Built a few AI tools and now fighting duplication and drift? The case for an internal AI marketplace — what goes in it, how to layer it, and how to curate it.
The first AI tool a company builds is exciting. The fifth is where the trouble starts.
By then, three teams have each written their own version of "summarise this in our tone of voice." Two of them hardcoded a slightly different brand colour. One pasted an API key into a script it shouldn't be in. Nobody can say which prompt is the good one, and a new hire rebuilds half of it from scratch because they didn't know it already existed.
The problem has quietly changed shape. It is no longer how to build AI capabilities — that part got easy. It is how to reuse them without losing track of quality, security, and brand. That is the problem an internal marketplace solves, and it is the difference between a company that does AI as a string of one-off experiments and one that runs it as infrastructure.
This is the case for building one: what it actually is, the three problems it fixes, what goes in it, how to layer it, how to curate it so it doesn't rot, and how to tell whether you're ready.
Strip away the word and a marketplace is a curated catalogue of vetted, reusable AI capabilities that anyone in the company can find and install instead of rebuilding. One place, one version per capability, a named owner for each. The capabilities are things like a writing-voice standard, a security rule set, a document generator, a content workflow, a small task-specific agent.
It is the same idea that component libraries brought to engineering and that internal tooling teams brought to data: stop solving the same problem five times in five slightly different, slightly wrong ways. The value is not the catalogue itself. It is that the catalogue becomes the single source of truth, so an improvement made once reaches everyone, and a rule set once is followed everywhere.
When a capability lives in one place, a fix or improvement propagates to every team that uses it. When it is copied into five tools, every copy drifts. Six months later the company has five different answers to "how do we write a follow-up email," none of them owned, all of them subtly out of date. A marketplace makes "build it once, use it everywhere" the default rather than the exception, and it turns an improvement into something that compounds instead of something that has to be re-applied by hand in five places.
The cost of drift is rarely a dramatic failure. It is a slow tax: slightly-off outputs, time spent reconciling versions, and the quiet erosion of a consistent voice and standard.
This is the part operations, security, and legal care about most. Rules — never paste client data into a prompt, use these exact brand tokens, handle personal data this way, this is how we write — can live as shared foundations that every other capability is built on. Set the guardrail once; everything in the catalogue inherits it.
The alternative is hoping each team remembers each rule each time. That does not scale, and it does not survive an audit. A marketplace turns governance from a memo people are supposed to have read into a property of the tools themselves. When a rule changes, you change it in one place and every capability that references it is updated — not thirty scattered copies you have to find first.
A new person should install what exists, not rebuild it. Without a catalogue, every joiner re-discovers the same prompts, repeats the same mistakes, and re-learns the same lessons that left with whoever wrote them. A marketplace turns institutional knowledge into something you can hand someone on day one. The scarce question shifts from "who here knows the good prompt" to "what's in the catalogue" — and that is a question with an answer that survives people leaving.
A useful catalogue holds a few distinct kinds of capability, each with an owner and a clear description of when to reach for it:
The unifying property is that each entry is a packaged, reusable unit with a name, a description that says when to use it, an owner, and a version — not a clever prompt buried in someone's chat history.
A marketplace works best in layers, and the layering is what keeps governance from becoming a copy-paste exercise.
At the base sit the shared non-negotiables: how you write, what you never expose, your visual identity, your data-handling and licensing rules. On top sit domain catalogues — one for engineering practices, one for business and marketing operations, and so on. Each domain capability references the foundations rather than restating them. So when a rule changes, it changes once at the base and propagates up; nothing downstream holds its own stale copy.
This is exactly how we structure it, for ourselves and for clients: a foundations layer that owns the guardrails (voice, security, brand, privacy, legal, accessibility), and separate domain marketplaces — engineering, operations — built on top of it. The discipline that makes it hold together is one rule: capabilities live in one place and are referenced, never duplicated. Duplication is how drift creeps back in, so the architecture is designed to make referencing easier than copying.
A marketplace is only as good as its curation. A catalogue anyone can add anything to, with no review and no owner, becomes a dumping ground — and a dumping ground is worse than nothing, because it looks like order while spreading the same drift you were trying to stop. A new joiner who installs three things that don't work trusts the catalogue less than if it had been empty.
Curation is the actual work, and it is light but non-negotiable:
This is the difference between a marketplace and a folder. A folder accumulates. A marketplace is tended.
Most companies are not at the marketplace stage, and forcing it early is its own waste. If you have two AI tools, you have a folder, not a platform, and the overhead of a catalogue exceeds its value. Build the tools first.
The signals that you're ready are specific:
When two or more of those are true, the bottleneck has moved from building to reuse and governance, and another tool won't fix it. What fixes it is a place to put the good ones, with the rules built into the floor.
The shift this creates is more than tidiness. Once the catalogue is good, individual cleverness matters less and shared, vetted capability matters more — which is exactly the point at which AI stops being a collection of experiments and starts being infrastructure the whole company compounds on. That is the difference between doing AI and operating it.
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