Jaideep Parashar, founder of ReThynk AI, argues that DevOps teams often chase flashy AI projects instead of those that deliver measurable results. He warns against blanket slogans like “add AI everywhere” or “automate everything,” which turn experimentation into a series of failures. Instead, Parashar proposes a three‑step framework.

First, target pain points that recur daily—customer queries, sales follow‑ups, marketing copy, proposal drafts, internal reporting, and SOP training. Repetition builds habit and adoption. Second, choose workflows with a clear before‑and‑after metric, such as response time, turnaround, hours saved, conversion rate, error rate, or customer satisfaction.

A single KPI beats vague ideas. Third, start with low‑risk, high‑leverage tasks—drafts, assistance, suggestions—so mistakes are recoverable and trust can grow before full automation. He also offers a quick scoring method that weighs frequency, friction, impact, measurability, and risk.

By treating AI as a system design tool rather than a gadget, DevOps can secure one repeatable win that demonstrates real value.