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AI
Foundational
9 min read

The AI Readiness Assessment Framework

A structured way to assess whether your data, processes, people and governance can actually support an AI programme before you commit budget.

Updated 19 May 2026

Why readiness assessment matters

Readiness is not about technical sophistication. Businesses with modest technology stacks frequently outperform better-resourced competitors because their processes are documented and their data is trustworthy.

Assess four dimensions honestly: data, process, people and governance. A weakness in any one of them will cap the return on everything else.

Dimension one: data

You do not need a data lake. You need to know, for each commercially important process, where the record of truth lives and how reliable it is.

  • Is there one authoritative system for customer records?
  • Can you reconstruct the last twelve months of enquiry-to-outcome history?
  • Do two people asking the same question get the same number?

Dimension two: process

Automation encodes a process. If the process is undocumented or varies by individual, automation will encode the variation and amplify it.

  • Can the process be described end to end in a single page?
  • Are the exception cases known and enumerable?
  • Is there agreement on who approves an exception?

Dimension three: people

The single strongest predictor of programme success is whether an operational leader, not a technologist, owns the outcome. Enthusiasm in IT is not sufficient.

Dimension four: governance

Decide before launch what the system is permitted to do without a human, what it must escalate, and who reviews the log. Retrofitting governance after an incident is expensive and slow.

Scoring and interpreting the result

Score each dimension one to five. Any dimension below three should be addressed before deployment in that area, not in parallel with it. A business scoring three or above across all four is ready to begin, regardless of size or sector.

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