AI Consulting · Framework

The AI Delivery
Framework

A four-step approach for taking AI from pilot to production, used across startups, scaleups and large enterprises.

Four ascending steps drawn as a blueprint
The Approach

Four steps from
pilot to production.

The sequence matters as much as the steps. Skip one and the results don't hold.

01
Assess Readiness

Check the foundation before choosing a tool: data quality and access, how well the target workflows are understood, team AI literacy and leadership alignment. Most organisations discover the real constraint is not the model.

02
Prioritise Use Cases

Rank opportunities by business value and feasibility, and pick the ones that can reach production. The most impressive demo is rarely the right first project.

03
Design the Operating Model

Define who owns the AI capability, where humans review or approve, how success is measured and how the workflow changes, all before anything is built.

04
Build and Scale

Build against a system designed to receive it, measure outcomes in business terms, then extend what works. The goal is a capability your team keeps after the engagement ends.

Why It Works

Built for real organisations,
not case studies.

Built by a practitioner
Shaped by shipping AI agents into production and leading a GenAI build-vs-buy decision, not by reading about them.
Calibrated to your stage
A 20-person startup and a 10,000-person enterprise need different depth. The framework adapts; the sequence stays the same.
Business outcomes first
Success is defined in business terms before the build starts: hours saved, cost per run, adoption, revenue.
Built for execution
Every finding comes with an owner, a priority and a next step. No slide-deck-only outcomes.
Apply the Framework

Find out where your
AI initiative is stuck.

The depth changes with your size and stage. The sequence never does.