Video 6 [04:16]: Chatbot vs Agent

  1.  Module 7: Introduction and Instructions (Completed)
  2.  Video 1 [04:04]: Module Introduction (Completed)
  3.  Video 2 [06:13]: Demo vs Pilot (Completed)
  4.  Video 3 [02:46]: Klarna: Case Study (Completed)
  5.  Video 4 [03:53]: Allianz Project Nemo: Case Study (Completed)
  6.  Video 5 [02:58]: Salesforce Agentforce: Case Study (Completed)
  7.  Watch: The Race for Excel AI Agents: Here's What to Know (Completed)
  8.  Video 6 [04:16]: Chatbot vs Agent (Completed)
  9.  Video 7 [03:37]: Human-Guided Agent Patterns (Completed)
  10.  Self-Study Quiz 7.1: Think & Apply💡From Experimentation to Real-World Pilots ((Must submit the Quiz))
  11.  Video 8 [04:09]: Connectors for Automation (Completed)
  12.  Video 9 [03:05]: Five Design Principles (Completed)
  13.  Video 10 [03:41]: Multi-Agent Platforms (Completed)
  14.  Video 11 [02:15]: Singapore Bank’s Agentic Workflow: Case Study (Completed)
  15.  Video 12 [03:22]: When to use Multi-Agent Platforms (Completed)
  16.  Self-Study Quiz 7.2: Think & Apply💡Designing Agentic Workflows ((Must submit the Quiz))
  17.  Video 13 [10:20]: M365 Copilot Workflows: Demo (Completed)
  18.  Self-Study Assignment 7.3: Think & Act💡 Design Your AI Workflow Pilot (Completed)
  19.  Reading: Spot the Automation Opportunity (Completed)
  20.  Video 14 [04:03]: Final Thoughts (Completed)
  21.  Self-Study Assignment 7.4: Think & Act💡Workflow Governance Review (Completed)
  22.  Discussion Board 7.5: Think & Share💡Trusting AI Agents at Work ((Not yet completed))
  23.  Summary and Video Transcripts: Module 7⭐ (Completed)
  24.  Professor Ian's Recommendation for Further Learning: Module 7 (Completed)
  25.  Module 7: Q&A Discussion Board ((Not yet completed))
  26.  Module 7: Feedback Survey ((Must submit the Quiz))

In this video, Prof. Ian explains the key differences between traditional chatbots and AI agents. He highlights how agents go beyond conversation by using tools, working autonomously, maintaining context and completing multi-step tasks to achieve a goal. Through practical examples, he shows how agents can combine reasoning, memory and system access to automate more complex workflows while reducing the need for constant human input.

Downloaded lesson video