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Artificial Intelligence for Managers: Leverage the Power of AI to Transform Organizations & Reshape Your Career
Understand how to adopt and implement AI in your organization
Key Features:
7 Principles of an AI Journey
The TUSCANE Approach to Become Data Ready
The FAB-4 Model to Choose the Right AI Solution
Major AI Techniques & their Applications:
- CART & Ensemble Learning
- Clustering, Association Rules & Search
- Reinforcement Learning
- Natural Language Processing
- Image Recognition
Description:
Most AI initiatives in organizations fail today not because of a lack of good AI solutions, but because of a lack of understanding of AI among its end users, decision makers and investors. Today, organizations need managers who can leverage AI to solve business problems and provide a competitive advantage. This book is designed to enable you to fill that need, and create an edge for your career.
The chapters offer unique managerial frameworks to guide an organization's AI journey. The first section looks at what AI is; and how you can prepare for it, decide when to use it, and avoid pitfalls on the way. The second section dives into the different AI techniques and shows you where to apply them in business. The final section then prepares you from a strategic AI leadership perspective to lead the future of organizations.
By the end of the book, you will be ready to offer any organization the capability to use AI successfully and responsibly - a need that is fast becoming a necessity.
What will you learn:
Understand the major AI techniques & how they are used in business.
Determine which AI technique(s) can solve your business problem.
Decide whether to build or buy an AI solution.
Estimate the financial value of an AI solution or company.
Frame a robust policy to guide the responsible use of AI.
Who this book is for:
This book is for Executives, Managers and Students on both Business and Technical teams who would like to use Artificial Intelligence effectively to solve business problems or get an edge in their careers.
Table of Contents:
1. Preface
2. Acknowledgement
3. About the Author
4. Section 1: Beginning an AI Journey
a. AI Fundamentals
b. 7 Principles of an AI Journey
c. Getting Ready to Use AI
5. Section 2: Choosing the Right AI Techniques
a. Inside the AI Laboratory
b. How AI Predicts Values & Categories
c. How AI Understands and Predicts Behaviors & Scenarios
d. How AI Communicates & Learns from Mistakes
e. How AI Starts to Think Like Humans
6. Section 3: Using AI Successfully & Responsibly
a. AI Adoption & Valuation
b. AI Strategy, Policy & Risk Management
7. Epilogue
About the Author:
Malay A. Upadhyay is a Customer Journey executive, certified in Machine Learning. Over the course of his role heading the function at a N. American AI SaaS firm in Toronto, Malay trained 150+ N. American managers on the basics of AI and its successful adoption, held executive thought leadership sessions for CEOs and CHROs on AI strategy & IT modernization roadmaps, and worked as the primary liaison to realize AI value on unique customer datasets. It was here that he learnt the growing need for greater knowledge and awareness of how to use AI both responsibly and successfully.
Malay was also one of 25 individuals chosen globally to envision the industrial future for the Marzotto Group, Italy, on its 175th anniversary.
Key Features:
7 Principles of an AI Journey
The TUSCANE Approach to Become Data Ready
The FAB-4 Model to Choose the Right AI Solution
Major AI Techniques & their Applications:
- CART & Ensemble Learning
- Clustering, Association Rules & Search
- Reinforcement Learning
- Natural Language Processing
- Image Recognition
Description:
Most AI initiatives in organizations fail today not because of a lack of good AI solutions, but because of a lack of understanding of AI among its end users, decision makers and investors. Today, organizations need managers who can leverage AI to solve business problems and provide a competitive advantage. This book is designed to enable you to fill that need, and create an edge for your career.
The chapters offer unique managerial frameworks to guide an organization's AI journey. The first section looks at what AI is; and how you can prepare for it, decide when to use it, and avoid pitfalls on the way. The second section dives into the different AI techniques and shows you where to apply them in business. The final section then prepares you from a strategic AI leadership perspective to lead the future of organizations.
By the end of the book, you will be ready to offer any organization the capability to use AI successfully and responsibly - a need that is fast becoming a necessity.
What will you learn:
Understand the major AI techniques & how they are used in business.
Determine which AI technique(s) can solve your business problem.
Decide whether to build or buy an AI solution.
Estimate the financial value of an AI solution or company.
Frame a robust policy to guide the responsible use of AI.
Who this book is for:
This book is for Executives, Managers and Students on both Business and Technical teams who would like to use Artificial Intelligence effectively to solve business problems or get an edge in their careers.
Table of Contents:
1. Preface
2. Acknowledgement
3. About the Author
4. Section 1: Beginning an AI Journey
a. AI Fundamentals
b. 7 Principles of an AI Journey
c. Getting Ready to Use AI
5. Section 2: Choosing the Right AI Techniques
a. Inside the AI Laboratory
b. How AI Predicts Values & Categories
c. How AI Understands and Predicts Behaviors & Scenarios
d. How AI Communicates & Learns from Mistakes
e. How AI Starts to Think Like Humans
6. Section 3: Using AI Successfully & Responsibly
a. AI Adoption & Valuation
b. AI Strategy, Policy & Risk Management
7. Epilogue
About the Author:
Malay A. Upadhyay is a Customer Journey executive, certified in Machine Learning. Over the course of his role heading the function at a N. American AI SaaS firm in Toronto, Malay trained 150+ N. American managers on the basics of AI and its successful adoption, held executive thought leadership sessions for CEOs and CHROs on AI strategy & IT modernization roadmaps, and worked as the primary liaison to realize AI value on unique customer datasets. It was here that he learnt the growing need for greater knowledge and awareness of how to use AI both responsibly and successfully.
