HBR Guide to AI Basics for Managers

Description

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. 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