case study
A bespoke, interactive AI Outcomes Maturity Model built for a UK gas energy retailer serving SME and Industrial & Commercial customers, mapping five maturity stages across business outcomes and enabling capabilities to shape a safe, governed AI roadmap.
Industry
Client Overview
Case Study Overview
We built a bespoke AI Outcomes Maturity Model for the client, covering the functions that matter most to a gas retailer — billing and revenue, customer service, supply chain, CoS and industry flows, credit risk, and the enabling capabilities that underpin them. The model assesses each function across five maturity stages from Reacting through to Autonomy, with drill-downs into the specific AI options and technology requirements to progress at each step.
the problem
Problem Statement
AI adoption in regulated energy retail sits at the intersection of operational value, regulatory exposure, and customer impact. Without a structured model, initiatives were being assessed individually and inconsistently, governance was reactive rather than designed-in, and leadership had no shared language to discuss what good looked like across the functional estate.
outcome
Results We Delivered
An overview of the outcomes we delivered
IT leadership now has a defensible, board-ready view of where AI can add value across the business, what the risks are, and what capabilities need to be built to unlock each stage. The model is being used to prioritise investment decisions, shape the AI Design Authority agenda, and frame regulatory conversations with confidence.
approach
Our Approach
An overview of the approach we took to deliver the results
We spent time with the client's IT leadership and functional SMEs to understand the operational estate, the regulatory context, and the AI initiatives already in flight. We then designed a five-stage maturity framework, populated each function with specific AI options and technology requirements grounded in gas retail reality, and delivered it as an interactive HTML model that the IT Director can use in briefings, strategy sessions, and investment reviews.
application
What We Did
The specifics over what we performed and how we delivered the results
Five-stage maturity framework
Reacting, Running, Anticipating, Avoiding, and Autonomy stages give a consistent lens across every business function.
Outcome and enabler layers
Separates business-outcome rows (billing, CoS, credit risk, customer service) from enabling capabilities (data, skills, governance, platform).
Function-specific AI options
Each cell surfaces the concrete AI options relevant to that function and maturity level, not generic advice.
Technology requirement mapping
Every maturity stage is paired with the technology and tooling needed to achieve it — Azure ML, Power BI, Fabric, low-code agent builders, and more.
Interactive assessment mode
Click-to-assess mode lets IT leadership mark current maturity per function, creating an instant heatmap of the estate and a conversation starter with the executive team.
Governance-by-design
Risk classification, regulatory mapping, and Design Authority review are embedded at every stage — not bolted on afterwards.