• SELECTED WORK
Real projects. Quiet transformation.
A selection of engagements where AI adoption, workflow redesign, and operational clarity made a measurable difference — without the disruption.
• ENGAGEMENTS
How I typically work with organisations
AI adoption strategy
Helping leadership teams move from interest to a clear, staged adoption plan — scoped to real workflows, not theoretical use cases.
Workflow redesign
Mapping existing processes, identifying where AI adds value, and redesigning workflows so the technology actually gets used.
Operating model design
Building the structures, roles, and decision frameworks that let AI tools function inside a real organisation.
• CASE NOTES
Selected engagements
Financial services firm
Turning a stalled AI pilot into a working content workflow
A mid-size financial services team had invested in an AI writing tool but adoption had flatlined after three months. I mapped the existing content process, identified where the tool was being asked to do work it wasn’t designed for, and redesigned the brief-to-publish workflow around it. Within eight weeks, output had doubled and the team stopped treating the tool as a threat.
Why most teams get wrong about AI adoption →
B2B SaaS company
Designing an operating model for AI-assisted customer success
The CS team was using four different AI tools with no shared framework. I ran a workflow audit, consolidated to two core tools with clear roles, and designed an operating model that gave the team shared language, escalation paths, and quality standards. Churn dropped and response quality became measurably more consistent.
The difference between an AI pilot and an operating model →
Professional services consultancy
Building a content system that scales with the practice
A growing consultancy was producing thought leadership manually — each piece took two weeks and required partner sign-off at every stage. I redesigned their content system: templated structures, AI-assisted first drafts, streamlined review gates. They now publish weekly with less effort and more consistency.
Content systems are organisational systems →
• OUTCOMES
What changes after we work together
Faster adoption
Teams using AI tools within weeks, not quarters
Clearer workflows
Processes designed around the technology, not bolted on
Measurable output
Concrete improvements in speed, quality, or consistency
Lasting structures
Operating models that survive beyond the initial engagement
• PROCESS
A typical engagement
01.
Discovery
Understanding your current workflows, tools, and team dynamics before recommending anything.
02.
Mapping
Documenting what actually happens — not what the org chart says should happen.
03.
Design
Redesigning workflows, briefs, and operating structures around where AI genuinely helps.
04.
Embedding
Working alongside your team until the new way of working is the default, not the experiment.
Every engagement starts with a conversation about what’s actually happening.
Ready to talk about what AI could change for your team?
No pitch deck. No pressure. Just a clear conversation about where you are and what might be worth trying.