The Enterprise AI Readiness Checklist
Before you scale AI across your enterprise, assess whether your data foundation is ready with this 15-question checklist covering data access, context & accuracy, governance & trust, and integration & delivery.
Are You AI Ready?
Enterprise AI investments have reached an inflection point in 2025. While 77% of organizations prioritize AI-ready data, production reality reveals a harsh truth: 60% of AI initiatives fail to meet business SLAs, not because the models aren’t sophisticated enough, but because the data foundation isn’t ready. This gap explains why most “talk to your data” agents stall in pilots despite impressive demos. The difference between AI that delivers ROI and AI that disappoints comes down to architecture, not algorithms — unified access to distributed data, contextual intelligence that ensures accuracy, governance enforced at query time, and integration with existing workflows that drives adoption.
What you’ll discover:
- Whether your data architecture can actually support the AI initiatives you’re building, assessed across four critical pillars: data access, context & accuracy, governance & trust, and integration & delivery
- Your specific AI readiness score and what it means — from AI-Ready (13-15 yes answers) where you can scale confidently, to Early Stage (0-4 yes) where foundational work is required before AI investments pay off
- Concrete next steps tailored to your readiness level, plus the architectural capabilities that separate the enterprises successfully scaling AI from those trapped in endless pilots and POCs