AI Adoption Specialist for Insurance & Financial Services
88% of companies use AI. Only 6% see the value.
That gap is adoption, not access, and it's a change problem, not a technology one. I close it in 90 days: diagnose, design the change strategy, deliver it, track & evolve, until it sticks.
25 years leading change and transformation for insurance & financial services, including Swiss Re, Zurich Insurance Group, PartnerRe and Galytix.
The AI adoption gap
Most companies have the technology. Almost none have the adoption.
AI adoption is a change problem, not a technology one, and it's solvable in 90 days.
88% of organisations now use AI, but only 6% have achieved significant enterprise-level EBIT impact from it. The gap is adoption, not access.
Fewer than a third of companies have upskilled even a quarter of their workforce to use AI, and initiatives without active sponsorship are roughly three times less likely to meet their objectives.
The AI Adoption Accelerator closes that gap: diagnose, design the change strategy, deliver it, track & evolve, to realise the value the investment was meant to create.
88%
of organisations use AI in at least one business function
6%
have achieved significant enterprise-level EBIT impact from it
McKinsey, "Capturing Central Europe's AI Opportunity", June 2026, citing "The State of AI in 2025" (n=1,993, 105 countries) · BCG, "Closing the AI Impact Gap", 2025
See the full picture
The real problem
Fewer than a third of companies have upskilled even a quarter of their workforce to use AI.
And initiatives without active sponsorship are roughly three times less likely to meet their objectives. Technology was never the hard part.
What I do
AI Adoption Accelerator
The offer
A 90-day acceleration programme for insurers
Diagnose, design, deliver, then track and evolve, built around sponsorship, workflow redesign and reinforcement, the three conditions that turn AI investment into adopted behaviour.
Explore the Accelerator
Free tool
AI Readiness Diagnostic
Twelve questions across the three pillars of adoption: sponsorship, workflow redesign and reinforcement. About five minutes, and you'll see exactly where your organisation stands.
A 90-day acceleration programme for insurance & financial services companies
A 90-day programme that turns AI investment into adopted behaviour, and value you can measure and realise.
The AI adoption gap
Most companies have the technology. Almost none have the adoption.
AI adoption is a change problem, not a technology one, and it's solvable in 90 days.
88% of organisations now use AI, but only 6% have achieved significant enterprise-level EBIT impact from it. The gap is adoption, not access.
Fewer than a third of companies have upskilled even a quarter of their workforce to use AI, and initiatives without active sponsorship are roughly three times less likely to meet their objectives.
The AI Adoption Accelerator closes that gap: diagnose, design the change strategy, deliver it, track & evolve, to realise the value the investment was meant to create.
88%
of organisations use AI in at least one business function
6%
have achieved significant enterprise-level EBIT impact from it
McKinsey, "Capturing Central Europe's AI Opportunity", June 2026, citing "The State of AI in 2025" (n=1,993, 105 countries) · BCG, "Closing the AI Impact Gap", 2025
Access looks healthy. Use doesn't. Here's what the drop-off looks like once a tool actually goes live.
Rollout
−52 pts
92%
Tool access
78%
Initial training
61%
First use
40%
Sustained use (technology alone)
Provisioned (has access)In use (where it breaks down)
Reading the gap
Access and training numbers look healthy on a dashboard. But leaders overestimate real usage by up to 3x. That 40% plateau is where the fix has to start.
Worklytics, citing Morgan Stanley & RSM, 2025
And it's not evenly spread. Here's what the people who never adopt at all say is holding them back.
Prefer their current way of working
46%
Ethically opposed to using AI
43%
Data privacy or security concerns
43%
Don't think AI can help with their work
39%
Tried AI, found it not useful
26%
Gallup, "AI in the Workplace: What Separates Adopters and Holdouts" (Feb 2026 survey, n=23,717 US employees), April 2026
Not because the platform fails. Because sponsorship fades after launch, the workflow never gets redesigned around the tool, or reinforcement stops once the project team moves on. That costs companies millions in wasted investment.
I've spent 25+ years leading change and transformation across insurance, technology and hospitality, and I've been a Prosci-certified Change Practitioner since 2015. I know how to close this gap.
Prosci, Best Practices in Change Management (updated 7 August 2026) · BCG, "AI at Work: Why Strategy Matters More Than Tools", 3 June 2026
The model
The AI Value Cycle
After go-live, adoption needs an ongoing loop of use, evidence and refinement, not a one-time rollout.
Sustained use is most likely when all three conditions hold together, not one at a time.
Sponsorship
A leader visibly uses AI, shares what they learn and encourages others to experiment.
