MS Advisory
Selected work

Governance that holds, in programmes and in AI.

Work where clear ownership, decisions and controls changed the outcome. Client names are withheld.

AI adoption

AI put to work in real businesses.

UK service SME

An owner upskilled to bring AI into 8 areas of operations

8 areas of operations1 source of truth

The situation

Most operational knowledge sat with the owner, so every question on policy, pricing or an unusual case waited for one person.

What I did

Upskilled the owner and built their autonomy to automate 8 areas of business operations, working from one source of truth with one rule: people decide, AI drafts.

The result

The owner now runs and extends the automation independently, and the team gets reliable answers on the spot without waiting for them.

Tech start-up

Fast MVP roll-outs with consistent governance, ready to hand over

Brief before codeStandards that keep improving

The situation

A tech start-up needed to roll out MVPs fast, but safely and with full documentation, so a technical team could take each one over without starting again.

What I did

Set up one governed process for building with AI across every project: a brief before any code, requirements and documentation templates, a decision log and a handover after each session. Lessons from every session feed back into the standards.

The result

Each MVP is ready to hand over with complete requirements, technical documentation and a decision log, and every new project starts from better standards than the last.

Programme delivery

The track record behind the AI work.

Advanced manufacturing

From threatened termination to client acceptance

113 days£2.5m programme

The situation

An enterprise software programme for an advanced manufacturing client was under threat of termination.

What I did

Took over the programme and re-baselined scope and milestones.

The result

Client acceptance at the go/no-go decision, 113 days after taking over.

Advanced engineering

One regulated release across vendor, partner and client

3 organisations£300k+ commercials

The situation

A regulated release had to land across three organisations: a software vendor, a delivery partner and a global advanced engineering client.

What I did

Designed one shared release model across all three.

The result

The deadline was met despite late changes, more than £300k of commercials stayed under control and the client extended the work.

Automotive scale-up

From undefined scope to a costed, governed plan

5 weeks7 workstreams

The situation

An automotive scale-up needed to mobilise phase 2, starting from undefined scope.

What I did

Sequenced seven workstreams around one critical path, with the resource model, commercials and governance in place.

The result

A costed, governed plan ready to mobilise in five weeks.

The same discipline,applied to AI.

Where is AI creating risk or rework for you today?

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