liveBook · Manning

Disruption

As explained in The Art of AI Product Development

An operational disruption is a temporary interruption, slowdown, or added workload in a business process caused by system behavior.

An operational disruption is a temporary interruption, slowdown, or added workload caused by system behavior. In AI products, an error may require manual intervention, delay workflows, increase pressure on staff, or frustrate customers. section 12.3.2

Manage disruption by pairing candid risk communication with practical recovery measures:

  • Explain how errors can affect workflow speed, staffing, and customer response times. section 12.3.2
  • Provide escalation pathways so unresolved cases reach live agents instead of blocking service. section 12.3.2
  • Use real-time updates or status information to help teams adjust operations quickly. section 12.3.2

Peak-demand chatbot failure

When a customer-service chatbot fails during peak demand, live-agent workload rises and response times slow. An escalation path limits the disruption by transferring cases the AI cannot resolve. section 12.3.2

How The Art of AI Product Development covers it

How deep it goes
Defines disruption through consequences and fallback measures, but stops short of detailed incident-management procedures.
Examples
Uses a peak-demand customer-service chatbot failure that increases live-agent workload and slows response times.
What it assumes
Assumes familiarity with AI-enabled workflows and teaches disruption through concrete consequences of system errors.
What you can do after
Operate more resiliently by recognizing workflow impacts and preparing escalation or status-update responses.
How it connects
Connects disruption with AI errors, escalation pathways, manual intervention, customer service, and real-time status communication.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.