AI Readiness Checklist
Before you invest in AI, confirm you're ready across the things that actually determine success: a clear strategy, usable data, people who can adopt it, and governance to keep it safe. Work through this checklist to find your gaps first.
Strategy & use cases
- Defined the business goals AI should serve
- Identified and prioritized high-value use cases
- Set success metrics and ROI targets for the first use case
Data
- Inventoried the data sources AI will rely on
- Assessed data quality, completeness, and access
- Confirmed data privacy and compliance requirements
People & skills
- Assessed current AI fluency across teams
- Identified internal champions to lead adoption
- Planned role-based training and support
Governance & risk
- Drafted an AI acceptable-use policy
- Defined where humans stay in the loop
- Assigned clear ownership for AI decisions
Technology & budget
- Reviewed existing tools before buying more
- Set a budget for a first, scoped pilot
- Chosen one high-ROI use case to pilot
Why this matters
Most AI initiatives stall not because the technology fails, but because the organization wasn't ready: unclear goals, messy data, no governance, or no adoption plan. A readiness check surfaces those gaps while they're cheap to fix.
Want help working through this?
An AI readiness assessment turns this checklist into a prioritized plan with the highest-ROI, lowest-risk place to start.
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