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Enterprise AI Readiness – Data, Workflow, and Deployment Choices

Lesson 4: Operations, Monitoring, and Change

Lesson Objectives

By the end of this lesson, students should be able to:

  • Name operational risks after launch.
  • Create a monitoring checklist.
  • Plan human escalation and update cycles.

Lesson Content

AI readiness does not end at launch. Workflows need monitoring because data changes, user behavior changes, costs change, and model behavior can change. A workflow that worked last month can become weaker when policies, documents, products, or student needs change.

Monitor:

  • Accuracy and usefulness.
  • Confusing or harmful responses.
  • Privacy mistakes.
  • Cost and usage spikes.
  • User complaints or workarounds.
  • Stale source material.
  • Cases that require human escalation.

Good operations also include a change log. When prompts, documents, settings, or review rules change, write down what changed and why.

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