Video 2 [06:13]: Demo vs Pilot
- Module 7: Introduction and Instructions (Completed)
- Video 1 [04:04]: Module Introduction (Completed)
- Video 2 [06:13]: Demo vs Pilot (Completed)
- Video 3 [02:46]: Klarna: Case Study (Completed)
- Video 4 [03:53]: Allianz Project Nemo: Case Study (Completed)
- Video 5 [02:58]: Salesforce Agentforce: Case Study (Completed)
- Watch: The Race for Excel AI Agents: Here's What to Know (Completed)
- Video 6 [04:16]: Chatbot vs Agent (Completed)
- Video 7 [03:37]: Human-Guided Agent Patterns (Completed)
- Self-Study Quiz 7.1: Think & Apply💡From Experimentation to Real-World Pilots ((Must submit the Quiz))
- Video 8 [04:09]: Connectors for Automation (Completed)
- Video 9 [03:05]: Five Design Principles (Completed)
- Video 10 [03:41]: Multi-Agent Platforms (Completed)
- Video 11 [02:15]: Singapore Bank’s Agentic Workflow: Case Study (Completed)
- Video 12 [03:22]: When to use Multi-Agent Platforms (Completed)
- Self-Study Quiz 7.2: Think & Apply💡Designing Agentic Workflows ((Must submit the Quiz))
- Video 13 [10:20]: M365 Copilot Workflows: Demo (Completed)
- Self-Study Assignment 7.3: Think & Act💡 Design Your AI Workflow Pilot (Completed)
- Reading: Spot the Automation Opportunity (Completed)
- Video 14 [04:03]: Final Thoughts (Completed)
- Self-Study Assignment 7.4: Think & Act💡Workflow Governance Review (Completed)
- Discussion Board 7.5: Think & Share💡Trusting AI Agents at Work ((Not yet completed))
- Summary and Video Transcripts: Module 7⭐ (Completed)
- Professor Ian's Recommendation for Further Learning: Module 7 (Completed)
- Module 7: Q&A Discussion Board ((Not yet completed))
- Module 7: Feedback Survey ((Must submit the Quiz))
In this video Prof Ian explains how to design effective AI pilots that are focused, time-bound, measurable, reversible and grounded in real operational challenges. Prof. Ian emphasises starting with small, repetitive tasks such as reporting, document handling and status updates, rather than attempting to automate entire workflows at once. He also introduces the pilot loop of build, run, observe and refine, highlighting the importance of continuous iteration and learning. Ultimately, successful pilots help organisations validate value before scaling AI more broadly.