What do you think?
Artificial Intelligence: The Insights You Need from Harvard Business Review
Companies that don't use AI will soon be obsolete.
From making faster, better decisions to automating rote work to enabling robots to respond to emotions, AI and machine learning are already reshaping business and society. What should you and your company be doing today to ensure that you're poised for success and keeping up with your competitors in the age of AI?
Artificial The Insights You Need from Harvard Business Review brings you today's most essential thinking on AI and explains how to launch the right initiatives at your company to capitalize on the opportunity of the machine intelligence revolution.
Business is changing. Will you adapt or be left behind?Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues--blockchain, cybersecurity, AI, and more--each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas--and prepare you and your company for the future.
From making faster, better decisions to automating rote work to enabling robots to respond to emotions, AI and machine learning are already reshaping business and society. What should you and your company be doing today to ensure that you're poised for success and keeping up with your competitors in the age of AI?
Artificial The Insights You Need from Harvard Business Review brings you today's most essential thinking on AI and explains how to launch the right initiatives at your company to capitalize on the opportunity of the machine intelligence revolution.
Business is changing. Will you adapt or be left behind?Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues--blockchain, cybersecurity, AI, and more--each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas--and prepare you and your company for the future.
182 pages, Kindle Edition
First published August 27, 2019
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 30 of 45 reviews
September 11, 2019
Excellent collection of essays on Artificial Intelligence by experts in the field. While not particularly an introduction to AI for business people, it does present its advantages and challenges from a business point of view, so it's not full of technical jargon.
Highly recommended for business people who want to know how AI can impact their business.
Highly recommended for business people who want to know how AI can impact their business.
September 16, 2025
Una muy buena guía práctica para entender las aplicaciones reales de la inteligencia artificial, y sus límites, en las empresas, con algunas ideas para desarrollar proyectos piloto.
Aunque fue publicado en 2019, me pareció bastante actualizado, o con información lo suficientemene actualizada para servir como primera aproximación al tema. Me pareció bastante objetivo.
Aunque fue publicado en 2019, me pareció bastante actualizado, o con información lo suficientemene actualizada para servir como primera aproximación al tema. Me pareció bastante objetivo.
January 4, 2025
Good overview and you learn how AI can influence your business.
For me it’s on a to basic and general level
For me it’s on a to basic and general level
September 13, 2026
Really good book on foundational introduction to AI, although it was printed in 2018 but still gives you solid base for navigating the new AI world.
September 17, 2021
It's a quick MUST for everyone who is interested in applying AI in their everyday business life.
September 3, 2019
This is an excellent high-level view of AI at the moment. Like any business book, you're rating will depend on what you're seeking. Because there is no technical language, it has lots of interesting examples and each chapter (which is really a reprinted article) has a nice summary at the end. If you're seeking an intelligent and insightful set of authors that layout broad strokes, this is highly recommended.
October 15, 2022
A simple book to read, this collection of articles on AI and Machine Learning provides a nice wrap up of the state of this discipline.
If you have a decent understanding of machine learning, you probably have read many other books or articles that provide the same messages.
It’s a nice read for whoever has no understanding of ML or has never read any abstract paper on it.
Overall very easy read.
If you have a decent understanding of machine learning, you probably have read many other books or articles that provide the same messages.
It’s a nice read for whoever has no understanding of ML or has never read any abstract paper on it.
Overall very easy read.
