What does "AI at the core" mean?

It is a positioning phrase asserting that AI sits in the centre of a business rather than at its edges: in the value proposition the customer buys, not merely in the operations that produce it. Unlike AI-native, which is a structural claim about how something was built, AI at the core is a strategic claim about where the AI creates value. It is used loosely, and the useful version has a specific test attached.

How is AI at the core different from AI-native?

AI-native is about construction: the thing was built around AI and stops working without it. AI at the core is about commercial position: the AI is part of what the customer is paying for. They often coincide and do not have to. A company can be AI-native in how it operates while selling something whose value has nothing to do with AI, and a company can put AI at the core of its offer while running a conventional organisation behind it.

What is the test for AI being at the core?

Ask what the customer would notice. If you removed the AI and customers received a worse or slower version of the same thing, AI is in operations. If removing it means you no longer have the product, it is at the core. The second is a much stronger claim and a much more exposed position, because your product is then partly someone else's model.

Is putting AI at the core risky?

Yes, in specific and manageable ways. Your product roadmap becomes coupled to a provider's release schedule, a model deprecation becomes a product migration, and pricing changes upstream hit your margin directly. None of these are reasons not to do it. They are reasons to hold a second provider path and to know which parts of your value depend on a specific model rather than on capability generally.

Can a services business put AI at the core?

It can, and the honest version is uncomfortable, because it means selling an outcome rather than hours. A services firm using AI to produce the same deliverables faster has AI in operations and will find that the market eventually prices that in. Putting it at the core means the deliverable itself is something a conventional firm cannot produce at all, which is a harder proposition to build and a considerably more defensible one.

Is "AI at the core" a recognised term?

It is common in strategy writing and it is not a term of art, with no settled definition and almost no direct search demand. We treat it as a positioning phrase worth defining precisely rather than a concept with an established meaning, and we would generally advise making the specific claim underneath it instead, since a specific claim can be evaluated.

AI at the Core: Is AI in What You Sell, or How You Make It?

Core means the customer is buying the AI

"AI at the core" claims that AI sits in the value proposition rather than in the back office. There is one question that settles it: if you removed the AI, would customers get a worse version of your product, or would you no longer have one? Most companies using the phrase mean the first, which is a good position described with the wrong words.

By Thomas Prommer · Published 11 August 2026 · 5 min read

A note on the phrase

This is a positioning phrase rather than a term of art. It has no settled definition and, unlike agentic or AI-native, essentially nobody goes looking for it. We define it here because it appears constantly in strategy documents and because the distinction it gestures at is worth having, but the general advice is to make the specific claim instead. Specific claims can be evaluated; positioning phrases cannot.

Core versus operations

AI in operations: AI makes you faster, cheaper or more consistent at producing something whose value does not depend on AI. The customer benefits indirectly, through price, speed or quality. This is where the overwhelming majority of value currently sits, and it is not a lesser position.

AI at the core: the AI is what the customer is buying. Remove it and there is no product, not a slower one.

The reason to keep these apart is that they have different competitive dynamics. Operational advantage from AI is real and temporary: it is available to your competitors from the same vendors, and the market prices it in. Core positioning is harder to reach and harder to copy, because it usually requires having built something around a capability rather than having adopted a tool.

What it costs to actually be there

Putting AI at the core imports three commitments that operations use does not:

Model changes become product changes. A deprecation is a migration, a behaviour change is a regression your customers notice, and neither is on your schedule.
An upstream outage is your outage. Not degraded internal productivity, but the thing you sell being unavailable.
Upstream pricing lands on your margin. Directly, with limited ability to renegotiate.

These are manageable, and managing them is what distinguishes a company that made the decision from one that drifted into it. The practical minimum is knowing which parts of your value depend on a specific model rather than on model capability generally, and having a tested path to a second provider for those parts.

The services version, which is the awkward one

For a services business the distinction is uncomfortably sharp. Using AI to produce the same deliverables faster is operations, and the market will eventually extract that saving through price, because your competitors have the same tools. Putting AI at the core means the deliverable itself is something a conventional firm cannot produce, which usually means selling an outcome rather than time. That is a harder business to build and a much more defensible one, and pretending the first is the second is the most common version of this claim being made badly.