Deployment is now the (acknowledged) constraint.
I’m not sure if you noticed the AI announcements the past two weeks.
OpenAI and Anthropic just made the same strategic move:
They both stepped beyond selling models and into the messy work of enterprise AI deployment.
OpenAI launched a majority-controlled Deployment Company.
OpenAI Chief Revenue Officer Denise Dresser described the core problem the venture is designed to solve:
“AI is becoming capable of doing increasingly meaningful work. The challenge now is helping companies integrate these systems into the infrastructure and workflows that power their businesses. DeployCo is designed to help organizations bridge that gap.”
Anthropic launched a partner-backed enterprise AI services company with Blackstone, Hellman & Friedman, and Goldman Sachs, where Anthropic Applied AI engineers will help mid-sized companies bring Claude into core operations.
In a May 4th release, Anthropic said: “Putting Claude to work in an organization’s core operations takes hands-on engineering and deep familiarity with how each business runs.”
Different structures but the same signal.
The bottleneck is no longer access to intelligence, it is workflow redesign.
It has always been about workflow redesign.
We’ve been saying this since 2023.
It has always been true that successful AI integration is about a new mindset and constant change as the capabilities improve and you have change models or even change from assistive to agentic AI integration.
Teams that can understand this and build workflows that you can plug and play different versions of AI to create more value will win.
It’s a new game.
And the frontier labs are now admitting what the best AI adopters already know: AI value is captured when leaders choose the right workflows, redesign the work with the people closest to it, and operationalize AI inside the business rather than bolting it on from the side.
In 2023–2025, the differentiator may have been “who has the best model.”
In 2026, these announcements make it clear that everyone knows the differentiator is “who can get AI into production workflows safely and measurably.”
For small businesses the formula is simple:
1. Find the business constraint – Sales or Ops?
2. Identify the workflow that unlocks this business problem
3. Map it with people doing the work
4. Ask your team and AI how we could do this better
5. Ask AI “how Assistive or Agentic AI could improve this process.”
6. Measure it
Then go to the next business constraint.
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I wanted to save this for next week but if you’re a business owner who is feeling the pressure of performance and you don’t have enough time to “learn AI” – the start is not beyond your reach!
