Last week, OpenAI and Anthropic both launched professional services companies in the same week targeting the enterprise AI transformation market. OpenAI's vehicle, DeployCo, is backed by $4 billion in initial investment from Capgemini, Bain, and McKinsey. Anthropic's came with Wall Street financial services backing.
The stated rationale from OpenAI: the challenge is no longer building capable AI. The challenge is helping organizations integrate it into the infrastructure and workflows that drive their business.
This is worth pausing on. The companies that built the technology have concluded they need to own the transformation layer to deliver on their own promises. That tells you something important about where the actual work is.
The 93% problem
The labs didn't make this move arbitrarily. The 2026 AI & Data Leadership Executive Benchmark Survey found that 93% of Fortune 1000 data leaders identify culture and change management as the primary barrier to AI adoption. Just 7% point to technology.
A separate study of 6,000 senior executives found that 69% report active AI use, but 90% say it has had no measurable impact on productivity.
Your organization may recognize itself in that data. Teams using AI tools. Leaders asking why the outcomes haven't changed. The gap between deployment and value is not a model problem. It's an organizational problem: unclear ownership of decisions, workflows that weren't redesigned, leaders who weren't brought along, adoption patterns that don't match the capability available.
The labs are now in the business of solving that problem. They've confirmed it's the real problem.
What this means for your evaluation
If you are assessing AI transformation partners right now, the events of this week clarify something useful: the question has changed.
The old question was: which AI tools should we deploy? That question has largely been answered. The tools exist. The capabilities are real and improving.
The new question is: what does it take for our organization to actually capture value from those capabilities? That question requires a different kind of partner than a platform vendor.
It requires practitioners who can diagnose the organizational conditions that are blocking execution, not just assess your tech stack. Who can work at the level of leadership behavior and change management capability, not just integration architecture. Who can build adoption patterns that hold under the day-to-day pressure of how your organization actually operates.
What specialized transformation practices offer
DeployCo and its counterparts will serve the large enterprise market well. The engagements are going to be priced and structured accordingly.
The organizations that get the most from specialized transformation partners tend to share a profile: they have clear intent and real leadership commitment to AI adoption, but they've hit execution limits. They've deployed tools that aren't being used consistently. They have pockets of strong adoption and pockets of resistance that nobody has systematically addressed. They've made the technology investment and are still waiting for the organizational investment to catch up.
That's a solvable problem. But the solution isn't another platform evaluation or a second wave of tool deployment. It's a structured approach to the organizational conditions that determine whether capability becomes performance.
Artisan's work starts with the organizational diagnosis: understanding why the current state exists before prescribing a path forward. That work doesn't require the size or the investment structure of a DeployCo engagement. It requires practitioners who have done it before and can move quickly to the level where the real leverage is.
The question worth asking before your next planning cycle
The labs just told you, with a $4 billion capital allocation decision, that the transformation gap is the business problem worth solving.
The question for your planning cycle is whether your current AI investment strategy is designed to close that gap or whether it's still optimized for model selection and deployment velocity, while the organizational readiness question waits for the next cycle.
If you'd like to talk through what that diagnosis looks like for your organization, that's where we start.