A 90-day roadmap to choose a use case, build a workflow, measure it against a baseline, and decide with evidence whether it should scale without improvisation.
Days 1–15: find a friction point that matters
The team maps recurring tasks, time, volume, quality, errors, data, systems, and responsibilities. It then prioritizes a problem that is valuable, observable, and sufficiently focused. Summarizing monthly reports, structuring briefs, or qualifying inquiries may be a better start than building a general-purpose agent for the entire company. The baseline records how things work today and what must not get worse. Without a starting point, any demo will seem fast and any result will be difficult to defend.
Ninety days are enough to turn a priority friction point into an informed decision, not to transform an entire company. The right roadmap documents the current process, chooses a bounded case, defines a baseline and controls, builds with real users, evaluates quality and adoption and ends with an explicit decision: scale, correct or stop.
Days 16–30: design the workflow and its limits
Define inputs, steps, sources, outputs, users, owners, human decisions, exceptions and metrics. Security and legal review data and providers according to the case's risk. The team selects representative examples and agrees on a rubric before building. It also establishes which part remains manual during the pilot. Architecture can be simple; definitions must be precise.
Days 31–60: build alongside the people doing the work
The prototype is tested with real users within a controlled scope. Each iteration examines where context is missing, which steps cause rework, and what exceptions arise. Instructions, templates, and integrations are versioned. The team avoids automating stages it does not yet understand and keeps a manual route available. The aim is not to maximize features, but to make one complete journey produce a usable, traceable output.
Days 61–75: compare against the baseline
Evaluation reviews total time, quality, corrections, adoption, failures, operating cost, and the experience of the people involved. A speed improvement that multiplies reviews may not create real capacity. Adverse cases and the pause mechanism are tested too. Results are separated by task and user type so an average cannot hide a critical failure.
Days 76–90: decide and turn learning into a system
The conclusion is not a pilot presentation, but an evidence-based decision. If it scales, support, an owner, budget, training, controls and a next cohort are assigned. If it needs adjustments, the team specifies exactly which hypothesis remains untested. If it stops, the reasons and lessons are documented. In every case, the process leaves reusable assets: a map, test dataset, rubric, policy and criteria for choosing the next case.
90 days, with decisions before scaling
This roadmap is an adaptable proposal. The days are planning windows, not a guaranteed commercial timeline.
| Window | Deliverable | Decision |
|---|---|---|
| Days 1–15 | Process, owner, and starting point | Do we have data and a priority problem? |
| Days 16–30 | Prototype, evaluation, and permissions | Does it meet minimum quality criteria? |
| Days 31–60 | Supervised pilot and error logging | Does it add value over the current process? |
| Days 61–90 | An adoption, support, and follow-up plan | Scale, correct, or stop? |
Dependencies: access, authorized data, validators, and budget. Document each phase's exit criteria before starting.
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