For decades, enterprise databases have evolved in response to infrastructure shifts: from spinning disk to flash, from on-premises to public cloud. But the rise of AI introduces something fundamentally different. This isn’t a change in storage medium or deployment model. It’s a change in who … or what … is consuming the data.
AI systems don’t want reports. They don’t tolerate latency. They don’t operate in batches. They expect immediate access to operational truth. As inference engines and AI agents move closer to systems of record, the database is no longer just storing business state — it is becoming part of the reasoning path itself.
Inference is now a first-class database workload.
Index
Part 1 – The Shift: How AI agents change the way systems of record are accessed, queried, and used.
Inferencing Is a Database Problem Disguised as an AI Problem
Databases Were Built for Humans – AI Agents Change the Equation
AI Doesn’t Read Dashboards… and That Changes Everything for Databases
Why We Spent 20 Years Protecting Databases from Analytics (and Why AI Just Broke That Truce)
The Cloud Is Built on Uniformity. Databases Are Not
The Hidden Cost of Letting AI Agents Query Live Systems
AI Can Replace Interfaces, Not Systems of Record
Part 2 – Under Pressure: How AI agents place systems of record under sustained architectural, operational, and economic pressure.
AI Agents Don’t Just Add Load. They Change Its Shape
Transactions Assume Intent. Agents Don’t Guarantee It
More to follow…
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