Nine Unusual Ways My Clients Use AI With SQL Server
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Nine real-world workflows where AI was used alongside SQL Server to tackle large, tedious tasks that teams had avoided for years. The use cases include extracting business rules from 800 PL/SQL packages during an Oracle migration, reverse-engineering undocumented vendor schemas using DDL, foreign key graphs, value distributions, and Extended Events captures, decoding abbreviated German ERP column names, mapping schemas during M&A due diligence, converting compliance documents into executable SQL checks, tracing column-level data lineage through dynamic SQL, auditing and classifying 240 SQL Agent jobs, diagnosing query plan regressions after version upgrades, and building differential test suites to catch semantic dialect drift after migrations. The common thread: AI reads at volume and proposes; humans verify and decide. Inverting that order produces confident fiction. None of these were hard problems — they were large, tedious reading tasks that nobody ever started because they seemed too big to finish.
