Research
AI opportunity and readiness assessment framework
A concept for a reusable framework that ranks AI use cases by value, feasibility, data readiness and risk.
- Updated:
- What it is
- A defined concept for an assessment framework: the questions, criteria and outputs an AI Opportunity Assessment works through, written down so that each assessment is consistent and comparable.
- What it is not
- Not software, not a scoring product and not a substitute for the judgement of the engagement team.
The question
How can an organisation choose between AI ideas on evidence, rather than on enthusiasm or the latest demonstration?
What the framework would assess
- Value: the business or user outcome, and what happens if nothing changes.
- Feasibility: whether the workflow, systems and integration make the use case buildable.
- Data readiness: whether the data the use case needs exists, is accessible and is of known quality.
- Risk: security, privacy, human oversight and the consequences of the model being wrong.
- Organisational readiness: governance gaps, ownership and the capacity to adopt the change.
What it would produce
- An opportunity map and ranked use cases.
- A feasibility and risk view for each.
- A recommendation on which use case, if any, is worth a prototype.
Principles it would encode
No AI for its own sake; bounded, measurable workflows before broad autonomous systems; evaluation criteria defined before production; operational cost, reliability and vendor dependence understood early.
Known limitations
This page describes a concept drafted from Vitalos's own delivery methods. It makes no claim about any implementation, results or client use; none are published here. The criteria have not been independently reviewed, weightings and thresholds are not defined, and the framework would need evidence from real assessments before it could be treated as an accelerator.