1. Roadmap readiness
- Have you separated productivity use cases from decision-sensitive Finance workflows?
- Have you ranked use cases by value, feasibility, data readiness, risk and adoption effort?
- Have you defined what must be in place before pilots scale?
Related guide
If your immediate problem is deciding where AI should start, use the practical guide on prioritising AI Finance use cases without creating pilot sprawl.
Read the use case prioritisation guide2. Data and process readiness
- Do you understand actual process variation across teams, entities and systems?
- Are key data owners, definitions and quality issues visible?
- Can process mining evidence be translated into standardisation and automation decisions?
3. Control and governance readiness
- Have you defined human-in-the-loop review points?
- Are escalation rules clear for low-confidence or high-impact AI outputs?
- Can you track benefits, errors, adoption, risk and control strength together?
4. Adoption readiness
- Do Finance teams understand what AI will and will not do?
- Are leaders aligned on augmentation, accountability and measurable value?
- Is user feedback designed into the operating model?
Next step
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