When a growing company gets serious about AI, the first question usually sounds practical. Do we hire someone, buy a tool, or hand the project to an outside team?

The enterprise market just answered that question in a fourth way. OpenAI and Anthropic are putting serious capital behind embedded teams that sit inside customer organizations and turn AI into working systems. If you run a Fortune 500, that path is becoming clearer by the week.

If you run a 50 to 500 person company, that path was not built for you, and the price tag was not sized for you either. So the real question for the operators I meet is simpler. What is my version of that?

The three options most teams weigh

When a growing company gets serious about AI, the conversation narrows to three choices. Each is reasonable. Each has a failure mode we see often.

Build it. Hire an AI engineer, maybe a small team, and own the capability in-house. It can work, and it is slow and expensive. A strong AI engineer runs six figures, is hard to find, and harder to keep. You wait months to learn whether the first project even lands, and one hire rarely covers strategy, data, building, and adoption at once. For most SMBs, building is a large bet placed before you have any evidence.

Buy it. Pick a tool off the shelf and roll it out. Fast and cheap to start, which is why it tempts everyone. The trouble is that a tool is not a result. Software shows up with a login and a training video, and adoption becomes your problem. We have watched more pilots die this way than any other.

Outsource it. Hand the project to an agency. You get capacity without a hire, which helps. The risk is that a typical shop ships a project and leaves, right when the data turns out dirty and the team needs convincing. AI is not a one-time build. It needs someone who stays through the messy middle.

The fourth option: borrow the team

There is a fourth path that fits a smaller company better than any of those, and it is the same model the giants are paying billions for. Borrow the team.

Bring in people who have already shipped AI inside businesses like yours. They embed with your team the way OpenAI's engineers embed with theirs. They map your workflow, build the pilot, and stay long enough to turn it into a system your people trust. You get strategy, building, and adoption from a group that has done it before, without the cost and lead time of building in-house or the abandonment risk of a project shop.

Think of it as the technical co-founder you can borrow. You would not expect one off-the-shelf tool to replace a co-founder who understands your business. It will not replace the work of getting AI into production either.

How to choose

A quick way to read it. Build if AI will be core to your product and you can fund the wait. Buy if you have a narrow, well-defined need and a team that adopts new tools easily. Borrow if you want results in weeks, you have no AI expertise in-house, and you need someone accountable for adoption, not delivery alone.

For most B2B SMBs in the 50 to 500 person range, borrowing is the honest answer. You get the embedded model the labs validated this month, sized for your business and pointed at outcomes you can measure quickly. If you want help placing your own company on that map, the AI Readiness Assessment is a practical starting point.

The bottom line

OpenAI and Anthropic spent billions this month proving that embedded expertise is what turns AI from a demo into a result. The model is sound. The real question for a smaller company is how to get the same thing without an enterprise budget.

You do not need to build a department or gamble on a shelf. You need a team you can borrow, focused on one workflow at a time, that stays until it works.

Not sure whether to build, buy, or borrow? The AI Readiness Assessment helps map the decision to your workflows.