregate returns from AI adoption don’t obviously cover the enormous costs being built upstream, setting the stage for a harsh financial reckoning.
The bubble talk is real
Look, we’ve all been dazzled. The capabilities are insane. But here’s the thing: aspirations aren’t cashflows. The article nails it by pointing out the “familiar smell of circular finance”—deals between companies that only work as long as everyone keeps believing. In any other sector, we’d call that a bubble. In AI, it’s called “the future.” But capital markets won’t subsidize thought experiments forever. Training and running these models is brutally expensive, and someone, eventually, has to write a check that doesn’t just go to buying more Nvidia chips. The music is going to stop. The question is, who’s left without a chair?
The monetization hammer is coming
So how does Big AI start making real money? The analysis suggests two brutal paths. First, control of attention. Think about it. If OpenAI needs a $750bn valuation to make sense, a few million ChatGPT Plus subscriptions won’t cut it. They’ll need leverage. We’re talking about an “answer engine” that quietly becomes a direction engine—steering you to sponsored products, default recommendations, and paid placements. Google might have hesitated to cannibalize search, but they won’t sit by while AI hijacks the eyeballs that gaze on their ads. This gets even trickier with agentic AI that doesn’t just answer but acts. Who do you trust when your agent is negotiating with a corporate agent on your behalf? What if the “best” mental health advice quietly points to a paid service? The profit temptation will be too strong to resist.
The second path is the messy world of B2B. If AI becomes essential for innovation, the prize is huge. But this sparks a massive stack war. Everyone—cloud providers, model makers, ERP vendors, consultants—will fight to be the control point where AI gets embedded into workflows. Trust and liability become the new battlegrounds. Will big pharma or consumer goods giants retool their slow-moving organizations to use AI at speed? Or will startups and Big Tech itself move up the stack and eat their lunch? It’s going to be a bloody fight for the enterprise wallet.
Winners, losers, and broken organizations
The impact won’t be some uniform profit uplift for all. It’ll be brutally uneven. Some sectors hide behind regulation. Others, like translation or advertising, face direct displacement. And young graduates? They’re in the crosshairs, as AI eats the entry-level jobs that used to train them. But the deeper insight is about organizations themselves. Throwing AI at a broken company doesn’t fix it; it usually amplifies the problems. As the article notes, companies are systems of incentives and handoffs. AI demands new leadership skills and a total workflow redesign. That’s why reinvention often comes from new companies, not incumbents trying to bolt a chatbot onto a 1990s corporate structure while telling employees not to panic.
Regulation is the new battleground
And then there’s the rulebook. This is where it gets geopolitical. Regulation is no longer a side conversation; it’s the primary battleground for capturing value. Whoever sets the standards and defines liability doesn’t just shape safety—they shape the entire division of power and profits. In a world of national competition, governments will be pushed to act fast. The huge risk? “Protecting the national interest” becomes a convenient banner for today’s incumbents to write rules that lock in their advantage. They could harden today’s AI stack into tomorrow’s unshakeable economic order. It’s a high-stakes game where the winners take all.
Basically, the free ride is over. The era of innocent wonder is done. Now we get to the hard part: deciding who does what, who decides, and most importantly, who pays. It’s going to get messy.
