The Cost of Blurry Responsibilities in Automated Systems
Practical guidance on the cost of blurry responsibilities in automated systems and what to do about it.
The point
The Cost of Blurry Responsibilities in Automated Systems is not a technology statement. It is a decision quality statement.
The decision lens for this topic
Ask: "What would a good decision look like without AI?" Then ask: "What does AI change - speed, coverage, consistency, or risk?" If you cannot answer, you are not ready to automate this decision.
Why this matters
In operations, AI is often introduced to "remove friction". But friction is sometimes a signal: missing data, unclear handoffs, or unresolved ownership.
Common failure pattern
Automation is added on top of an unclear process. The organization gets:
- faster mistakes
- inconsistent outcomes
- harder debugging (because the system is now complex)
Never automate a step you cannot clearly describe, measure, and audit.
A practical checklist
- What is the input? Who produces it?
- What is the output? Who consumes it?
- What is the definition of "done"?
- What are the exceptions and edge cases?
- What happens when the system is unsure?
Fix the process first. Then automate the clean version.