The rush to automate everything with AI is creating hidden costs and strategic risks that businesses must consider. While agentic AI and automation offer transformative potential for complex, data-heavy processes, many applications now solve trivial problems through unnecessarily complex global systems.

Author Itay Sagie illustrates this with a simple example: using Google Assistant to turn on a shower vent that could be manually switched just inches away. The command travels through submarine fiber networks to Europe and back, consuming compute resources and creating multiple failure points. This pattern repeats across many AI workflows that deploy sophisticated orchestration tools and external APIs for tasks that junior staff could handle in minutes.

Beyond operational complexity, the economic and environmental costs compound at scale. Voice commands and AI workflows rely on paid infrastructure including compute, API calls, and vendor integrations. Meanwhile, data centers already generate hundreds of millions of tons of CO₂ emissions annually, with AI becoming an increasingly significant contributor. Sagie warns that optimizing for automation's sake often means losing focus on solving meaningful problems.