Wall Street presses AI monetisation

Greg Brockman’s testimony this week landed because it turned an abstract AI boom into a very concrete Wall Street question — who is actually getting paid, how much, and what exactly are investors buying into? In federal court in Oakland on May 4, OpenAI’s president said his stake in the company is worth nearly $30 billion and acknowledged deeper financial ties to Sam Altman than had been publicly known. That came in Elon Musk’s lawsuit over OpenAI’s shift away from its original nonprofit structure. Why does that matter beyond courtroom drama? Because the market mood around AI is changing. For the last couple of years, the easy story was adoption — more users, bigger models, faster chips, more data centers. Now the harder question is monetisation. Investors still believe AI could remake software, search, advertising, cloud computing, and customer service. But belief is no longer enough on its own. They want to know whether the giant spending wave can turn into durable cash flow rather than just bigger infrastructure bills. What changed on the spending side? The scale got harder to wave away. Bloomberg’s tally last week put planned 2026 capital spending by the biggest US tech groups at as much as $725 billion, driven mainly by AI data-center equipment. Alphabet and Microsoft were each pegged around $190 billion, Amazon stayed near $200 billion, and Meta raised its range to $125 billion to $145 billion. That is no longer “investing for the future” in the casual sense — it is an industrial buildout. So why is Wall Street pressing now instead of cheering? Because once the numbers get that large, investors stop rewarding ambition by default. They start asking which company has a real revenue engine and which one just has a very expensive science project. Meta’s stock drop after it lifted capex guidance was a clean example. The market wasn’t saying AI is fake. It was saying the burden of proof has gone up. Where does OpenAI fit in that? OpenAI sits at the center of the whole trade. It helped kick off the generative-AI frenzy, it has raised well over $100 billion, and it is being discussed as a possible trillion-dollar IPO candidate. That makes its governance structure unusually important. If a company that influential is still sorting out who controls it, who benefits financially, and how nonprofit language fits with enormous private stakes, investors read that as more than gossip — they read it as execution risk. Is this just about OpenAI’s courtroom mess? Not really. OpenAI is the sharpest example, but the issue is broader. Public-market investors are now separating AI companies into two buckets. One bucket can point to visible payoffs — stronger cloud demand, better ad targeting, more enterprise software sales. The other bucket mostly points to usage growth and future potential. The first bucket gets patience. The second gets interrogation. What’s the real tension underneath all this? AI still looks like a platform shift, but platform shifts are expensive before they are profitable. The catch is that the financing story and the governance story are now colliding. If companies are asking markets to tolerate enormous spending, they also need to show cleaner control structures, clearer incentives, and a believable path from hype to margins. The bottom line is simple. Wall Street has not turned against AI. It has moved to the next phase. The question is no longer whether AI is important. It is who can turn that importance into profits without blowing up trust on the way.