The CIO's Guide to Context Graphs
A practical roadmap to capture decision traces, build institutional memory, and move AI from pilots to production – without waiting for perfect agents.
TRUSTED BY LEADERS
Inside the guide
Discover the key strategies that CIOs are using to implement context layers and scale AI.
Why Context Graphs Matter
Closing AI gaps by turning scattered decisions into queryable precedent.
Knowledge vs. Context Graphs
Why knowledge graphs are paper maps, while context graphs are GPS.
The 5-Stage Maturity Model
A staged roadmap from human-in-the-loop logging to partial autonomy with guardrails.
Selling Context Internally
Stakeholder-specific positioning with metrics that prove value.
Your First 90 Days
Guidance to instrument workflows, prove ROI, and scale from one domain to many.
Risks to Mitigate
How to avoid context sprawl, stale precedent, and vendor lock-in.
AI Programs Stall Without Context
The CIO's Principles
Start where you are, not where you wish you were.
Begin with human-in-the-loop processes and a small problem set.
Build institutional memory that compounds.
Minimum Viable Decision Traces (MVDTs) turn exceptions into standards.
Prove value in 90 days, then scale.
Execute a workflow, show impact, and expand with repeatable playbooks.
Federate ownership, centralize infrastructure.
Implement a context layer with domain-specific context graphs.
Make adoption inevitable, not mandated.
Embed precedent search where teams already work so logging isn’t a chore.
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