AI readiness starts at the top. Do you have a clear vision, sponsorship, and alignment across leaders? We don’t have a defined AI strategy or owner. A few leaders are exploring use cases independently. Leadership understands AI’s potential and is shaping early priorities. There’s shared agreement on a roadmap and measurable goals. AI is part of our enterprise strategy and leadership performance plans.

Strong data and connected systems are the backbone of AI. Without them, even good ideas stall. What state is yours in? Our data is siloed or inconsistent. Some systems connect, but access and quality vary. We’re modernizing data and testing AI capabilities. Data is connected, secure, and cloud-ready for AI. We can deploy and monitor AI reliably across our business.

AI changes how people work. Readiness means your teams understand AI’s role and feel confident using it. How do your people feel about AI? Most employees have limited exposure to AI tools. A few teams are testing AI without training or guidance. We’ve started offering AI learning or enablement programs. Teams use AI in daily work and share results across departments. AI fluency is part of how we hire, train, and promote.

AI moves fast, but trust can move slowly. Guardrails let companies scale with confidence. We don’t have clear AI policies or ownership established. Early draft policies exist but aren’t consistently applied. We’ve defined responsible use and review processes. We monitor for bias, privacy, and compliance issues. Governance is built into every stage—from design to deployment.

AI success should be measurable. Readiness means you know what’s working, what isn’t, and how to improve. What does success look like and how will you measure it? We don’t track results from new tech initiatives right now. We measure activity or use, not business outcomes. We track performance for select pilots. We measure ROI and share insights with leadership. We continuously optimize and expand what works.