AILD executive tool

AI Leadership Readiness Checklist

Use this checklist before scaling AI across functions. The goal is to assess whether leadership, governance, and operating discipline are ready for wider deployment.

Who this is for

  • Strategy leaders
  • Transformation owners
  • Nontechnical executive teams
  • Board and governance reviewers

How to score

  • 1 = weak or unclear
  • 3 = partial readiness
  • 5 = strong and repeatable

Mark each dimension, then note the first leadership action required.

1. Executive readiness scorecard

Strategy and priorities

Do leaders agree on where AI creates value this quarter, and what should not be automated?

Decision rights

Is it clear which decisions AI can inform, which require approval, and who owns overrides?

Governance and controls

Are policy rules, escalation logic, and review checkpoints explicit for higher-risk use cases?

Operating cadence

Is there a weekly or monthly leadership rhythm for signals, decisions, follow-through, and calibration?

Measurement and evidence

Do teams track baseline time, quality, risk, and decision outcomes before claiming success?

Capability and trust

Do leaders and managers understand what AI is good at, where it fails, and when humans must step in?

Dimension Score (1-5) Gap you see First action
Strategy and priorities
Decision rights
Governance and controls
Operating cadence
Measurement and evidence
Capability and trust

2. Board and executive review questions

3. First 90 days action plan

Days 1-30

  • Choose one priority decision stream
  • Capture baseline cycle time and quality
  • Define trust and override rules

Days 31-60

  • Run a controlled pilot with weekly reviews
  • Log exceptions, overrides, and lessons
  • Refine KPIs and escalation logic

Days 61-90

  • Decide whether to expand, pause, or redesign
  • Prepare a board or executive update
  • Institutionalize the operating cadence

4. Good signals vs warning signals

Good signal Leaders can name the top use cases, owners, review points, and metrics. Warning signal AI activity is high, but no one can show decision quality, control posture, or business impact.