Definition
What is ai readiness?
AI readiness is the degree to which an organisation can deliver, operate and govern an AI-supported workflow. It spans six dimensions: data availability and quality, process stability, systems and integration access, skills, governance, and change capacity.
Updated 3 September 2026
Why it matters
- Readiness determines delivery speed and how much of a first project is preparation work.
- It is opportunity-specific: a company can be ready for document extraction and unready for anything touching its core platform.
- Ignoring readiness produces roadmaps that look ambitious and deliver nothing in year one.
Business example
A company with high-value opportunities in its policy platform starts instead with inbound email triage, because the email data is immediately reachable while platform integration takes two quarters.
Common misconceptions
- 'We need clean data before starting.' You need reachable data for one workflow.
- 'Readiness is an IT property.' Reviewer time and process ownership are usually the binding constraints.
- 'It is a one-time score.' Readiness moves quarterly and should be re-scored.
Related concepts
- AI maturity
- AI governance
- AI opportunity assessment
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Editorial standard. Merjora publishes analysis, frameworks and publicly documented examples. We do not publish invented statistics, unattributed benchmarks or unverified customer stories.