A readiness assessment examines foundations such as data, technology, skills, ownership and controls. That is useful when leadership needs to understand what is preventing a chosen strategy from working.
An opportunity assessment starts with customers and business performance. It identifies where a new capability could improve the result, then examines what that opportunity requires.
A business can have uneven foundations and still be able to test a worthwhile opportunity. It can also spend heavily improving those foundations without establishing what it should use them for.
Which question are you trying to answer?
| Your situation | Useful starting point |
|---|---|
| Plenty of ideas, but no clear investment priority | Compare the opportunities and their value cases |
| A specific AI capability is proposed, but its benefit is unclear | Examine the outcome, assumptions and evidence needed |
| Several credible initiatives are blocked by the same data or technology problem | Assess that shared constraint and the work needed to resolve it |
| An agreed strategy requires capabilities across several teams | Assess the foundations against the strategy’s requirements |
| A sensitive use requires dependable controls | Establish those requirements alongside the opportunity, before testing it |
These approaches can be combined. The useful distinction is whether the work begins with a business opportunity or an organisation-wide constraint.
Make readiness specific.
Consider two illustrative applications: an internal assistant that retrieves information, and a system that influences a consequential customer decision. Both may use AI, but they need different information, review arrangements and safeguards.
A single maturity score can conceal those differences. For each proposed use, ask:
- Can the team access representative information and work?
- Is the information reliable enough for this purpose?
- Who will review the result or act on it?
- What could go wrong, and how would people recover?
- Which connections to existing systems are necessary?
- Who will run and improve it after the initial work?
This turns a broad gap such as “data quality” into a requirement the business can act on.
Compare opportunities using five questions.
Become uses five connected tests to structure the discussion. They support judgement; a score alone cannot establish an investment case.
Does it support an important business goal?
Name the customer, commercial or operating outcome. Interest in AI is not enough to establish a priority.
How could it create value?
Explain how changed work could improve revenue, cost, capacity, service, quality or risk. Record the assumptions that connect the change to the result.
When can we learn enough to decide?
Identify what can be tested before a larger commitment. A short test may answer a critical question even when the full change takes much longer.
Does it improve work that matters?
Examine the decisions, delays or repeated activity affecting the outcome. Check whether a new capability would remove the constraint or simply add another tool.
Can we test and deliver it?
Consider access to people, information, technology and representative work. Identify any practical or control requirement that could overturn the case.
What should the assessment leave you with?
You should be able to explain what to pursue, what needs a further test and what to defer or stop. Each recommendation should connect the expected benefit to the necessary investment, client input, ownership and unresolved assumptions.
If several worthwhile opportunities share a constraint, there may be a good case for common foundations. If one can proceed responsibly with what already exists, a broader programme need not be its first step.