
HBR Guide to AI Basics for Managers
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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.
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Harvard Business Review is the leading destination for smart management thinking. Through its flagship magazine, 12 international licensed editions, books from Harvard Business Review Press, and digital content and tools published on HBR.org, Harvard Business Review provides professionals around the world with rigorous insights and best practices to lead themselves and their organizations more effectively and to make a positive impact.
You can find HBR at: hbr.org
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Content
- Intro
- 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
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