Pragmatic AI Adopton is Hard!
summary
Claims that adoption fails from “cool tool” rush and instead AI strategy workshop identifies high‑impact, low‑risk uses and creates an AI policy that defines where and how to use models. Recommends experiments that scale: run prompts on a sales table starting with 10 then 100 then 1,000 rows to surface data quality and cost issues. Uses Jira builtin AI, Claude Code for coding, and n8n + Kubernetes to orchestrate and monitor usage; gradual scaling reduces breakage.
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