Partnering with AI Agents for Business Success by Pearson

Course details

Discover how to partner with AI agents to drive business success and innovation. Dive into the differences between generative AI chats and AI agents, and learn how to delegate tasks to AI while maintaining quality control. Explore the potential of hybrid teams composed of humans and AI agents working together seamlessly. Master the skills of adopting a manager mindset to effectively introduce AI into workflows. Gain insights into best practices for long-running task assignments and how to keep AI agents aligned with your business goals. This course is perfect for business professionals, AI innovators, and anyone interested in enhancing productivity through AI collaboration. By the end, you’ll be equipped with the skills you need to comfortably navigate AI agent environments, ensuring optimal productivity and strategic alignment.

Concepts

Introduction

Welcome to the course

Generative AI Chat vs. AI Agents

Intro to generative AI
Deep neural networks and probabilistic output
AI agents and how they differ from chatbots
MCP and A2A protocols
The scaling laws
LLM chatbots and probabilistic output
Examples of AI agents and M365 out-of-box agents
AI agent environments and capabilities
Simulating an AI agent environment with generative AI in M365 Copilot
Demo - M365 AI agents researcher
Demo - M365 AI agents analyst

Delegating Actions to AI

Factors to evaluate when permitting AI to perform tasks
Implicit considerations in human communication
Assessing the quality of AI deliverables
Using iteration and feedback to improve AI results
Existential challenges - Determining human value when AI does the work
Adopting a manager mindset
Demo - M365 Copilot simulation of a team scheduling agent

Hybrid Teams - Humans and AI Agents

Introducing hybrid teams - Humans and AI agents
Best practices for operating in hybrid teams - Humans and AI agents
Considerations when assigning AI long-running tasks - Research and code refactoring
Human in the loop - Deciding when and how AI needs to check in with you
Function vs. task design