OpenAI just launched a $4 billion venture to become a consulting firm.
This week, OpenAI launched the OpenAI Deployment Company, a majority-owned venture with more than $4 billion in initial investment from OpenAI and 19 outside partners including TPG, Advent, Bain Capital, and, notably, consulting giants McKinsey and Bain themselves. OpenAI holds the majority stake. The new company's job isn't to build models. It's to get companies to actually use them.
The pitch is straightforward. OpenAI's investment partners collectively touch more than 2,000 portfolio companies, and the consulting partners work with thousands more. That's a built-in customer base guaranteed to be steered toward ChatGPT deployments. Denise Dresser, OpenAI's chief revenue officer, framed it as helping companies "integrate these systems into the infrastructure and workflows that power their businesses."
Translation: the model isn't the product anymore. The deployment is.
There's a very good reason OpenAI is doing this. According to a new Orgvue survey, 92% of organizations have now invested in AI. 78% say those projects have either failed outright or stalled in pilot. And 57% admit they deployed AI in the first place because their competitors did, not because they had a plan.
"Failed AI deployments are not a technology problem; they're a workforce design problem," said Oliver Shaw, Orgvue's CEO. Companies bought the tools. Nobody figured out what to do with them.
The company that already cracked this is Palantir, and its latest earnings show what happens when you get it right.
- US revenue up 104% year-over-year to $1.28 billion, with US commercial up 133% to $595 million
- 47 deals over $10 million closed in a single quarter, with total contract value up 61%
- Rule of 40 score of 145%, a profitability-plus-growth metric that CEO Alex Karp noted only Nvidia, Micron, and SK hynix have matched
Palantir's whole business is what the industry calls forward-deployed engineering: sending your own people to sit inside customer companies and actually build the AI workflows for them. It's slow, expensive, and doesn't scale the way SaaS does. But it works, and enterprises are paying massive sums for it, which is exactly why OpenAI and Anthropic are now trying to copy the playbook.
Accenture is running a version of the same play from the consulting side, with CEO Julie Sweet telling investors the firm is "moving clients from using AI to running on AI." Marc Nachmann, Goldman Sachs' head of asset and wealth management, made the point more bluntly when discussing Goldman's Anthropic partnership: "Having the model alone doesn't change your workflows or how you operate. You need people who can combine the technology with what's actually happening in the business." Which is a strange thing for a bank to have to say out loud, but here we are.
The moat in AI was never going to be the model. Everyone in the industry has known this for a while, they just didn't say it. Models are becoming commodities, open-weight options are catching up fast, and inference keeps getting cheaper. What isn't commoditized is the messy human work of figuring out what a company actually does and how AI could plausibly help. That's the business OpenAI just bought its way into, and the one Palantir has been quietly cornering for years. Just keep an eye on who benefits: when private equity is fronting $4 billion to "integrate" AI into their own portfolio companies, the productivity gains rarely end up with the workers doing the work.
