Reimagining tech infrastructure for (and with) agentic AI
Nobody is talking about this: agentic AI's real bottleneck isn't the model—it's your data infrastructure.
Why it matters
As agentic AI deployment accelerates, infrastructure and data governance emerge as critical success factors. Leaders need to shift focus from model capability to building scalable, trustworthy data foundations that agents can reliably interpret and act on.
The key facts
9 to knowMcKinsey framework positions data governance as prerequisite for agentic AI scaling
Focus on converting unstructured data into governed, reusable assets
Emphasis on shared technical foundations and standards enforcement
Strategic insight relevant to enterprise AI infrastructure planning
Focus on data governance as prerequisite for agentic AI deployment
Emphasis on converting unstructured data into governed, reusable assets
Shared foundations and standards enforcement identified as key enablers
Targets data leaders and infrastructure decision-makers
Published Apr 2026 — timing aligns with agentic AI acceleration narrative
Go to the source
McKinsey Insightsmckinsey.com
Publisher excerpt: Scaling agentic AI requires turning unstructured data into governed, reusable assets that systems can interpret and trust. Data leaders can start by building shared foundations and enforcing standards.