What the sprint does
The AI Workflow Sprint takes one visible bottleneck and tests whether AI can improve it under clear data boundaries and human review. It is designed to produce a decision, not an open-ended pilot.
- Map the current workflow and baseline.
- Classify data sensitivity and approval boundaries.
- Build or design one AI-assisted workflow.
- Train the people involved.
- Produce a decision note with ROI assumptions and next steps.
Good-fit workflows
The best candidates happen often, waste time, involve repeated documents or knowledge lookup, and have an owner who can decide whether the result is useful.
- Document intake, classification and routing.
- Policy or procedure retrieval.
- Compliance evidence pack preparation.
- Client or adviser response drafting under review.
- Meeting, case or complaint timeline summarisation.
Decision after the sprint
The final decision is deliberately simple: scale, improve, pause or stop. That protects the buyer from drifting into vague transformation work before evidence exists.
- Scale if value and controls are clear.
- Improve if the workflow is promising but needs refinement.
- Pause if data, ownership or review controls are not ready.
- Stop if AI does not improve the work enough to justify attention.