AI Work Sprint
Change the work, not just the tool
A focused four-to-six-week engagement for a team that is already using AI, or knows it should be, but has not translated that into measurable business improvement. We choose a small number of real workflows, establish how they work today, redesign them around people and AI, implement what is practical and measure what changed.
Your people use AI every day. Has the work changed?
Many teams using AI have added a tool to the old way of working. Drafting gets quicker, while the hand-offs, the checking, the decisions and the measures stay as they were, so the business sees a fraction of the benefit.
The sprint works on three representative workflows with one team. We establish how each one works today and what it costs in time and quality, redesign it around what people and AI each do well, put the practical changes in place and measure the difference against the baseline.
Where a workflow needs more than configuration, the sprint ends with a scoped recommendation for the build, so the larger investment rests on evidence from the team's own work.
How a sprint runs
Five phases, one team, three workflows
Four to six weeks from the baseline to the evidence.
Baseline
Map how each workflow runs today and record the time, quality, cost and hand-offs before anything changes.
Redesign
Redesign each workflow around people and AI: what AI prepares, what people check, what people decide and where the review points sit.
Implement
Put the practical changes in place, in the tools the team already uses where possible, with configuration or small additions where they are needed.
Enable
Build the team’s capability through its own work, with the manager alongside, instead of sending people on a generic AI course.
Prove
Measure the redesigned workflows against the baseline, separate what has been shown from what still needs evidence and recommend what to do next.
Enable
Capability built through the work
The team learns to delegate to AI, review what it produces, recognise when it should not decide, work with agents and keep a person accountable for the result, all inside its own workflows.
Use
Get reliable results from the tools the team already has.
Judge
Check AI output against its sources and know when it should not decide.
Design
Redesign a workflow around what people and AI each do well.
Delegate
Hand work to AI and agents with clear instructions and limits, and a named person accountable.
Who this is built for
- Operations leaders and managing directors whose people use AI but whose results have not moved
- A team with repeated, information-heavy work such as client updates, proposals, reporting, case handling or account management
- Businesses that have finished an AI Work Review or Discovery and want to act on it
- Leaders who want capability built inside the team rather than another training course
What you receive
- The current workflow for each of the three, with a baseline of time, quality and cost
- The redesigned workflow, with a responsibility model: what AI does, what people check and what people decide
- Working capability or configuration where appropriate, in the tools you already use or a small addition to them
- Process changes and team guidance, with the governance and review points agreed
- Before-and-after evidence for each workflow
- Recommendations for the next opportunities, including anything that needs a build
How engagements run
Four to six weeks with one team, in five phases: baseline, redesign, implement, enable and prove. A named lead runs the sprint with the team's manager, and progress is reviewed every week.
Typical investment
Fixed scope, fixed price
Know what the answer costs before we start. All figures ex VAT; the final fixed fee is confirmed after scoping.
- One team, three workflows
- from £7,500
- Larger teams, more workflows or deeper technical implementation
- scoped separately
What we need from you
- One team, its manager and time set aside to work on three real workflows
- Access to the tools, systems and data those workflows use
- Someone who can approve changes to how the team works
Scope and boundaries
- Team size, the number of workflows and the amount of technical implementation set the price. Not every sprint costs £7,500.
- It is not a generic AI training course. Capability is built through the team's own work.
- Software licences and new platforms are separate, and are only recommended where the evidence supports them.
- A production build that goes beyond configuration is scoped separately, usually as Build & Productionise.
Before you commit
Questions before you commit
How is this different from the AI Work Review?
The review finds the workflows worth changing, in a 90-minute session and a written readout. The sprint changes three of them with one team and measures the result.
Do we need to buy new software?
Usually not to start. Most sprints use the tools the team already has. Where something new would make a real difference, we say so, with the cost and the alternatives, and there is no resale margin behind the recommendation.
What happens after the sprint?
You keep the redesigned workflows, the guidance and the evidence. The next step might be another team, a build for a workflow that needs one, or nothing more from us.
Is this AI training?
No. The team learns by redesigning and running its own workflows: how to delegate work to AI, check what it produces and keep a person accountable. There is no classroom course.
How do you measure AI adoption and ROI?
Each workflow is baselined before anything changes: time taken, quality, rework and cost. The same measures are taken after the change, and anything not yet shown is marked as such. No return is promised in advance.
Does it work with Microsoft Copilot or ChatGPT?
Yes. Most sprints start with the tools a team already has, such as Microsoft 365 Copilot or ChatGPT, and only recommend something new where the evidence supports it.
What you get
Illustrative example, not client data. The real thing carries your evidence and your numbers.
TechGuidr
Sample extractAn extract from a sprint results note
- Workflow
- Weekly client update, assembled by account managers
- Baseline
- Time per update and corrections after review, recorded for two weeks before any change
- Redesign
- AI drafts from the CRM and shared files; the account manager checks the figures and the tone, then sends
- Stays with people
- What the client needs to hear, every figure and the decision to send
- Result
- Measured against the baseline over four weeks, with anything not yet shown marked as such
Illustrative example, not client data. The real document carries your evidence and your numbers.
TechGuidr product
Relevant work
CommercialIQ brought portfolio diagnostics and proposed actions into an account team's daily workflow. AI prepares each recommendation with its reasoning, a person accepts or rejects it, and every accepted action has an owner and a date.
Read the case studyThe route
Other services
Every engagement sits on the route from an idea to a working system. Start wherever you are.
Recognise the situation?
Two or three sentences is enough. You will get an honest view of whether and how we can help.