If the last chapter was about getting your engine in order, this one is about bolting on AI and knowing exactly when to put your foot down.

Here, I walk you through the design process step-by-step: how to choose the right AI tools for your context, how to integrate them into your existing frameworks without losing the rigour, and how to make sure the tech serves the insight, not the other way round. We’ll talk about data pipelines, predictive analytics, and dynamic benchmarking, but always in the service of the client conversation, not as a distraction from it.

I’ll share the lessons I’ve learnt building AI-enhanced assessments that don’t just spit out a report, but generate living roadmaps, tools that evolve with the business, flag risks before they bite, and help clients act in the moment. Because when the system can learn, adapt, and guide in real time, the role of the consultant changes too, you’re delivering insight but along with capability.

By the end of this chapter, you’ll have a clear, practical framework for bringing AI into your maturity assessments in a way that’s both scalable and deeply human.

Next up: Chapter 5, a guided tour of how the big consulting firms do it. From McKinsey to Bain to BCG, we’ll look at the tools they’ve built, the way they deploy them, and what you can learn to sharpen your own edge.