AI Workflow Sprint

Two weeks. One workflow. A decision your team can trust.

A contained route from AI interest to evidence: choose one workflow, govern the boundary, test with real work, train the people involved, and decide what to do next.

Book a sprint fit check Review governance controls

What it produces

A practical answer, not a vague pilot.

The sprint is designed for teams that need evidence before scaling AI. The output is a clear recommendation: scale, improve, pause, or stop.

Current-state workflow map and baseline
One AI-assisted prototype or operating model
Data-boundary and human-review controls
Procurement, vendor-risk or IT/security notes where they matter
Staff enablement session for the people doing the work
Decision note with ROI assumptions and next steps

Delivery cadence

Ten working days with visible gates.

Day 0

Fit check, scope boundary, artefact list, meeting schedule and client responsibilities.

Day 1

Workflow and baseline: capture volumes, time, rework, exceptions and decision points.

Days 2-3

Data and governance: classify sample documents, define permissions and review rules.

Days 4-6

Prototype or assisted workflow: search, summarisation, drafting, classification or evidence-pack assembly.

Day 7

User test with staff: capture errors, edge cases and adoption friction.

Days 8-9

Improve and document the workflow, controls, limitations and ROI assumptions.

Day 10

Readout: scale, improve, pause, or stop based on evidence from the work.

A sprint is only useful when the conditions are real.

The fit check exists to protect both sides. If the workflow is too vague, the data is not available, or the team cannot name a useful measure, we recommend a smaller first step.

A named workflow owner is available.
Representative sample data or documents can be used safely.
The work happens often enough for improvement to matter.
Human review remains explicit for sensitive or regulated decisions.
The buyer can name the measure that would make the sprint worthwhile.
The approval route is known if IT, security, compliance, legal or procurement need to be involved.

Decision frame

Know when to sprint and when to prepare the ground.

When to run it

Run a sprint when the work is specific enough to inspect and the team can make time for a contained test.

One workflow is visible and repeated enough to matter.
A process owner can judge whether the output is useful.
Sample material can be used safely, redacted, or replaced with synthetic examples.
A time, quality, risk, or service measure can be recorded before the sprint starts.

Start smaller when

Choose a fit check, governance session, or data-boundary exercise first when the foundations are not ready.

The team cannot yet name a workflow owner or decision sponsor.
Sensitive data would need to be shared before a safe route is agreed.
The desired outcome involves autonomous regulated judgement.
The buyer wants a free audit report, guaranteed ROI or production agent before evidence exists.
Staff need basic AI-use rules before testing anything live.

Check the data boundary first

Next step

Have one workflow worth pressure-testing?

Book a short fit check and we will pressure-test whether AI can genuinely help, what data is safe to use, and who needs to be involved.

Book a 20-minute Fit Check