We ran our method on ourselves. Here is the map.

The problem we shared with our clients

Every regulated firm now has an AI mandate, and most have a budget to match. What almost none have is a method for deciding where the AI should actually go. The result tends to be one of two failure modes: paralysis, or automating whatever a vendor demo made look easy.

We had the same problem in miniature. A founder-led startup, eight marketing channels, competitor and regulatory news to monitor, content to draft, publish, measure and learn from, and a founder whose highest-value hours belong to clients and product. Run manually, that is roughly a 40 hour week of marketing work. A marketing suite at around £3,000 per month would have imposed someone else's processes on us. Handing everything to AI would have put a language model in charge of our voice and our credibility. Somewhere in the middle was a set of right answers, and we needed a way to find them that would stand up to scrutiny.

Stage one: map how the work actually happens

We mapped our marketing the way we map a client's operations: by sitting with the work itself. Seven high-level processes emerged, from intelligence and research through content, publishing, engagement and performance. Each expanded into detail; the performance process alone held 11 distinct nodes once it was drawn in full.

The value showed up immediately in the nodes nobody would have listed from memory: stamping the live URL of a published post so its performance can be measured later; the first hour after posting, when replies drive reach more than the post itself does; triaging connection requests so warm interest is answered while it is still warm. None of these appear on a marketing suite's feature list. All of them turned out to matter.

Stage two: score every step, then decide deliberately

Every node was scored on a lens simple enough to survive contact with a board: how much judgement does this step need, how repeatable is it, what is the impact if it goes wrong, and is there data to verify it against? Four verdicts came out of the scoring. An extract from the register:

The counterintuitive rows are the point. The scoring did more than tell us what we could automate. It told us what we should not, and for a regulated firm that second list is the one the board needs most.

Three of our first-pass scores changed on contact with reality, and the case study names them. A method that never revises its own scores is a method that has stopped looking.

What this means beyond marketing

Marketing was simply the process we could publish, because it is our own. Swap the word for client onboarding, fund launches, breach reporting or board MI and the questions are identical: where does AI belong in this process, what must stay human, and how do you evidence the decision? That is what a four-week engagement answers, and the method is published in full.