AI Accenture, Not Accenture for AI
Productizing diffusion. Accelerate the world.
Deployment is the main thing
We’re in the installation period of the AI supercycle where hype, speculative capital, and technological progress are rampant. The deployment period, where it becomes usefully integrated into our productive base, is just beginning and will last generation(s).
Deployment is the most important thing happening in the world right now. Acceleration and abundance vs stagnation rests in the balance.
Accordingly, there is intense, widespread interest in making bets directly on deployment. Betting not just on the beneficiaries (new AI-enabled products and services) but also on the delivery (the IT services working on AI transformation projects for legacy institutions).
System integrators and other consultants/AI services firms are/will be the connective tissues between installation and deployment.
There are three or four main flavors of AI services right now:
Fast moving FDEs/bodyshops: (elite) generalist teams parachuting into enterprise transformation work horizontally and on a per-engagement basis
The captives/joint ventures: the deployment arms and JVs being spun up by the labs and hyperscalers
The product companies: specialists building an internal product that delivers a specific outcome for a specific kind of customer, repeatedly. We have one company here (operating as a system integrator) and are looking for more. And of course there are a few companies selling these kinds of tools externally to other service providers (arguably the fourth).
The bodyshop approach is a rational response to the current market environment and the belief that things are moving too fast to do anything else. There’s not time to build a product; you just have to do stuff. It’s also a much better deal for a certain kind of talent. The best FDEs get to be the hero and directly monetize their skills instead of running customer success for a research team that sees deployment as overhead.
The JVs/captives are a fundamentally different proposition but also rational for their backers/creators. Their deployment JVs don’t need to create value companies directly; instead they generate EV by expanding the surface area and lock-in for their sponsors. Investing $100M to improve the odds for a $10B position is obviously rational. At $1T it becomes necessary.
Of course there is some risk of a “Hotel California” situation: once they’ve built your AI infrastructure on their stack, with their FDEs, around their models, you can’t check out. Their people aren’t working for your outcome, they’re working for their sponsor’s lock-in. The tradeoff is that they have max recognition and access, so a lot of buyers will take the deal anyway.
The most interesting version of the story is a product company delivering a service, rather than a service company delivering a product.
The internal product enables differentiated service delivery. The product might look like some combination of an agent/harness, context layer, workflow automation, etc. but in any case you’re creating a product that you consume internally in order to deliver a service externally (to your customers) better, faster, cheaper. The product companies bend the cost curve down rather than charging more because of temporal buying pressures and unique access to talent.
One of the most obvious tells is whether you’ll do anything for everyone or if you have a narrowly defined ICP. Are you trying to productize the process that delivers a specific kind of outcome in a specific context, or are you offering to do custom work and build anything your customers want? The product companies will have clear religious beliefs about what they can’t touch or won’t do.
We’re looking to back AI Accenture, not “Accenture for AI.” That is, there’s an immense opportunity for services companies to fundamentally rebuild how they deliver, not merely what they deliver.
Read more:
Cliff Club
Introducing Cliff Club: a community exclusively for early employees at venture-backed companies and we’re starting with NYC first!
We’re gonna bring in great early operators and subject matter experts to talk about questions like:
WTF is QSBS?
How should I think about early exercising?
How should my role evolve as the company scales?
How should I feel about getting layered?
Should I specialize into a role?
Really excited to work on this with my friends Charley and Leeor.






Hi Yoni! AI-native service businesses can be built for law firms, consultancies, and accounting firms. These businesses would be able to earn a higher profit margin due to the use of AI integrated into everyday workflows. I write a blog in substack titled "The LegalTech Thesis," wherein I analyze LegalTech startups, trends, and opportunities in the space to invest in. Would love to get your thoughts on my post analyzing AI-native law firms as an investment opportunity in 2026.
https://harshithviswanath.substack.com/p/three-legaltech-whitespace-plays