Malay was also one of 25 individuals chosen globally to envision the industrial future for the Marzotto Group, Italy, on its 175th anniversary.
180 pages, Paperback
Published September 17, 2020
11 people are currently reading
15 people want to read
About the author
Malay A. Upadhyay
10 books53 followersMalay A. Upadhyay grew up in the Eastern provinces of paradoxical India. It was a childhood of anomalies - a different spacetime, where he could not understand a friend's passion for books on one hand even as he wrote for school elocution on the other. Today, all his non-fiction works constitute matter(s) inherent to the society, organizations or the world around us.
A Duke of Edinburgh awardee, Advisor to The George Washington University School of Business's CX program and one of pioneering business leaders 2021 according to Mirror Review, Malay works as a Marketer, advisor and online instructor with an equivalent tilt towards Artificial Intelligence and its responsible usage. He conceived many of the techno-economic ideas described in his fictional book - Kalki Evian: The Ring of Khaoriphea - at Bocconi University in Milano. His extended profile can be seen at www.theupadhyays.com.
At other times, Malay is a fly who loves to travel with Mrs. Fly and discover the elusively effervescent, ephemeral connection among beings across space and time. That is after all, a belief that underlies every piece of literature ever written.
A Duke of Edinburgh awardee, Advisor to The George Washington University School of Business's CX program and one of pioneering business leaders 2021 according to Mirror Review, Malay works as a Marketer, advisor and online instructor with an equivalent tilt towards Artificial Intelligence and its responsible usage. He conceived many of the techno-economic ideas described in his fictional book - Kalki Evian: The Ring of Khaoriphea - at Bocconi University in Milano. His extended profile can be seen at www.theupadhyays.com.
At other times, Malay is a fly who loves to travel with Mrs. Fly and discover the elusively effervescent, ephemeral connection among beings across space and time. That is after all, a belief that underlies every piece of literature ever written.
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Displaying 1 - 14 of 14 reviews
December 23, 2021
This was a great book. I enjoy reading about artificial intelligence will aid managers for any companies. The leadership skills will provide great information for a career.
March 17, 2021
A well written and coherently organized book for people looking to get into AI.
What I absolutely loved was how everything was so structured. The language is easy follow with relevant graphs and diagrams. The questions at the end of each chapter makes it a perfect self learning material.
My favourite part is actually the beginning itself where the author in very simple everyday example explains AI. That itself sets the tone of the book - informative but not too heavy.
Just a teeny tiny thing that I didn't like is that one of it's strength itself which becomes a problem i.e the structure. Yes the text is well structured but in few places it is so differentiated that becomes a little difficult to follow (or maybe just for me!).
But other than that it's a wholesome read. Definitely recommend.
What I absolutely loved was how everything was so structured. The language is easy follow with relevant graphs and diagrams. The questions at the end of each chapter makes it a perfect self learning material.
My favourite part is actually the beginning itself where the author in very simple everyday example explains AI. That itself sets the tone of the book - informative but not too heavy.
Just a teeny tiny thing that I didn't like is that one of it's strength itself which becomes a problem i.e the structure. Yes the text is well structured but in few places it is so differentiated that becomes a little difficult to follow (or maybe just for me!).
But other than that it's a wholesome read. Definitely recommend.
April 17, 2021
For decades, followers of technology have touted the value of Artificial Intelligence (AI) in computing. Some present a utopian future; others present a dystopian future. In this work, Upadhyay presents a realistic assessment of what’s inevitably coming. He overviews the essential parts of the technology – like convoluted neural networks or K-nearest-neighbor mapping – and then speculates on their business value.
At 178 pages, this work does not waste unnecessary words. It instead provides a quick overview of the theory, illustrations to aid understanding, an example or two to bring the idea to life, and a business assessment of the ideas’ potential impacts. It presents nothing especially earth-shattering as the contents are well-established in the research literature. Instead, it brings it to life within the context of an organization and aims to make the reader the subject-matter expert in her/his context.
The strength of Upadhyay’s analysis lies in its levelheadedness. He acknowledges that correct decisions in the near future must be made regarding this technology. Success is neither guaranteed nor automatic. Ethics about privacy, social impact, job security, and financial risk need to be considered as companies seek to adopt AI software into its practices. The author presents a realistic picture of these challenges, neither overly optimistic nor patently pessimistic. The business community should therefore welcome his assessment.
This book’s obvious audience consists primarily of those in the business community and those who might manage AI projects. Although this book is not technical and does not outline programming procedures, the ambitious computer scientist might also benefit from its pages. Understanding the business and how the human and economic sides work can aid software developers. Finally, those who might benefit from understanding AI’s economic impact, like policymakers and social prognosticators, can also benefit from perusing its pages.
It’s also worth noting that this book is published on the Indian subcontinent. It speaks to the up-and-coming technological prowess of that country. Upadhyay has shone a light on the intersection of AI and business for all of us to see. He shows how AI computing can make organizations more productive in the near future. It is no longer an out-there, far-off idea. Instead, it is becoming nearer to ever-fuller adoption, and the savvy businessperson will attend to its impacts with wisdom. This book certainly makes those who read it wiser for that future day.