March 3, 2023
Very high level brief overview not in depth review , most of the content I was already familiar with but this book will be very helpful to new players without any awareness of AI
Humans know a lot more than what they do on a regular basis whereas machines can do a lot more than what they know
this book doesn't cover all approaches of machine learning: inductive reasoning, connectionism, evolutionary computation, Bayes' theorem and analogical modelling
just focuses 3 of the above that too more emphasis on supervised learning
supervised learning
deep learning
statistical models
think of AI interms of augmenting human capabilities not entirely replacing human workforce
somethings humans are good at (creativity , compassion , social aspect) where as machines are good
at processing speed of computing voluminous data , scalability , automating mechanical tasks ,
Instead of focussing on best algo , focus on how your business use cases fit into existing algo with rapid experimentation then eventually focus on better algo
data is oil for new economy , not completely true once you build a model its applicable only till that period of time ,.. think sustenance and future prediction models based on new learnings
data is important , but quality of data is even more important alongside quantity of data
aware of errors/accidents than could occur during learning phase and production phase some we cant predict
so to mitigate the risks of unforeseen ones validate inputs more rigorously , have alternative fallback in place for temp correction(in production)
ex errors of past: army training model was learning background instead of target , automated email systems were sending inappropriate response messages
like I love you , porn videos surfaced in adobe production systems without validating age of kids , human was killed in robotic machine assembly
Think of AI in all possible industries for cost cutting , improved productivity , scaling production
flexibility
speed
scalability
prediction
personalisation
Humans know a lot more than what they do on a regular basis whereas machines can do a lot more than what they know
this book doesn't cover all approaches of machine learning: inductive reasoning, connectionism, evolutionary computation, Bayes' theorem and analogical modelling
just focuses 3 of the above that too more emphasis on supervised learning
supervised learning
deep learning
statistical models
think of AI interms of augmenting human capabilities not entirely replacing human workforce
somethings humans are good at (creativity , compassion , social aspect) where as machines are good
at processing speed of computing voluminous data , scalability , automating mechanical tasks ,
Instead of focussing on best algo , focus on how your business use cases fit into existing algo with rapid experimentation then eventually focus on better algo
data is oil for new economy , not completely true once you build a model its applicable only till that period of time ,.. think sustenance and future prediction models based on new learnings
data is important , but quality of data is even more important alongside quantity of data
aware of errors/accidents than could occur during learning phase and production phase some we cant predict
so to mitigate the risks of unforeseen ones validate inputs more rigorously , have alternative fallback in place for temp correction(in production)
ex errors of past: army training model was learning background instead of target , automated email systems were sending inappropriate response messages
like I love you , porn videos surfaced in adobe production systems without validating age of kids , human was killed in robotic machine assembly
Think of AI in all possible industries for cost cutting , improved productivity , scaling production
flexibility
speed
scalability
prediction
personalisation
January 11, 2020
This is a really good book. The content is high-quality, meaty, meaningful and usefull, containing information and ideas that can be taken straight into the workplace by leaders involved in digital. Chapter 1 on the business of AI lays out a great definition and explanation of what AI is and more importantly what it is not. Here there are some insightful nuances, for example the fact that we will be unable to a certain degree of knowing how AI came to a specific conclusion. Chapter 2 on Facebook AI' workshop is excellent, taking us right inside so we can see how AI is rolled out in one of the worlds largest organisations. Again there are some real gems here, like focussing on some very specific processes where AI can help and then starting there, as opposed to the grand, big-picture prespective. Chapter 8 covers the nature of collaboration between AI and humans, something the book takes as a central theme. Here 5 characteristics of business processes that companies typically want to improve: flexibility, speed, scale, decision making and personalisation. There are some good examples of eacg provided, for example Mercedes use of cobots to allow greater customer personilsation of cars.
The section on how AI is getting more emotional is way too short and feels perfunctory. The are a few references to cars but not much more than that, as with the chapter on strategy, could be longer and more detailed.
All-in all though a great text I'd recommend for anyone wanted a greater insight into effective uses of AI.
The section on how AI is getting more emotional is way too short and feels perfunctory. The are a few references to cars but not much more than that, as with the chapter on strategy, could be longer and more detailed.
All-in all though a great text I'd recommend for anyone wanted a greater insight into effective uses of AI.
September 2, 2019
I’ve been working with data for the majority of my career. I started out with Executive Reporting, moved on to Business Intelligence, which then became Business Analytics, and added in Performance Management and Predictive capabilities. Eventually this led to Artificial Intelligence, Machine Learning, Data Science, and more.
Artificial Intelligence is much like other technologies in that it is not a question of whether your organization will adopt AI, but rather when and how to tackle that first project. As with most new technologies, that first project is the most daunting of all. I have seen many companies dive in head first and quickly try to keep their heads above water. It’s not difficult, but it’s a matter of identifying the right use cases and the right place to start within your company. Getting started is key and if you haven’t already started, you may already be behind the curve compared to your peers.
The articles in this book are a good compilation that can help companies get past that first bump in the road and begin their AI journey in earnest. This would be a great read for any team that is just starting out to help set the stage for their conversations and set the wheels in motion. It would also be a good read for any team that may have stumbled on their first foray and need to get things back on track quickly.
As always HBR has solid articles and advice. A pleasure to read these in a combined offering.
Artificial Intelligence is much like other technologies in that it is not a question of whether your organization will adopt AI, but rather when and how to tackle that first project. As with most new technologies, that first project is the most daunting of all. I have seen many companies dive in head first and quickly try to keep their heads above water. It’s not difficult, but it’s a matter of identifying the right use cases and the right place to start within your company. Getting started is key and if you haven’t already started, you may already be behind the curve compared to your peers.
The articles in this book are a good compilation that can help companies get past that first bump in the road and begin their AI journey in earnest. This would be a great read for any team that is just starting out to help set the stage for their conversations and set the wheels in motion. It would also be a good read for any team that may have stumbled on their first foray and need to get things back on track quickly.
As always HBR has solid articles and advice. A pleasure to read these in a combined offering.
January 2, 2021
Short and sweet
This is a short compilation of HBR articles about AI (the added value opportunity, the risks, the method how to formulate problems correctly and how to work with it in existing workplaces/companies).
