You have the technical answer. The architecture is sound, the delivery plan is credible and the team can stand up the pipeline.
Then the bank or insurer scores you down on a question the architecture can’t answer: do these people understand how our business runs? If you’ve sat through that debrief, you know it.
AI has made the first half of that gap cheaper to close. It’s currently doing nothing for the second. This is our read of the market for the people who lead financial services (FS) and insurance consultancies.
What AI made cheaper
Building. Standing up a data pipeline, writing the code and producing a first model all take less time and fewer people than they did, and clients know it. That changes what they will pay a premium for – and it also changes what a consultancy has to show at bid stage, because the buildable part no longer separates one bidder from the next.
Any bench of capable engineers can now show a client a working prototype. The consultancy that wins is the one whose people can explain why that prototype will (or won’t) survive contact with the client’s business.
What AI didn’t make cheaper
Deciding what should change, and what good looks like in a particular industry. In FS and insurance that judgment is concrete. It means knowing which controls a change will touch, which parts of the operating model are fixed by regulation and which are habit, and what a credible sequence looks like for a firm running legacy platforms.
Regulators haven’t taken that decision away from people. The Financial Conduct Authority (FCA) says it does not plan to introduce extra regulations for AI and will rely on existing frameworks, and that its rules emphasise accountability for senior managers. Someone senior at the client still owns the outcome. The consultancy advising them needs someone who can talk to that accountability in the client’s own terms.
Who is the scarce profile?
The senior generalist: the enterprise architect, the transformation lead, the delivery director. They understand an operating model well enough to redesign it, not just build against it. They rarely describe themselves as AI specialists, and a CV search for AI skills won’t surface them.
Many consultancies try to cover the gap with a bench of specialists. A bench of specialists can build, but it seldom contains the person who says an approach will not get through the risk committee, or that a controls team will want to see the design before the build starts.
What does this mean for bids?
In our view, the answer is to name the person who has done it, and put them in the room early. An architect with a track record in the client’s kind of firm carries more weight than the same bid with a strong generic bench and a generic summary of experience. A specialist added in Week 3 of a programme can’t repair a weak answer given in Week 1.
It also means saying no more often. Some mandates need a profile you don’t have and cannot credibly name before the deadline. Bidding on those costs time you could spend on mandates you can win.
How do you test your own bench?
Start with three questions:
- Who on your bench has run this kind of change inside an FS or insurance firm, rather than advised on it from outside?
- Could they answer a controls or risk question in the first ten minutes of a client meeting, without a briefing note?
- If a client asked tomorrow for a named lead on the next programme, who would you name, and how quickly could they start?
What about once you’ve won?
The same gap shows up after the contract is signed. Halfway through, the client asks how a change would run through underwriting, or what the conduct risk team will accept, and nobody on the team can answer. Finding a subject matter expert (SME) at that point costs weeks you don’t have.
Know before you bid which SMEs you can reach and how fast. If the answer is “we’d have to find one”, price that into the plan.
Where SR2 Consulting fits
SR2 Consulting is a delivery partner and SME network for consultancies. We’ve supplied AI and data engineering resource to a specialist data and AI consultancy on private equity (PE) backed portfolio AI value creation work, and we support consultancies with pre-bid and request for proposal (RFP) work on regulated private sector mandates.
If this matches a bid or programme on your desk, Jack Hollocks, Head of Private Sector Consulting, and the team are happy to talk it through.