At 178 pages, this work does not waste unnecessary words. It instead provides a quick overview of the theory, illustrations to aid understanding, an example or two to bring the idea to life, and a business assessment of the ideas’ potential impacts. It presents nothing especially earth-shattering as the contents are well-established in the research literature. Instead, it brings it to life within the context of an organization and aims to make the reader the subject-matter expert in her/his context.
The strength of Upadhyay’s analysis lies in its levelheadedness. He acknowledges that correct decisions in the near future must be made regarding this technology. Success is neither guaranteed nor automatic. Ethics about privacy, social impact, job security, and financial risk need to be considered as companies seek to adopt AI software into its practices. The author presents a realistic picture of these challenges, neither overly optimistic nor patently pessimistic. The business community should therefore welcome his assessment.
This book’s obvious audience consists primarily of those in the business community and those who might manage AI projects. Although this book is not technical and does not outline programming procedures, the ambitious computer scientist might also benefit from its pages. Understanding the business and how the human and economic sides work can aid software developers. Finally, those who might benefit from understanding AI’s economic impact, like policymakers and social prognosticators, can also benefit from perusing its pages.
It’s also worth noting that this book is published on the Indian subcontinent. It speaks to the up-and-coming technological prowess of that country. Upadhyay has shone a light on the intersection of AI and business for all of us to see. He shows how AI computing can make organizations more productive in the near future. It is no longer an out-there, far-off idea. Instead, it is becoming nearer to ever-fuller adoption, and the savvy businessperson will attend to its impacts with wisdom. This book certainly makes those who read it wiser for that future day.
June 27, 2024
It is a great book, that is in simple language without any code snippets because as the author cleared in the title that book is for managers to understand the AI Journey, various AI techniques, and risks.
AI has generated a lot of curiosity in business managers; However, many Managers still struggle to appreciate How AI works and whether they can apply AI to their business case.
The book title is quite intriguing and comprised of 3 Sections covering 10 Chapters and has a wonderful example of Maya's robot referred to from the first chapter till the end of the book for conceptual clarity.
𝐖𝐡𝐞𝐭𝐡𝐞𝐫 𝐰𝐞 𝐭𝐡𝐢𝐧𝐤 𝐀𝐈 𝐢𝐬 𝐝𝐚𝐧𝐠𝐞𝐫𝐨𝐮𝐬 𝐨𝐫 𝐚 𝐠𝐢𝐟𝐭, 𝐰𝐞 𝐡𝐚𝐯𝐞 𝐭𝐨 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐢𝐭 𝐩𝐫𝐨𝐩𝐞𝐫𝐥𝐲 𝐟𝐢𝐫𝐬𝐭. 𝐀𝐧𝐝 𝐭𝐡𝐚𝐭 𝐛𝐫𝐢𝐧𝐠𝐬 𝐮𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦 𝐚𝐭 𝐡𝐚𝐧𝐝.
Most AI initiatives fail today not because of a lack of good solutions but because of one or more of the following issues on the management side:
• Lack of understanding of what AI is and why/when it can be powerful
• Unrealistic expectations of what AI can do
• Absence of a proper business strategy in place around AI
• Wrong choice of the type of AI technique for a business problem
• Uninformed choice of a weak/superficial AI solution
• Lack of readiness in terms of data
• Lack of employee and/or leadership support.
The growth and success of AI depend on the support and investment it receives from informed current and future organizational leaders and managers. After all, they are the sponsors, decision-makers, and end-users of AI.
What is also boosting our need for AI is our declining cognitive ability: the more we use phones and other digital technologies, the more distracted we become.
AI is also timing itself well to converge neatly with Blockchain and the Internet of Things (IoT).
𝐁𝐥𝐨𝐜𝐤𝐜𝐡𝐚𝐢𝐧 𝐜𝐚𝐧 𝐛𝐮𝐢𝐥𝐝 𝐬𝐞𝐜𝐮𝐫𝐞 𝐧𝐞𝐭𝐰𝐨𝐫𝐤𝐬 𝐚𝐧𝐝 𝐮𝐧𝐞𝐧𝐝𝐢𝐧𝐠 𝐭𝐫𝐚𝐢𝐥𝐬 𝐨𝐟 𝐝𝐚𝐭𝐚 𝐟𝐫𝐨𝐦 𝐰𝐡𝐢𝐜𝐡 𝐀𝐈 𝐜𝐚𝐧 𝐞𝐱𝐭𝐫𝐚𝐜𝐭 𝐦𝐞𝐚𝐧𝐢𝐧𝐠𝐟𝐮𝐥 𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐞𝐧𝐚𝐛𝐥𝐞 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐈𝐨𝐓 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐨 𝐩𝐞𝐫𝐟𝐨𝐫𝐦 𝐭𝐡𝐞𝐢𝐫 𝐚𝐜𝐭𝐢𝐨𝐧𝐬 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭𝐥𝐲 𝐚𝐧𝐝 𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐲!