The authors are pretty good guys from whom I already read some books (The second machine age; Machine Platform Crowd; Prediction Machines) so their knowledge is firm on the topic.
What's good about the book:
- it's short and does not overwhelm you with techno-jargon
- it's relevant regarding the selection of bigger topics: what is AI and Machine Learning, what does data mean for your company, how to deal with it now and long-term
- also gives good examples about specific companies and their implemented strategies (e.g. Facebook, who embraced AI fully across its businesses)
- it's neither too optimistic, nor too pessimistic
5 stars because the articles are definitely worth reading, even one by one or straight in a raw for business people.
Note: This book is NOT about coding AI and ML algorithms, but about its potential impact on business and suggested implementation strategies.
This is a short compilation of HBR articles about AI (the added value opportunity, the risks, the method how to formulate problems correctly and how to work with it in existing workplaces/companies).
The authors are pretty good guys from whom I already read some books (The second machine age; Machine Platform Crowd; Prediction Machines) so their knowledge is firm on the topic.
What's good about the book:
- it's short and does not overwhelm you with techno-jargon
- it's relevant regarding the selection of bigger topics: what is AI and Machine Learning, what does data mean for your company, how to deal with it now and long-term
- also gives good examples about specific companies and their implemented strategies (e.g. Facebook, who embraced AI fully across its businesses)
- it's neither too optimistic, nor too pessimistic
5 stars because the articles are definitely worth reading, even one by one or straight in a raw for business people.
Note: This book is NOT about coding AI and ML algorithms, but about its potential impact on business and suggested implementation strategies.
December 31, 2023
These compilation of articles will be useful to people, who have no idea about AI and haven’t read anything about it. So for me there was no new information hence the 2 stars. Some interesting for me parts out of the articles are:
Risks of machine learning - people have hard time to understand how the machines have come to the results and don’t quite comprehend exactly the underlying algorithms. There are 3 risks:
1. Machines might have hidden biases based on what data they have been trained.
2. Neural network systems deal with statistical truths rather than literal truths. That can make it impossible to prove that the system would work in all cases, especially in situations that weren’t presentable in the training data.
3. When the system makes an error, diagnosing and correcting the problem might be difficult.
Machine learning is only as good as its training.
Risks of machine learning - people have hard time to understand how the machines have come to the results and don’t quite comprehend exactly the underlying algorithms. There are 3 risks:
1. Machines might have hidden biases based on what data they have been trained.
2. Neural network systems deal with statistical truths rather than literal truths. That can make it impossible to prove that the system would work in all cases, especially in situations that weren’t presentable in the training data.
3. When the system makes an error, diagnosing and correcting the problem might be difficult.
Machine learning is only as good as its training.
September 19, 2019
This book has a great collection of articles explaining what is artificial intelligence, how it affects the modern business landscape, what are the implications to ordinary consumers, and so much more.
Readers will also benefit greatly with the Take Aways provided by the end of each article. This is a great way to summarize the main points discussed; so if the reader is pressed for time he/she can jump right to the take away section.
The articles are well written, carefully selected, and easy to understand. I would definitely recommend this book to anyone who wants to get fast and in-depth understanding of the basic concepts of artificial intelligence.
Readers will also benefit greatly with the Take Aways provided by the end of each article. This is a great way to summarize the main points discussed; so if the reader is pressed for time he/she can jump right to the take away section.
The articles are well written, carefully selected, and easy to understand. I would definitely recommend this book to anyone who wants to get fast and in-depth understanding of the basic concepts of artificial intelligence.
July 11, 2021
From the HBR Insights series, on the topic of Artificial Intelligence, this book contains 12 articles from leading experts, leaders, and AI practitioners across the technology industry. This book is a good starting point for a novice, a timely reminder for industry leaders, and mandatory reading for anyone interested to know more about the AI topic. Each of the articles are unique, present independent perspectives, and list current examples for AI application in a variety of industries and platforms
August 27, 2024
Um conjunto de textos bem organizados e um excelente contributo para a adoção da IA no contexto das empresas. Sem o hype que atualmente está associado com a inteliGência artificial e com um conjunto de capítulos de diferentes especialistas que se complemetam de forma útil para dar uma visão que ainda se revela adequada - o livro é de 2019.
A versão portuguesa peca pela tradução pouco cuidada dos termos técnicos associados com a IA e pode gerar alguns mal entendidos em função disso. No restante, um texto útil e de leitura rápida.
A versão portuguesa peca pela tradução pouco cuidada dos termos técnicos associados com a IA e pode gerar alguns mal entendidos em função disso. No restante, um texto útil e de leitura rápida.
