What should I look for when choosing an AI implementation partner for a 200-person company?
Look for a partner that builds working systems rather than only advising, that puts senior people on your account from scoping through handover, that starts with your data and processes instead of a tool they resell, and that can show you a comparable system running at a business your size. Then check how they define "done" and who runs the system after they leave.
By Cade Dannels, Founder, Daita Dynamics. Updated .
Why a 200-person company is a tricky size to buy for
At 200 people you are too big for a freelancer to handle every system and too small to absorb the overhead of a large consulting program. You have real data, several departments with their own tools, and enough repetitive work that automation pays off quickly. You also have no spare team to babysit a fragile build. The right partner for you is one that has delivered at this scale before and can say, in plain terms, what it shipped and what it took.
Do they build, or only advise?
Ask for a walk-through of a system they built, not a strategy deck they wrote. Advice is useful, but a roadmap that nobody implements is a very expensive PDF. A partner that both scopes and builds has to live with its own recommendations, which keeps the recommendations honest. If the firm advises and then hands the build to someone else, find out who that someone is, because that is who you are really hiring.
Who actually does the work?
The people in the sales conversation are not always the people who build. Ask directly:
- Who will scope the work, and will that person also build it?
- How many years has the lead builder spent shipping systems like this one?
- If the lead leaves the engagement, who takes over and how is the knowledge preserved?
At a 200-person company you cannot afford three layers between you and the engineer. A partner where senior practitioners do the work themselves will be faster and will catch problems a junior team would miss.
Do they start with your data or with a tool?
Most disappointing AI projects start with a product decision: "we are going to roll out this assistant" or "we are going to buy this platform." Good projects start with a process. Which task eats the most hours? Where does the information for that task live today? How clean is it? A partner that asks to see your spreadsheets, your inbox, and your existing systems before proposing anything is working from evidence. One that leads with a tool they resell is working from a commission.
How do they scope and price?
You do not need a fixed price on day one, but you do need to understand what drives the number. Reasonable drivers are the number of systems to integrate, the state of your data, whether anything needs to be custom versus configured, compliance requirements, and how much ongoing operation the partner will handle. Be wary of quotes that arrive before anyone has looked at your workflows. Be equally wary of open-ended hourly engagements with no defined deliverable.
What does "done" look like?
Ask the partner to define, in one sentence, what will be true when the project is finished. Good answers sound like: "Month-end reporting for your clients runs in an afternoon instead of three days, and your controller owns the process." Bad answers sound like: "You will have an AI foundation to build on." Insist on a measurable outcome tied to a task your team does today.
Who runs it after they leave?
A system that only the vendor understands is a liability. Ask how the handover works, what documentation you get, who in your company will be trained, and what support looks like in month six. The best partners design for the day they are no longer needed and teach your team to run and extend what was built.
Red flags
- A proposal that arrives before anyone has seen your actual workflows.
- Every answer routes back to one platform the partner happens to sell.
- No named individual will commit to being on your project from start to finish.
- No reference at a business within a few times your size.
- "AI transformation" appears in the pitch but no specific task in your business does.
- Ownership of the code, prompts, and data pipelines is unclear or stays with the vendor.
A ten-question scorecard
Score each partner from one to five on these, and let the total guide the shortlist:
- Can they show a working system they built for a company like ours?
- Will the person who scopes the work also build it?
- Did they ask to see our data and processes before proposing?
- Is the outcome defined as a change to a task we do today?
- Do we understand what drives their price?
- Do we own everything they build?
- Is there a clear handover and training plan?
- Can they explain the approach without jargon?
- Are they willing to say what they would not automate?
- Do we want to work with these specific people for six months?
Where Daita Dynamics fits
Daita Dynamics is a Denver-based AI strategy and implementation firm founded in 2024, working remotely with growing businesses across the United States. We sit between the large consultancies and the single-person consultants: senior practitioners scope the work, build it, and teach your team to run it. We start every engagement with a free AI Opportunity Assessment of your actual workflows, and we will tell you if the honest answer is that you do not need us yet.
Frequently asked questions
- How long should partner selection take?
Two to four weeks is plenty for a 200-person company. Longer than that usually means the buying committee has not agreed on which problem to solve first, and no partner can fix that for you.
- Should we run a paid pilot before committing?
Yes, if the pilot has a defined outcome and a short timeline. A pilot that automates one real task in a few weeks tells you more about a partner than any proposal. Avoid pilots that are really discounted strategy work.
- Do we need an AI strategy before choosing a partner?
No. A good partner will produce the strategy as part of scoping, grounded in your workflows. Buying a standalone strategy first often produces a plan the eventual builder has to redo.
- Should the partner be local?
Not necessarily. Most implementation work happens remotely and in your systems. What matters is responsiveness, time-zone overlap for working sessions, and whether the people you met are the people doing the work.