Module 3 Narration#
Opening#
Open with the professional setting: an operations team deciding whether to automate part of a high-volume administrative workflow. Ask students what decision is being made, who is affected, and what evidence would be persuasive to a skeptical reviewer.
Middle#
Move through the module in four passes:
Define Document and data extraction in the context of Automation & Process Optimization.
Walk through the lab as a proxy-data exercise, emphasizing what it can and cannot show.
Compare a baseline with an AI-enabled or more sophisticated alternative.
Translate the result into stakeholder language: recommendation, risk, mitigation, and next evidence.
Closing#
Close by returning to the module artifact: automation readiness memo with workflow map, exception policy, control points, and ROI estimate focused on document and data extraction: Prototype a document extraction pipeline.. Students should leave knowing exactly what artifact they are producing and how it will be judged.