Method
The Value-Led AI Method
Almost everyone starts from the tool. We start from the value the business needs, work back to what has to change, and buy the tool last.
01
Weeks 1 to 2
Assess
Where you are now, before anyone designs anything.
- What has already been rolled out, and what came of it
- The structures, tools, systems and data you have today
- What is already in flight, and what it is costing
- Where the governance and decision rights actually sit
02
Weeks 2 to 7
Direction
The stage that decides whether the rest is worth doing.
Ask
Where does the business need to get to, and why is it not there? Not where could AI help, which is the bottom-up question in a suit.
Clean Sheet
If you were designing this service today, knowing what AI can do, how would you run it? Whole journey, end to end, cross-functional people in the room together.
Case
The value cases that fall out of it, sized. The business case. The roadmap. One argument an investment committee can sign, not forty small ones.
- Sessions with sales, marketing, HR, finance, operations and shared services
- The transformation programmes already running, and what AI changes about them
- The product or service itself, and what customers will expect next
- Cost to take out, revenue to add, and capacity freed up
03
Runs alongside
Foundations
Build the skeleton once, so use case two costs a fraction of use case one.
- Gap analysis against what Direction says you need
- Buy or build, decided by your size and sector
- Tool stack, data, security, orchestration and monitoring
- The operating model during the change, and after it
04
Three-week cycles
Labs
Ship against the roadmap the business already agreed to.
- One prioritised value case per lab, running by the end of it
- Redesign the process, do not automate the old one
- Change management with the teams whose work changes
- Track the value against the case, through to delivery
What changes
Four things, together.
Change one and the value leaks out of the other three. New tools on old processes give you a faster version of the wrong thing.
AI value
creation
People
- Build an AI-native mindset
- Build capability in the teams you have
- Build new teams where you need them
- Define the new roles and responsibilities
Technology
- Enterprise architecture built for AI
- The AI tool stack, which looks nothing like the last one
- Data security and privacy
- Laid over the systems you already run
Governance
- Who approves what, and risk tiering
- Monitoring and observability
- A record of what the AI did and why
- The EU AI Act and GDPR
Process
- Business processes redesigned around AI
- Not the old process with a tool added
- Work that was queued or re-keyed, removed
- Decisions made where the work happens
Hover a part to see what changes. All four have to change together.
How we work with you
Fractional Chief AI Officer
An operator inside the business, accountable for the value creation plan and for delivering it. Days per month, for as long as it takes.
AI Operating Partner, portfolio-wide
Prioritisation across the book, shared playbooks and benchmarks, then delivery company by company. Several businesses at once.
Value discovery and business case
Fixed scope. Discovery, target operating model, stack, cost and sized value. Ready for an investment committee.