The enterprise AI deployment gap is now the biggest business opportunity in tech

Disclaimer: i work at Twilio, where we think about enterprise AI deployment constantly, but views here are my own.

Anthropic and OpenAI both launched AI services ventures this week, backed by billions from Blackstone, Goldman Sachs, Hellman & Friedman, TPG, and Bain. The timing wasn’t coincidental and the logic was identical: the models are ready, the organizations are not, and closing that gap is large enough to build multi-billion dollar businesses around.

What both announcements said pretty clearly is that model capability alone doesn’t produce business outcomes. Right. Dario put it plainly: enterprise demand for Claude is significantly outpacing any single delivery model. The services arm is the response to that signal.

But i think that the gap is deeper than the technical framing alone suggests.

Getting an agent to work reliably in a business process requires someone to articulate that process with a level of precision most organizations have never needed before (yes, you know that.)

What is the goal? What does good output look like? Where does human judgment stay in the loop? Most processes have answers to those questions living partly in someone’s head, partly in an outdated document, and partly in informal corrections that experienced people apply automatically without ever writing down. I’ve been doing this work hands-on and the thing that still consistently surprises people (especially those who are still stuck with asking ChatGpt for email rewrite) is how much of the challenge has nothing to do with the tech at all.

The IT integration is solvable; the question that takes the longest (and occasionally exposes things leadership would rather not examine) is whether the organization can clearly describe what it’s actually trying to accomplish.

For anyone who understands the PE model, the structure of the Anthropic venture matters for a reason beyond distribution. Blackstone owns 250+ portfolio companies. PE firms operate on compressed timelines with explicit return expectations, which is incompatible with the “let’s run a pilot and revisit next quarter?” approach most enterprises take. One of the most consistent failure modes in enterprise AI is that initiatives get launched and then stall when the work of actually changing how people work runs into organizational friction. PE ownership removes some of that insulation in a way a vendor relationship cannot.

My honest read on both announcements is that the labs can serve companies that are already ready, and through PE, companies that will be forced to get ready on a compressed timeline. What fills the gap for everyone else - the companies without PE ownership, without organizational clarity, without internal deployment capacity - is the more interesting question for the next 18 months.

ps - while writing this article i realised that i have to write a follow up piece soon on the bit i mentioned above 👇

The IT integration is solvable; the question that takes the longest (and occasionally exposes things leadership would rather not examine) is whether the organization can clearly describe what it’s actually trying to accomplish.