Checklist

AI Integration Readiness Checklist

An actionable, savable checklist teams can use to assess readiness before introducing AI-assisted tools into workflows. Includes fields to capture approvals, effort estimates, risk scoring, ownership, and notes to support prioritization and follow-up.

Interactive Tool

AI Integration Readiness Checklist

Use this checklist before launching an AI pilot or embedding AI into a workflow. Answer each item, capture owners and estimates, and record open issues. The form saves structured responses so teams can prioritize, track approvals, and return to update status.

Tip: Focus on measurable objectives, documented data governance, clear human oversight, explainability where required, monitoring and rollback plans, and stakeholder training.

Give a short name that stakeholders will recognize.
Who owns the pilot and will be accountable for follow-up?
Is the objective written down and linked to measurable outcomes or KPIs?
Describe expected outcome, metrics, and how success will be measured.
Consider data sources, ownership, access controls, retention, and PII handling.
Record legal or regulatory approvals required for data use.
Are roles, decision gates, and escalation paths defined for human review?
Is explainability required for this use? If yes, note the level (e.g., feature-level, decision rationale).
Includes metrics to monitor, validation tests, alerting thresholds, and clear rollback criteria.
Attach vendor documentation, model factsheets, contracts, SLAs, and audit rights where applicable.
Plans for training end users, support staff, and communicating changes to impacted groups.
Rough estimate for running the pilot and initial monitoring (used for prioritization).
Higher numbers indicate higher potential harm, compliance exposure, or reputational risk.
1.0 10.0
Who will follow up on outstanding items and shepherd approvals?
Record unresolved questions, blockers, or links to supporting documents.
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