February 23, 2025
I recently picked up Crypto by the Harvard Business Review, and I can confidently say it has been one of the most valuable resources in my journey of understanding and working within the crypto industry. As someone who navigates the complexities of blockchain, wallets, and digital assets daily, this book provided a level of clarity and depth that few other resources have.
What I loved most about this book was how it distilled complex topics—decentralization, smart contracts, crypto regulation, and enterprise adoption—into digestible insights without oversimplifying. Harvard Business Review’s approach combines expert perspectives with real-world applications, making it an excellent resource for me as a beginner turning into a professional.
One of the biggest takeaways for me was its discussion on the strategic implications of crypto for businesses. It highlighted how companies (both in and out of finance) are leveraging blockchain technology beyond just Bitcoin and Ethereum. This perspective helped me rethink how my company can better position itself in the evolving landscape—whether through enhanced security measures, regulatory compliance, or better integrations with DeFi and Web3 ecosystems.
What I loved most about this book was how it distilled complex topics—decentralization, smart contracts, crypto regulation, and enterprise adoption—into digestible insights without oversimplifying. Harvard Business Review’s approach combines expert perspectives with real-world applications, making it an excellent resource for me as a beginner turning into a professional.
One of the biggest takeaways for me was its discussion on the strategic implications of crypto for businesses. It highlighted how companies (both in and out of finance) are leveraging blockchain technology beyond just Bitcoin and Ethereum. This perspective helped me rethink how my company can better position itself in the evolving landscape—whether through enhanced security measures, regulatory compliance, or better integrations with DeFi and Web3 ecosystems.
January 11, 2020
A great way to start the year!
This book is fascinating, clear, and concise. It looks at AI from different points of view from the most prestigious scientist in the field, such as Andrew Ng. This was exactly what I need to have a clearer view of applications of machine learning in the real world. Highly recommended.
This book is fascinating, clear, and concise. It looks at AI from different points of view from the most prestigious scientist in the field, such as Andrew Ng. This was exactly what I need to have a clearer view of applications of machine learning in the real world. Highly recommended.
October 24, 2021
نکات خوبی در مورد هوش مصنوعی از زاویه تصمیم گیرندگان کسب و کارها بیان میکنه که خوندنش مخصوصا برای رهبران تجاری و استراتژیست های حوزه تکنولوژی احتمالا مفید خواهد بود.
مخصوصا دو فصل آخر، که در مورد تاثیر آینده هوش مصنوعی در تغییر استراتژی و همچنین نگاه بالا به پایین در هوش مصنوعی و لزوم کاهش داده های ورودی برای یادگیری ماشین صحبت میشه برای من جالب بود.
مخصوصا دو فصل آخر، که در مورد تاثیر آینده هوش مصنوعی در تغییر استراتژی و همچنین نگاه بالا به پایین در هوش مصنوعی و لزوم کاهش داده های ورودی برای یادگیری ماشین صحبت میشه برای من جالب بود.
September 13, 2019
An excellent collection of essay really useful for people who want to understand what AI is and the impacts.
It's highly recommended!
Many thanks to the publisher and Netgalley for this ARC, all opinions are mine.
It's highly recommended!
Many thanks to the publisher and Netgalley for this ARC, all opinions are mine.
December 16, 2019
An interesting collection of articles providing with a broad overview of what AI means for business. Best percieved if you already have some understanding of what AI is, but otherwise relatively basic concepts.
April 22, 2020
This book is written in simple language to help a non IT professional understand the scope and depth of AI. This helps you become aware of what companies are doing and what AI can and can’t do. A good read without Jargons and complex mathematical model.
March 15, 2021
If you're looking to get familiar with artificial intelligence and machine learning, you can start with this book. This is a very good collection of articles on the topic that will guide you through the history, application and future development of these technologies.
January 4, 2025
The book has amazing real world examples that are implemented by organizations and their implementation and results that can help us understand how AI is making it's way everywhere. A must read for technical background people or any AI enthusiasts.
December 14, 2025
کمی بیش از حد کلی و ساده سازی شده هست ولی برای کسانی که میخواهند ایده هایی در مورد هوش مصنوعی داشته باشند بد نیست. به نظرم منابع بسیار جذابتری وجود دارند. هم رشته محور هم پژوهش محور و حتی به زبان ساده ولی با جزییات بسیار بیشتر و ایده ها و وضع فعلی و آینده نزدیک.
January 26, 2020
Generic high-level overview
February 8, 2020
A summary of situations in AI era as I am shifting my research interest in AI and human aspects. Enjoyable.
March 12, 2020
Nice summary of the status of AI right now from a couple of articles by some leading names in the field.
June 20, 2020
great book filled with fundamentals for future work.
October 15, 2020
Very well written and eye opening
October 18, 2020
Good no nonsense, honest overview of the topic
Displaying 1 - 30 of 45 reviews