How long does AI implementation take?

The honest answer: a focused first system is usually live in four to eight weeks. Not the year-long programme some firms try to sell. The timeline is mostly a function of how tightly the project is scoped, so here is what those weeks actually look like, and where time gets lost.

Week by week, roughly

Week one is discovery and scope: we map the workflow, agree exactly what the system will and won’t do, and write it down. Weeks two to five are the build, connecting to your tools, wiring the logic, testing against real cases. The last week or two is rollout: getting it in front of your team, fixing what trips them up, and confirming it’s actually being used. You see something working well before the end, not at some distant finish line.

What makes a project take longer?

Three things, mostly. Messy data is the big one, if the information the system needs lives in three spreadsheets that disagree, cleaning that up comes first. The second is scope creep: every "can it also do…" adds time, which is why we fix scope up front. The third is approvals, a system that places real orders or moves money needs more testing and sign-off than a draft a human checks.

How to keep it fast

Start with one specific, countable task rather than a grand platform. Pick something where the data is reasonably clean and the stakes are forgiving. Get it live, prove the payback, then expand. This is the whole logic behind how we approach AI implementation: small, specific, live in weeks, then build on what works.

The fastest projects aren’t the ones with more people on them. They’re the ones scoped tightly enough to finish.

Want a realistic timeline for your situation? The free AI audit comes back with the systems worth building first and roughly what each takes to ship.