𝐓𝐡𝐞 𝐠𝐫𝐨𝐰𝐭𝐡 𝐰𝐚𝐬 𝐮𝐧𝐝𝐞𝐫𝐥𝐢𝐧𝐞𝐝 𝐢𝐧 2017 𝐛𝐲 𝐑𝐮𝐬𝐬𝐢𝐚𝐧 𝐏𝐫𝐞𝐬𝐢𝐝𝐞𝐧𝐭 𝐕𝐥𝐚𝐝𝐢𝐦𝐢𝐫 𝐏𝐮𝐭𝐢𝐧, 𝐰𝐡𝐨 𝐬𝐚𝐢𝐝 𝐭𝐡𝐚𝐭 𝐰𝐡𝐨𝐞𝐯𝐞𝐫 𝐛𝐞𝐜𝐨𝐦𝐞𝐬 𝐭𝐡𝐞 𝐥𝐞𝐚𝐝𝐞𝐫 𝐢𝐧 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐛𝐞𝐜𝐨𝐦𝐞 𝐭𝐡𝐞 𝐫𝐮𝐥𝐞𝐫 𝐨𝐟 𝐭𝐡𝐞 𝐰𝐨𝐫𝐥𝐝.
𝐈𝐭 𝐰𝐚𝐬 𝐬𝐨𝐨𝐧 𝐟𝐨𝐥𝐥𝐨𝐰𝐞𝐝 𝐛𝐲 𝐒𝐩𝐚𝐜𝐞𝐗 𝐚𝐧𝐝 𝐓𝐞𝐬𝐥𝐚 𝐂𝐄𝐎 𝐄𝐥𝐨𝐧 𝐌𝐮𝐬𝐤, 𝐰𝐡𝐨 𝐚𝐝𝐝𝐞𝐝 𝐭𝐡𝐚𝐭 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐢𝐨𝐧 𝐢𝐧 𝐀𝐈 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐚𝐭 𝐭𝐡𝐞 𝐧𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐥𝐞𝐯𝐞𝐥 𝐰𝐨𝐮𝐥𝐝 𝐦𝐨𝐬𝐭 𝐥𝐢𝐤𝐞𝐥𝐲 𝐛𝐞 𝐭𝐡𝐞 𝐜𝐚𝐮𝐬𝐞 𝐨𝐟 𝐖𝐖3.
I do realize that this title is a must for all managers whose role is just not to manage the team's activities but to make informed decisions, choose the right data, and prepare the mindset of resources within the team to accept and get the results out of AI solutions.
Author, Maya, already described various existing AI-enabled tools, and applications. Also, make clear by giving options like Build AI solutions, and Buy AI solutions based on the need, data, existing resource capabilities, and requirements of the organization.
Moreover as mentioned in the book - managers don't need to learn code to use and understand AI. ML, NPL, and Deep learning concepts are described with the help of use cases.
Seven principles should always be kept in mind while adopting AI:
1. Have all data in one place or have them seamlessly connected to one system.
2. As a first step, break down the core problem into specific use cases that may or may not be solved by AI.
3. Choose the software that's the right fit for your needs, budget & existing organizational systems, and processes, rather than going for the most popular ones.
4. Choose AI software that can show the rationale behind its analysis, especially for critical tasks and decision-making.
5. Ensure that data is proper and ready for AI use.
6. Effective AI requires proper adoption by the users, the right processes to support it, the right measures to keep it working properly, and only the desired degree of disruption to existing systems and processes.
7. Not all solutions have to be AI.
The data required for an AI solution should always fulfill a set of conditions.
For ease of remembering, let's call these conditions, TUSCANE:
1. Timely, which means that it is either up to date, getting updated regularly, or belonging to the time that is being analyzed.
2. Usable, which generally requires data to be in one place and available without restrictions so that it can be easily accessed.
3. Structured. For a business manager, 'structure' implies a dataset that is not effectively garbage and devoid of logic, relevance, or analysis to the problem that AI is supposed to solve.
4. Complete. Incomplete data has to be dealt with and filled out for AI to properly analyze information.
5. Accurate. Inaccurate or erroneous data is the number one reason for inaccurate results.
6. Neutral and not biased. The number two reason for inaccurate results and the number one reason to think about AI ethics is bias. Bias in data is often difficult to catch and can lead to insights that appear accurate at first but cease to be if the situation changes. Worse, the insights may continue to appear accurate even if they are not.
7. Enough. Techniques like Deep Learning or even Machine Learning require a lot of data to be effective.
An AI journey requires an investment of time and money, training of both the AI model and its end users, and policies to govern its performance effectively and ethically.
All of these tie into the organizational strategy.
There are a few best practices that can help weave a clear strategy around AI. These include:
• Start small, with a low-risk pilot
• Gauge the level of support and expectations from the leadership
• Be clear on why a team wants to use AI before undertaking a project
• Involve managers from all relevant teams to gauge project feasibility
• Identify the roles, responsibilities, and accountabilities.
Technology brings some risks and accordingly benefits and responsibilities to decision-makers, managers, end users, and sponsors so AI is not risk-proof. So, benefits, and risks are honestly mentioned.
Here is a quote available in the book: 𝐍𝐨 𝐚𝐫𝐦𝐲 𝐜𝐚𝐧 𝐬𝐭𝐨𝐩 𝐚𝐧 𝐢𝐝𝐞𝐚 𝐰𝐡𝐨𝐬𝐞 𝐭𝐢𝐦𝐞 𝐡𝐚𝐬 𝐜𝐨𝐦𝐞 - 𝐕𝐢𝐜𝐭𝐨𝐫 𝐇𝐮𝐠𝐨
I would recommend this book to everyone to understand AI in a simplistic approach.
