“My experience with Philip felt like what I want a client to experience financial planning to be like. He was in control, asking the right questions and introducing the roadmap as we went along. You want the client to think: all I really need to do is turn up, provide the right information, and you'll take care of the rest.”
Demand wasn't the problem. Capacity was.
Christian Mather's LinkedIn content had done what most financial planning practices never manage: it created a waiting list. Three new clients a month and referrals arriving alongside inbound enquiries. Demand was still accelerating.
But almost everything behind that front end ran through Christian. Meeting notes, proposals, cashflow preparation, suitability drafts and follow-ups were sometimes taking three hours a day - time that should have been spent with clients. Onboarding was taking too long. There was no CRM, and client data was spread across multiple tools with no integrations between them.
This was a practice ripe for AI. But the question was where to start, in what order and how to build it so the practice owned the result rather than renting it?
Two parts: understand the practice, then sequence the fix
Diagnostic and discovery
Christian and his colleague Suzi Neal completed a detailed AI Transition Diagnostic together, scoring the practice across machine legibility, workflow and infrastructure, people and capacity, and governance. That gave us a baseline and showed where the gaps clustered.
We then ran three structured discovery sessions, tracing a client through all three phases of the business and examining the economics, the data environment and the compliance picture. Session 3 ended with three strategic moves agreed together.
The AI Transition Roadmap
The roadmap turned those three moves into a phased plan: a purpose-built CRM as the system of record, an automation layer built on top of it and a governance framework that makes both safe to run at scale.
Every phase came with specific deliverables, costs and timelines, plus a clear split between what the CRM vendor's onboarding team handles and what the build covers, so nothing gets paid for twice.
Diagnosed. Mapped. Revised.
The end result wasn’t a generic AI playbook, but a detailed plan built around one practice, one niche and one team - and changed when the client pushed back.
Scored on a diagnostic
Twelve questions across four dimensions, completed together by the leadership team rather than alone. The scores showed where the structural gaps sat and which ones mattered most. The final roadmap started exactly there.
Traced through the client journey
Rather than reviewing tools in isolation, we followed a client through every stage: the onboarding stages and various client-facing meetings. Each cause of delay was named and confirmed by the team, so the plan targets what actually slows things down.
Revised on feedback
The first draft led with a meeting automation. Christian's view was that the CRM is the practice's source of truth and should come first. He was right. Version 2 reordered the sequence, with the meeting notes pipeline built in parallel so the most painful problem still gets fixed early.
Choosing a CRM without the lock-in
Christian had seen first-hand, in previous businesses, how hard it can be to get data out of legacy adviser platforms. That concern shaped the selection criteria: the practice had to own its data in practice, not just in principle.
I evaluated the options, tested the shortlisted platform hands-on in its development sandbox and confirmed its data access position directly with the vendor's senior leadership. The recommendation was made independently, with no referral fee or commission involved.
- ✓ Client data can be extracted through an open API at any time, so the practice can always leave with it
- ✓ The same API carries every planned automation: meeting notes, digital forms, follow-ups and suitability drafting
- ✓ How the CRM sits alongside the network's case-file requirements
- ✓ Who does what between the vendor's onboarding team and the build, so no work is duplicated
- ✓ Minimum governance controls (approved tools, a named reviewer and a DPIA) in place before any client data flows
What One Day Wealth walked away with
A plan they can act on, with or without me
A sequenced roadmap with deliverables, costs and timelines for every phase. It's theirs to keep and designed to be actionable without further consultancy.
A system of record at the centre
One place for every client and prospect, from first LinkedIn conversation to annual review, replacing spreadsheets, scattered folders and memory.
The notes problem fixed early, not last
A meeting transcript pipeline built alongside the CRM setup, designed to turn three hours of manual extraction into a five-minute review.
A route to six-week onboarding
Digital data collection with automated reminders, a readiness tracker and automatic meeting booking, aimed squarely at the causes of delay the team confirmed.
Economics on real numbers
The roadmap sets out where costs come down and senior time comes back, with projections built on the practice's own figures rather than industry averages.
Governance that keeps pace with the build
Minimum controls before go-live, and a full AI governance policy developed alongside each phase rather than bolted on at the end.
Is your back office keeping up with your growth?
If demand is outrunning your capacity and you're not sure where AI fits or what to fix first, let's talk. I'll tell you honestly whether a roadmap is the right next step.
Let's TalkThis is the AI Transition Roadmap service in practice.