The Gap 2 Infrastructure AI Readiness Assessment measures seven dimensions across the infrastructure layer — and the synthesis reveals dependencies invisible to any single vendor.The capital is not the constraint. Hyperscalers are on track to invest roughly $675 billion in AI infrastructure in 2026 alone. The constraint is what sits underneath the organizations trying to run production AI on top of it. RAND's research on AI project failure found that more than 80% of AI initiatives fail — more than double the failure rate of non-AI technology projects — and identified inadequate infrastructure as one of the primary causes. Informatica's 2025 CDO Insights survey of 600 data leaders found that 43% cite data quality, completeness, and readiness as the leading obstacle keeping AI pilots from reaching production.Most organizations cannot answer, with precision, whether their infrastructure is enabling AI or quietly blocking it. Not because the question is complicated — because no single vendor sees the full stack, and no internal team is incentivized to audit its own dependencies.The Gap 2 Infrastructure AI Readiness Assessment exists for that reason. It does not evaluate infrastructure in isolation — it measures seven dimensions and synthesizes what they mean together, surfacing dependencies that infrastructure, workflow, and adoption teams each see only in part.If your organization is investing in AI infrastructure without a clear, independent measure of readiness, that is the conversation to start.Begin at aiecopartners.com.If you have any questions, drop us an email: info@aiecopartners.com.
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