AI has generated a lot of curiosity in business managers; However, many Managers still struggle to appreciate How AI works and whether they can apply AI to their business case.
The book title is quite intriguing and comprised of 3 Sections covering 10 Chapters and has a wonderful example of Maya's robot referred to from the first chapter till the end of the book for conceptual clarity.
𝐖𝐡𝐞𝐭𝐡𝐞𝐫 𝐰𝐞 𝐭𝐡𝐢𝐧𝐤 𝐀𝐈 𝐢𝐬 𝐝𝐚𝐧𝐠𝐞𝐫𝐨𝐮𝐬 𝐨𝐫 𝐚 𝐠𝐢𝐟𝐭, 𝐰𝐞 𝐡𝐚𝐯𝐞 𝐭𝐨 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐢𝐭 𝐩𝐫𝐨𝐩𝐞𝐫𝐥𝐲 𝐟𝐢𝐫𝐬𝐭. 𝐀𝐧𝐝 𝐭𝐡𝐚𝐭 𝐛𝐫𝐢𝐧𝐠𝐬 𝐮𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦 𝐚𝐭 𝐡𝐚𝐧𝐝.
Most AI initiatives fail today not because of a lack of good solutions but because of one or more of the following issues on the management side:
• Lack of understanding of what AI is and why/when it can be powerful
• Unrealistic expectations of what AI can do
• Absence of a proper business strategy in place around AI
• Wrong choice of the type of AI technique for a business problem
• Uninformed choice of a weak/superficial AI solution
• Lack of readiness in terms of data
• Lack of employee and/or leadership support.
The growth and success of AI depend on the support and investment it receives from informed current and future organizational leaders and managers. After all, they are the sponsors, decision-makers, and end-users of AI.
What is also boosting our need for AI is our declining cognitive ability: the more we use phones and other digital technologies, the more distracted we become.
AI is also timing itself well to converge neatly with Blockchain and the Internet of Things (IoT).
𝐁𝐥𝐨𝐜𝐤𝐜𝐡𝐚𝐢𝐧 𝐜𝐚𝐧 𝐛𝐮𝐢𝐥𝐝 𝐬𝐞𝐜𝐮𝐫𝐞 𝐧𝐞𝐭𝐰𝐨𝐫𝐤𝐬 𝐚𝐧𝐝 𝐮𝐧𝐞𝐧𝐝𝐢𝐧𝐠 𝐭𝐫𝐚𝐢𝐥𝐬 𝐨𝐟 𝐝𝐚𝐭𝐚 𝐟𝐫𝐨𝐦 𝐰𝐡𝐢𝐜𝐡 𝐀𝐈 𝐜𝐚𝐧 𝐞𝐱𝐭𝐫𝐚𝐜𝐭 𝐦𝐞𝐚𝐧𝐢𝐧𝐠𝐟𝐮𝐥 𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐞𝐧𝐚𝐛𝐥𝐞 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐈𝐨𝐓 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐨 𝐩𝐞𝐫𝐟𝐨𝐫𝐦 𝐭𝐡𝐞𝐢𝐫 𝐚𝐜𝐭𝐢𝐨𝐧𝐬 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭𝐥𝐲 𝐚𝐧𝐝 𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐲!
𝐓𝐡𝐞 𝐠𝐫𝐨𝐰𝐭𝐡 𝐰𝐚𝐬 𝐮𝐧𝐝𝐞𝐫𝐥𝐢𝐧𝐞𝐝 𝐢𝐧 2017 𝐛𝐲 𝐑𝐮𝐬𝐬𝐢𝐚𝐧 𝐏𝐫𝐞𝐬𝐢𝐝𝐞𝐧𝐭 𝐕𝐥𝐚𝐝𝐢𝐦𝐢𝐫 𝐏𝐮𝐭𝐢𝐧, 𝐰𝐡𝐨 𝐬𝐚𝐢𝐝 𝐭𝐡𝐚𝐭 𝐰𝐡𝐨𝐞𝐯𝐞𝐫 𝐛𝐞𝐜𝐨𝐦𝐞𝐬 𝐭𝐡𝐞 𝐥𝐞𝐚𝐝𝐞𝐫 𝐢𝐧 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐛𝐞𝐜𝐨𝐦𝐞 𝐭𝐡𝐞 𝐫𝐮𝐥𝐞𝐫 𝐨𝐟 𝐭𝐡𝐞 𝐰𝐨𝐫𝐥𝐝.
𝐈𝐭 𝐰𝐚𝐬 𝐬𝐨𝐨𝐧 𝐟𝐨𝐥𝐥𝐨𝐰𝐞𝐝 𝐛𝐲 𝐒𝐩𝐚𝐜𝐞𝐗 𝐚𝐧𝐝 𝐓𝐞𝐬𝐥𝐚 𝐂𝐄𝐎 𝐄𝐥𝐨𝐧 𝐌𝐮𝐬𝐤, 𝐰𝐡𝐨 𝐚𝐝𝐝𝐞𝐝 𝐭𝐡𝐚𝐭 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐢𝐨𝐧 𝐢𝐧 𝐀𝐈 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐚𝐭 𝐭𝐡𝐞 𝐧𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐥𝐞𝐯𝐞𝐥 𝐰𝐨𝐮𝐥𝐝 𝐦𝐨𝐬𝐭 𝐥𝐢𝐤𝐞𝐥𝐲 𝐛𝐞 𝐭𝐡𝐞 𝐜𝐚𝐮𝐬𝐞 𝐨𝐟 𝐖𝐖3.
