Advanced Power Apps Development with AI Builder and Model-Driven Apps — Lesson 2: AI Builder Models and App Integration

Learning Objectives

• Select, prepare, train, test, publish, and version suitable AI Builder models
• Display predictions, extracted data, confidence, and review controls in applications
• Capture corrections, approvals, exceptions, and model feedback

Detailed Topics

• Select: Select, prepare, train, test, publish, and version suitable AI Builder models
• Display predictions: Display predictions, extracted data, confidence, and review controls in applications
• Capture corrections: Capture corrections, approvals, exceptions, and model feedback

Guided Demonstration

1. Review the requirement, users, data, dependencies, permissions, risks, and expected result.
2. Demonstrate the relevant configuration, application, automation, analysis, security, or development workflow step by step.
3. Capture settings, outputs, logs, screenshots, calculations, test results, and other useful evidence.
4. Compare the observed result with acceptance criteria and explain any corrective action.

Hands-On Activity

Integrate an AI Builder model into a model-driven process.

• Document assumptions, prerequisites, and the planned sequence before starting.
• Complete the activity and preserve evidence of normal, boundary, and failure behavior.
• Record issues, corrective actions, reusable notes, and the next improvement priority.

Scenario Analysis

• Identify the business or technical decision that must be made.
• Compare valid implementation approaches and their trade-offs.
• Consider security, privacy, accessibility, performance, support, and operational impact.

Troubleshooting Focus

• Separate symptoms from causes and collect evidence before applying a fix.
• Check configuration, data, permissions, dependencies, capacity, connectivity, and recent changes.
• Validate rollback, recovery, ownership, user impact, and business continuity.

Validation Checklist

• The requirement, scope, inputs, and expected outcome are clear.
• The selected design or configuration is documented and follows approved standards.
• Normal, boundary, failure, security, accessibility, and operational conditions are reviewed.
• The result is supported by evidence and the next improvement is prioritized.

Lesson Outcome

Learners can explain and apply AI Builder Models and App Integration in a realistic scenario and validate the result with documented evidence.