Use the first month to find the workflow, not the tool
A 200-person business is large enough to have meaningful process complexity and small enough that a bad AI rollout can distract leadership quickly. The RSM middle-market AI survey shows middle-market AI adoption gaining momentum, and the San Francisco Fed analysis of AI and small businesses shows the same pressure reaching smaller businesses. The first roadmap should turn that pressure into one controlled operating win.
In the first month, collect workflow candidates from sales, service, finance, operations, HR, and leadership reporting. Score each one on value, data readiness, review clarity, system access, risk, and adoption effort. Do not start with the tool list. Start with repeated work that already has a frustrated owner.
Use the AI project use-case scoring model to rank the options. The first workflow should be important enough to matter and narrow enough to launch without a company-wide transformation program.
Use the second month to design the controlled pilot
The OECD report on AI adoption by small and medium-sized enterprises is helpful for a 200-person business because it treats adoption as more than awareness or access. The company needs data readiness, skills, workflow ownership, and governance. The pilot design should specify approved sources, user roles, reviewer responsibilities, exception handling, training, and success measures.
The NIST AI Risk Management Framework gives the governance pattern: govern, map, measure, and manage. In practice, that means the pilot has an owner, a documented workflow, approved data access, a human review rule, and a measurement cadence before any automation touches production work.
Use the AI readiness assessment to identify gaps before launch. If the gaps are material, the roadmap should fix the workflow before adding more AI capability.
Use the third month to prove operating value
The Deloitte State of AI report reinforces that AI value comes from process change. In the third month, move one workflow into a governed production rhythm: weekly value review, user feedback, quality checks, adoption training, and a clear decision on expand, hold, or stop.
The Gartner agentic AI project forecast is relevant because agentic AI projects can fail when leaders cannot prove value, cost, data quality, or controls. A 200-person company should earn the right to scale by proving one workflow first.
The next step is the 90-day AI implementation plan. Use it to turn the roadmap into accountable workstreams, owners, controls, and production checks.