I do realize that this title is a must for all managers whose role is just not to manage the team's activities but to make informed decisions, choose the right data, and prepare the mindset of resources within the team to accept and get the results out of AI solutions.
Author, Maya, already described various existing AI-enabled tools, and applications. Also, make clear by giving options like Build AI solutions, and Buy AI solutions based on the need, data, existing resource capabilities, and requirements of the organization.
Moreover as mentioned in the book - managers don't need to learn code to use and understand AI. ML, NPL, and Deep learning concepts are described with the help of use cases.
Seven principles should always be kept in mind while adopting AI:
1. Have all data in one place or have them seamlessly connected to one system.
2. As a first step, break down the core problem into specific use cases that may or may not be solved by AI.
3. Choose the software that's the right fit for your needs, budget & existing organizational systems, and processes, rather than going for the most popular ones.
4. Choose AI software that can show the rationale behind its analysis, especially for critical tasks and decision-making.
5. Ensure that data is proper and ready for AI use.
6. Effective AI requires proper adoption by the users, the right processes to support it, the right measures to keep it working properly, and only the desired degree of disruption to existing systems and processes.
7. Not all solutions have to be AI.
The data required for an AI solution should always fulfill a set of conditions.
For ease of remembering, let's call these conditions, TUSCANE:
1. Timely, which means that it is either up to date, getting updated regularly, or belonging to the time that is being analyzed.
2. Usable, which generally requires data to be in one place and available without restrictions so that it can be easily accessed.
3. Structured. For a business manager, 'structure' implies a dataset that is not effectively garbage and devoid of logic, relevance, or analysis to the problem that AI is supposed to solve.
4. Complete. Incomplete data has to be dealt with and filled out for AI to properly analyze information.
5. Accurate. Inaccurate or erroneous data is the number one reason for inaccurate results.
6. Neutral and not biased. The number two reason for inaccurate results and the number one reason to think about AI ethics is bias. Bias in data is often difficult to catch and can lead to insights that appear accurate at first but cease to be if the situation changes. Worse, the insights may continue to appear accurate even if they are not.
7. Enough. Techniques like Deep Learning or even Machine Learning require a lot of data to be effective.
An AI journey requires an investment of time and money, training of both the AI model and its end users, and policies to govern its performance effectively and ethically.
All of these tie into the organizational strategy.
There are a few best practices that can help weave a clear strategy around AI. These include:
• Start small, with a low-risk pilot
• Gauge the level of support and expectations from the leadership
• Be clear on why a team wants to use AI before undertaking a project
• Involve managers from all relevant teams to gauge project feasibility
• Identify the roles, responsibilities, and accountabilities.
Technology brings some risks and accordingly benefits and responsibilities to decision-makers, managers, end users, and sponsors so AI is not risk-proof. So, benefits, and risks are honestly mentioned.
Here is a quote available in the book: 𝐍𝐨 𝐚𝐫𝐦𝐲 𝐜𝐚𝐧 𝐬𝐭𝐨𝐩 𝐚𝐧 𝐢𝐝𝐞𝐚 𝐰𝐡𝐨𝐬𝐞 𝐭𝐢𝐦𝐞 𝐡𝐚𝐬 𝐜𝐨𝐦𝐞 - 𝐕𝐢𝐜𝐭𝐨𝐫 𝐇𝐮𝐠𝐨
I would recommend this book to everyone to understand AI in a simplistic approach.
June 30, 2024
Artificial Intelligence for Managers is a detailed guide on the integration of AI within business settings, covering an array of topics such as image recognition, text analysis, behavior prediction, and decision-making. The book underscores the significance of transparent AI solutions and accurate data for effective analysis. It delves into various AI techniques like K-nearest neighbors (KNN), support vector machines (SVM), and deep learning, providing practical examples of their applications. Additionally, the book discusses the ethical and operational aspects of AI, emphasizing the importance of policy framing and the principles governing human-AI work relationships. The content is presented with a well-structured approach, supplemented by questions at the end of each chapter to enhance learning.
While Artificial Intelligence for Managers offers a comprehensive overview of AI and its business applications, it falls short in certain areas, which ultimately affects its overall impact. One of the notable strengths of the book is its thorough exploration of AI techniques and their practical applications. The author does an admirable job of explaining complex concepts in an accessible manner, making it suitable for both business professionals and those with a technical background.
However, the book's major drawback is its verbosity. At 178 pages, the text often feels overly detailed, with extensive explanations that could have been more succinct. This wordiness detracts from the main points and can make the reading experience tedious. The structure, while generally helpful, sometimes becomes overly segmented, making it challenging to follow the flow of ideas seamlessly.
Another strength of the book is its balanced perspective on the ethical and operational aspects of AI integration. The author provides a realistic view of the challenges and opportunities associated with AI, neither overly optimistic nor unduly pessimistic. This balanced approach is refreshing and adds credibility to the discussion.