Workflow Redesign
Build AI into the real workflow with the people doing the work, then revisit it as trust and technology evolve.
Reinforcement
Managers and champions protect practice and feedback as the technology evolves.
Experimentation lives under Reinforcement, supported by Sponsorship: it's the psychological safety a team needs, protected day to day by managers and champions as the technology evolves.
The business case
From technology-alone to target state
This is the 40% plateau from the funnel above, before workflow redesign and culture do their part.
Illustrative value bridge: index values, not currency. Priced next in the AI Value Calculator.
What closing the gap is worth
A reusable formula for pricing that 40-to-80 move, in your own numbers. Adjust the inputs, no need to take mine.
Illustrative: swap these five inputs for your own numbers before this becomes a business case, we'll do exactly that together in Diagnose.
A business case in your own numbers
The AI Value Calculator's formula above, run with your headcount, task time and day rate, not ours.
Improved adoption, and the value it unlocks
The business case is revisited at day 90 with real usage data, so you see value realised, not just projected.
Documented deliverables
Change strategy and training plan, an adoption measurement dashboard, champion activation materials, and a continuation plan for local teams after handover.
Adoption tracked and reported
From your technology-alone baseline to the programme's target state, using the AI Readiness Diagnostic and weekly usage data.
Support throughout
Direct access to Eri, regular check-ins, practical support for local teams, and the internal capability to carry the work forward after day 90.
The programme
Four phases, ninety days
Then monthly support if you want continuity.
1
Diagnose
Stakeholder diagnosis & baseline
Usage barriers & workflow gaps
Success measures by user group
Wks 1–2
→
2
Design
Change strategy & rollout plan
Training & communication plan
Manager & champion enablement
Wks 3–4
→
3
Deliver
Readiness activities & training
Champion activation & feedback
Practical support for local teams
Wks 5–10
→
4
Track & Evolve
Post-launch tracking & iteration
Continuation plan
Internal capability to carry it forward
Wks 11–12
After the 90 days
Clients who want continuity move to an ongoing monthly retainer, minimum six months.
Curious where you stand?
Take the free AI Readiness Diagnostic first
Twelve questions, a scored breakdown across the three pillars, and the one thing worth fixing first. About five minutes.
Before the Accelerator existed as its own offer, I worked as a contract Change Manager, placed through a staffing agency, on the UAT phase of a global insurance company's new AI underwriting platform.
The role
Change Manager during UAT for a multi-country AI underwriting rollout. Internal resource for change management, training and communications was limited. Product and technology teams were focused on building the solution.
What I did
Coordinated UAT testing across countries, built the stakeholder communications and training materials, and delivered the user demonstrations myself.
My own estimate
With change management involved, UAT completion reached around 80%. My own estimate, not a measured figure, is that it would have landed closer to 40% without it. I handed over change management to the internal resource after go-live with intensive supporting materials including the scaleup framework with communication and training templates.
~40%→~80%
My own estimate of UAT completion, with vs without dedicated change management. Not a measured post-launch adoption result and not delivered through the Accelerator.
Industry context: BCG found in March 2026 that just 38% of P&C insurers were generating value at scale from AI in core workflows, most citing people and process gaps rather than technology.
More about my background
Two ways this goes
The gap at the top of this page doesn't close on its own.
Without the Accelerator
Adoption stays wherever it is, without a structured push to change it.
You're not among the 6% of organisations achieving significant enterprise-level EBIT impact from AI.
Whatever value your numbers modelled stays modelled, never realised.
With the Accelerator
We work together towards the target state, moving adoption further within 90 days.
Value gets tracked and reported at day 90, not just projected.
You join the minority already turning AI investment into bottom-line impact.
Let's talk
Ready to fix your AI adoption challenge?
Start with the free diagnostic or go straight to a 25-minute strategy session.
Twenty-five-plus years leading change and transformation across insurance and financial services, in Switzerland and the UK, including roles at Swiss Re, PartnerRe, Zurich Insurance Group and Galytix.
That's included leading a five-person consulting team through global transformation across underwriting operations at Swiss Re, building a 100-plus-person champion network for a technology change programme at PartnerRe, and working on an AI-enabled claim classification project at Galytix. I've been a Prosci-certified Change Practitioner since 2015.
Since August 2025 I've worked as an AI Adoption Specialist through Design and Lead Change GmbH, diagnosing AI adoption readiness and designing change strategy for insurance and financial services clients, work that grew directly out of a contract Change Manager role on the UAT phase of a live AI underwriting platform for a global insurance company. Read more about that experience.
