Context Graphs - AI’s Trillion-Dollar Technology

In the first episode of the AI to ROI: Big Story podcast, our co-hosts Peter Buchanan and Ray Rike discuss the emerging importance of Context Graphs in AI Software.

Why are context graphs suddenly being called a trillion-dollar opportunity in enterprise AI? In this inaugural episode of The Big Story, hosts Ray Rike (CEO of Benchmarkit) and Peter Buchanan (Managing Partner of New Plan) dive into the "glue technology" that fills the missing gap in the AI stack.

While traditional knowledge graphs tell you what happened, context graphs reveal the why! Context Graphs capture the decision traces, policy constraints, and precedents that make AI agents truly auditable and trustworthy. From preventing "data breakage" in regulated workflows to revolutionizing supply chain quality control, discover why context is the key to moving AI from experimental pilots to reliable production.

Key Takeaways

• The Why Behind the Action: Context graphs provide the connectivity that agentic AI lacks, recording who made a decision and under what specific constraints.
• A Trillion-Dollar Value Add: Industry leaders believe context is a massive economic value driver for companies in the era of AI.
• Beyond Knowledge Graphs: Moving from simple data points to decision lineages that explain the "why" behind an event.
• Real-World Use Cases: Deep dives into data governance at firms like Vanguard and Prudential, and quality control in the automotive supply chain.
• The Vendor Landscape: Discussion on current players like Atlan, Neo4j, and Writer, and why tech giants like Microsoft and Salesforce are the "lurkers" to watch.
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Timestamps

• 00:00 Introduction to the AI to ROI podcast series.
• 02:40 Defining Context Graphs: The missing gap in the AI stack.
• 04:15 The Trillion-Dollar Opportunity: Economic value vs. market size.
• 06:30 Knowledge Graphs vs. Context Graphs: Moving from "what" to "why".
• 09:20 Who should care? Roles from the CEO to the Chief Risk Officer.
• 12:45 Use Case 1: Data Governance and preventing "downstream breakage".
• 15:10 Use Case 2: Unifying the Go-To-Market (GTM) stack.
• 18:30 Use Case 3: Supply chain visibility and automotive quality control.
• 21:40 The Market Map: Current leaders and "Lurker" strategies from Big Tech.
• 25:50 Executive Summary: Things every leader must do right now.

Context graphs are a key component to turn Agentic AI software vision into Agentic AI explainability!

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