Hub / AI strategy
Templates, guides and insights for businesses deciding what to do with AI: how ready you are, where the opportunities sit, which come first, and how to run a pilot that reaches production.
The model
Four tiers of AI opportunity, sorted by how long each takes to reach production.
The method
How to compare any two AI ideas like for like, and why the room should correct the scores.
Guide
The decision behind every AI opportunity, and when waiting is the right answer.
Guide
What separates a pilot that becomes a system from one that becomes a demo.
Free templates drawn from CONVERGE, each with an editable download. Used in order, they take you from "should we use AI?" to a first pilot.
Word checklist
Twelve yes-or-no questions for a leadership team, and the first move each "no" points to.
Worksheet
Place every AI idea by time to deploy, and add a data position to each.
Spreadsheet
Score every idea on the same ten elements, and rank them by readiness as well as value.
Word template
The number, the scope, the owner, the escalation and the stop condition, and the five gates to production.
Everything on this hub is drawn from CONVERGE, the first book in our series. It sets out the Converge Methodology in full: the four levels of AI, the Opportunity Pyramid, data readiness, and the five phases that take a business from first conversation to a funded roadmap.
Publishing 7 December 2026.
Most businesses bring in outside help at some point. These guides set out what to expect and what to ask, whoever you choose.
The lessons from two decades of enterprise solutions, integrations and commerce builds turn out to be the lessons that decide whether an AI system reaches production. Five of them.
From a York base, working with manufacturers, food and drink producers, publishers and agencies across the county: the patterns in how Yorkshire businesses are approaching AI, and where the quickest wins are.
Readiness is not a maturity score; it is a set of specific conditions that decide whether an AI programme delivers in the first quarter or stalls in the second. Twelve questions a leadership team can answer in an hour.
Food and drink businesses carry the manufacturer's problems and the consumer brand's at once. The AI opportunities that follow, and why the data audit comes before the forecasting model.
Retail was early to AI and most retailers still think of it as the customer-facing bot. The faster returns are elsewhere: product content, segmentation, service assistants grounded in the systems of record, and forecasting once the data is pooled.
A magazine publisher's AI opportunities split cleanly in two: the digital platforms, where the work is data and personalisation, and the print-led workflows, where it is production and archive. Treating them as one programme fails both.
We run the Converge Methodology with your teams: from awareness and discovery to a prioritised roadmap and a first pilot.