Despite these positives, the book could benefit from more practical case studies or real-world examples to illustrate the concepts better. While theoretical explanations are valuable, concrete examples from actual business scenarios would enhance the reader's understanding and provide more actionable insights.
In conclusion, Artificial Intelligence for Managers is a well-structured and informative resource, offering valuable insights into the application of AI in business. However, its excessive wordiness and sometimes overly segmented structure make it less engaging than it could be. For those willing to sift through the verbose sections, the book provides a solid foundation in understanding and leveraging AI for business success.
While Artificial Intelligence for Managers offers a comprehensive overview of AI and its business applications, it falls short in certain areas, which ultimately affects its overall impact. One of the notable strengths of the book is its thorough exploration of AI techniques and their practical applications. The author does an admirable job of explaining complex concepts in an accessible manner, making it suitable for both business professionals and those with a technical background.
However, the book's major drawback is its verbosity. At 178 pages, the text often feels overly detailed, with extensive explanations that could have been more succinct. This wordiness detracts from the main points and can make the reading experience tedious. The structure, while generally helpful, sometimes becomes overly segmented, making it challenging to follow the flow of ideas seamlessly.
Another strength of the book is its balanced perspective on the ethical and operational aspects of AI integration. The author provides a realistic view of the challenges and opportunities associated with AI, neither overly optimistic nor unduly pessimistic. This balanced approach is refreshing and adds credibility to the discussion.
Despite these positives, the book could benefit from more practical case studies or real-world examples to illustrate the concepts better. While theoretical explanations are valuable, concrete examples from actual business scenarios would enhance the reader's understanding and provide more actionable insights.
In conclusion, Artificial Intelligence for Managers is a well-structured and informative resource, offering valuable insights into the application of AI in business. However, its excessive wordiness and sometimes overly segmented structure make it less engaging than it could be. For those willing to sift through the verbose sections, the book provides a solid foundation in understanding and leveraging AI for business success.
October 10, 2021
Fantastic work by Malay A. Upadhyay. Artificial Intelligence for Managers : Leverage the power of AI to transform Organisations and Reshape your career.
This book is in simple language without any code snippets because as author cleared in the title that book is for managers to understand AI Journey , various AI techniques and risks.
Book title is quite intriguing and comprised of 3 Sections covering 10 Chapters and having wonderful example of Maya's robot 🤖 referred from first chapter till end of the book for conceptual clarity.
I do realised that this title is must for all managers whose role is just not to manage the teams activities but to make informed decisions , choose the right data , prepare the mindset of resources within team to accept and get the results out of AI solutions.
Author already described various existing AI enabled tools , applications. Also , make clear by giving options like Build AI solutions , Buy AI solutions on basis of the need , data , existing resource capabilities and requirements of the organization.
Moreover as mentioned in the book - managers don't need to learn code to use and understand AI. ML , NPL , Deep learning concepts are described with help of use cases.
Each chapter is concluded and followed by Question and Answers to check the understanding of various use cases , techniques and concepts. Reference of Youtube videos , pictures and quotes could helpful for understanding and keeping subject intresting.
Technology brings some risks and accordingly benefits and responsibilities on decision makers , managers , end users and sponsors so AI is no risk proof. So benefits, risks are honestly mentioned.
Here is quote available in book : No army can stop an idea whose time has come - Victor Hugo
I would recommend this book to everyone to understand AI in simplistic approach.
This book is in simple language without any code snippets because as author cleared in the title that book is for managers to understand AI Journey , various AI techniques and risks.
Book title is quite intriguing and comprised of 3 Sections covering 10 Chapters and having wonderful example of Maya's robot 🤖 referred from first chapter till end of the book for conceptual clarity.
I do realised that this title is must for all managers whose role is just not to manage the teams activities but to make informed decisions , choose the right data , prepare the mindset of resources within team to accept and get the results out of AI solutions.
Author already described various existing AI enabled tools , applications. Also , make clear by giving options like Build AI solutions , Buy AI solutions on basis of the need , data , existing resource capabilities and requirements of the organization.
Moreover as mentioned in the book - managers don't need to learn code to use and understand AI. ML , NPL , Deep learning concepts are described with help of use cases.
Each chapter is concluded and followed by Question and Answers to check the understanding of various use cases , techniques and concepts. Reference of Youtube videos , pictures and quotes could helpful for understanding and keeping subject intresting.
Technology brings some risks and accordingly benefits and responsibilities on decision makers , managers , end users and sponsors so AI is no risk proof. So benefits, risks are honestly mentioned.
Here is quote available in book : No army can stop an idea whose time has come - Victor Hugo
I would recommend this book to everyone to understand AI in simplistic approach.
