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Every enterprise tracks KPIs for revenue and uptime. But very few track the metric that actually determines their future: The AI Readiness Score.
Spending money doesn't deliver outcomes. Readiness delivers outcomes. Most organizations think they are ready—until they begin a project and hit foundational gaps in data quality or governance.
Only 14% of organizations currently achieve a "High Readiness" score. The gap between them and the rest is massive. High-readiness companies:
▪️Scale AI 3x faster.
▪️Have 4x fewer model failures.
▪️Deploy AI agents confidently.
To improve your score, you must audit your organization across these five areas:
▪️Data Readiness: Is data governed, high-quality, and accessible?
▪️Technology Readiness: Is the architecture hybrid and composable?
▪️People Readiness: Do teams have the literacy to validate and monitor AI?
▪️Process Readiness: Are workflows optimized for human-AI collaboration?
▪️Trust Readiness: Do you have guardrails for safety and compliance?
Start by investing in governance early, trust accelerates adoption. Move toward a hybrid-by-design architecture and focus on automating data workflows to reduce manual errors.
Before asking "What AI should we build?", ask "Are we ready to build it?"