Enterprise Intelligence Group
Most AI Assessments Score Your Technology. We Score Your Readiness.
AI readiness is whether your data, knowledge, processes and people can turn AI into a business outcome, and five of the six dimensions in this model are about more than which technology to buy. The EIG Retail Intelligence Maturity Model, and how to see where you stand.
An AI maturity assessment can end up scoring your technology: how many tools you own, which platforms you have bought. After fifteen years in retail and CPG, I think that is the wrong scorecard. AI readiness depends less on your tool count than on whether your data, knowledge, processes and people are ready to turn AI into a real business outcome.
So we score readiness, not technology. Here is how.
The six dimensions of AI readiness
Our Retail Intelligence Maturity Model looks at six things. Five of them are about more than which technology to buy:
- Business-outcome alignment — is AI tied to margin, growth, productivity or customer experience, or is it a science project?
- Enterprise knowledge readiness — is the knowledge behind your decisions captured and usable, or trapped in people's heads?
- Data and context foundation — are your definitions, hierarchies, rules and exceptions trusted enough to build on?
- Process and adoption fit — where can AI realistically help without breaking accountability?
- Governance and trust — what guardrails, approvals and human-in-the-loop controls do you need?
- Technology and delivery path — and only then, which mix of retrieval, knowledge bases, copilots and agents makes commercial sense?
Why readiness beats tooling
Working technology is not enough on its own. If the organization is not ready to trust an AI tool, govern it, or fit it into how the business actually runs, the project can fail with the model performing exactly as specified. A capable model on an ungoverned knowledge base can produce confident answers that are hard to trace, which can be worse than no answer at all.
The stakes justify the discipline. McKinsey estimates generative AI could unlock $240–390 billion in value for retailers — a 1.2 to 1.9 percentage-point margin uplift (LLM to ROI, McKinsey, 2024) — while noting that few retailers have yet realized that potential at scale. Readiness is one of the conditions that helps turn a promising demo into a deployed capability, measured against a number you care about.
From a score to a roadmap
The assessment is a starting point: it gives a read across the dimensions it covers and suggested first steps. A fuller review can turn that into a prioritized plan: where the value is, where the risk is, and what is worth doing first. A Retail Intelligence Discovery Workshop can take that further for one commercial area.
Frequently asked questions
What does an AI readiness assessment cover?
The model in this article covers six dimensions: business-outcome alignment, enterprise knowledge readiness, data and context foundations, process and adoption fit, governance and trust, and only then the technology path. The output of a full review is a maturity picture plus a prioritized plan: what to fix first, what to pilot first, and what to leave alone.
How long does the EIG AI Maturity Assessment take?
About five minutes, and it is free. You receive a read across the dimensions it covers; it is a starting point, not a verdict, and not a score designed to sell you software.
What happens after the assessment?
You get a starting view of where AI assistance may be worth examining first. If you want to go deeper, a Retail Intelligence Discovery Workshop examines one commercial area in more detail; scope and deliverables are agreed before it begins.
See where you stand
It takes about five minutes and gives you a starting view of where AI assistance may be worth examining first, before any technology decision.
EIG brings practical consulting expertise across retail, CPG and distribution, connecting people, process, data and technology.
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EIG helps retail, CPG and distribution teams clarify business requirements, evaluate technology choices and plan implementation. The starting point is the decision you need to make—not a requirement to adopt AI.
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