June 20, 2024
Artificial Intelligence for Managers is fundamentally a textbook, designed as a minicourse in AI. Its 3 sections, entitled Beginning an AI Journey, Choosing the Right AI Techniques, and Using AI Successfully and Responsibly come with chapters which each contain explanations, summaries, and quizzes. The thought behind the creation of this text is that, according to the author, most current attempts to use AI fail due to lack of understanding, unrealistic expectations, bad strategy (either no strategy, wrong strategy or uninformed strategy), lack of applicable data or lack of leadership support, and that adherence to this text may ameliorate chances for success. The first section explains the differences between artificial intelligence (AI), machine learning (ML), deep learning (DL) and business intelligence (BI) It lists 7 principles which must be met, including identifying the core problem which AI should address, choosing the best fit of AI applications, and bringing all data into one system to interconnect solutions. Finally, section 1 introduces acronyms which enable the user to have a common language, such as TUSCANE and FAB-1. Section 2 introduces the more technical AI uses, describing Boosting Techniques, Decision Trees, Ensemble Learning, and Hierarchical or K Means clustering. Section 3 guides the reader in successful and responsible AI management, discussing valuation of AI results and risk assessment.
It stands to reason that a company sufficiently modernized to be implementing an AI program should have an AI specialist who is trained in all aspects introduced in this book.
It stands to reason that a company sufficiently modernized to be implementing an AI program should have an AI specialist who is trained in all aspects introduced in this book.
December 6, 2021
AI for Managers is an Awesome book. AI has generated lot of curiosity in business managers, However lot of Managers still struggle to appreciate How the AI works and whether they can apply AI to their business case.
Lot of discussion on AI available on Internet or books is technology intensive and mathematically rigorous.
Book is appropriately suited to managers as the language is simple to understand without rigorous mathematics.
One will be able to appreciate
The difference between traditionally programming and AI.
To what business problems can AI be applied.
How various Machine learning approaches work.
Book goes deep to cover aspects like Artificial Neural Networks.
Various nuances of business decision making, as to whether, the AI solution is deployable is delved in detail.
Author makes use of everyday examples to elucidiate AI concepts, Which makes it useful for students and educators alike.
Book is an inspiring read for enthusiast like me who were jittery to step into stormy waters of technically daunting literature on AI.
Book is unique in its coverage, presentation and language, A must read.
Lot of discussion on AI available on Internet or books is technology intensive and mathematically rigorous.
Book is appropriately suited to managers as the language is simple to understand without rigorous mathematics.
One will be able to appreciate
The difference between traditionally programming and AI.
To what business problems can AI be applied.
How various Machine learning approaches work.
Book goes deep to cover aspects like Artificial Neural Networks.
Various nuances of business decision making, as to whether, the AI solution is deployable is delved in detail.
Author makes use of everyday examples to elucidiate AI concepts, Which makes it useful for students and educators alike.
Book is an inspiring read for enthusiast like me who were jittery to step into stormy waters of technically daunting literature on AI.
Book is unique in its coverage, presentation and language, A must read.
February 16, 2022
The book is a great start to understanding how can you use AI and applicationally what AI is rather than textbooky "how" version of AI understanding. Simple yet clear examples to relate with the explanations and what one can expect to get an outlook on its effects, and gives us a chance to stop and think to make our decisions unlike forcing a decision or a statement as a solution, more like makes us to fit the solution in the given framework and situation. Some parts are a bit confusing until sources are referred and the questions at the end of every chapter really help in looking back and see what we have learnt. Its a journey from the basics of what we need to know about AI and advancing a step a time to apply it in our daily lives.
May 14, 2021
Upadhyah presents AI in computing with a realistic approach for his audience, who are, undoubtedly, the business community. His writing prose is simple and straight to the point; he provides an overview of his thesis followed by examples, assessments, and potential impacts without sugar-coating - His presentation is a balanced view, which he leaves for the reader to use their own initiative.
I read this book in one sitting and, without doubt, it made me wiser! – I highly recommend this book to the business community. It’s worth a read!
I read this book in one sitting and, without doubt, it made me wiser! – I highly recommend this book to the business community. It’s worth a read!
February 2, 2022
Easy to understand book for beginners
Lots of books are available for the given subject but the way concepts are explained by the author in this one is different. What makes it unique is the simplicity and clarity with which things are explained. I grew fond of Maya’s robot in particular.
Each chapter is concluded properly in the end followed by self-check questionnaire. Overall, it is a comprehensive beginner’s guide to AI starting with Fundamentals till the Risk Management. Liked the book :)
Lots of books are available for the given subject but the way concepts are explained by the author in this one is different. What makes it unique is the simplicity and clarity with which things are explained. I grew fond of Maya’s robot in particular.
Each chapter is concluded properly in the end followed by self-check questionnaire. Overall, it is a comprehensive beginner’s guide to AI starting with Fundamentals till the Risk Management. Liked the book :)
May 10, 2024
I reviewed another book about artificial intelligence written by this author, and I found this one easier to get along with. I think AI is quite mind-boggling and I can't say I'm an expert after reading this. However, I felt this one was easier to digest. There was still plenty of information but it didn't seem like an information overload; I felt there were more bullet pointed lists and diagrams to break up the text and illustrate the points. The questions section at the end of each chapter was a good idea too.
May 17, 2021
Almost every business can benefit from AI and Upadhyay paves the way for successful adoption, providing not only the how, but the why, which is just as important. With end-of-chapter questions, the book is perfect as a text for students.
August 31, 2024
This book is a very well organised one. Which tells about how AI helps in the corporate world.
The chapters and the description are easy to grasp.
If we research well and adopt this books key points it will help as managers aid.
Liked the book.
The chapters and the description are easy to grasp.
If we research well and adopt this books key points it will help as managers aid.
Liked the book.
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