AI is ready for business. Are you ready for AI?
From financial modeling and product design to performance management and hiring decisions, AI and machine learning are becoming everyday tools for managers at businesses of all sizes. But AI systems come with benefits and downsides—and if you can't make sense of them, you're not going to make the right decisions.
Whether you need to get up to speed quickly or need a refresher, or you're working with an AI expert for the first time, the HBR Guide to AI Basics for Managers will give you the information and skills you need to succeed.
You'll learn how to:
Understand key AI terms and concepts
Recognize which of your projects would benefit from AI
Work more effectively with your data team
Hire the right AI vendors and consultants
Deal with ethical risks before they arise
Scale AI across your organization
Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.
Author(s): Harvard Business Review
Series: HBR Guide to Harvard Business Review
Publisher: Harvard Business Review Press
Year: 2023
Language: English
Commentary: HBR Guide put data to work, digital transformation
Pages: 277
Tags: HBR Guide put data to work, digital transformation
What You’ll Learn
Contents
Introduction
Section 1: AI Fundamentals
Ch. 1: Three Questions About AI That Every Employee Should Be Able to Answer
Ch. 2: What Every Manager Should Know About Machine Learning
Ch. 3: The Three Types of AI
Ch. 4: AI Doesn’t Have to Be Too Complicated or Expensive for Your Business
Section 2: Building Your AI Team
Ch. 5: How AI Fits into Your Data Science Team
Ch. 6: Ramp Up Your Team’s Predicitive Analytics Skills
Ch. 7: Assembling Your AI Operations Team
Section 3: Picking the Right Projects
Ch. 8: How to Spot a Machine Learning Opportunity
Ch. 9: A Simple Tool to Start Making Decisions with the Help of AI
Ch. 10: How to Pick the Right Automation Project
Section 4: Working with AI
Ch. 11: Collaborative Intelligence: Humans and AI Are Joining Forces
Ch. 12: How to Get Employees to Embrace AI
Ch. 13: A Better Way to Onboard AI
Ch. 14: Managing AI Decision-Making Tools
Ch. 15: Your Company’s Algorithms Will Go Wrong. Have a Plan in Place
Section 5: Managing Ethics and Bias
Ch. 16: A Practical Guide to Ethical AI
Ch. 17: AI Can Help Address Inequity—If Companies Earn Users’ Trust
Ch. 18: Take Action to Mitigate Ethical Risks
Section 6: Taking the Next Steps with AI and Machine Learning
Ch. 19: How No-Code Platforms Can Bring AI to Small and Midsize Businesses
Ch. 20: The Power of Natural Language Processing
Ch. 21: Reinforcement Learning Is Ready for Business
Epilogue: Scaling AI
Ch. 22: How to Scale AI in Your Organization
Appendix: Case Study
Glossary of Key AI Terms
Index
