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AI Value Creators: Beyond the Generative AI User Mindset
We've arrived in a new era—GenAI is reshaping industries and decision-making processes across the board. As a result, understanding their potential and pitfalls has become crucial. But in order to stay ahead of the curve, you'll need to develop fresh perspectives on leveraging AI beyond mere technical know-how. Geared toward business leaders and tech professionals alike, this book demystifies the strategic integration of AI into business practices, ensuring you're equipped not just to participate but to lead in this new landscape.
This insightful guide by industry leaders Rob Thomas, Paul Zikopoulos, and Kate Soule goes beyond the basics, offering real-life success stories and learned lessons to provide a blueprint for meaningful AI engagement. Whether you're a novice or a seasoned expert, you'll come away with an enhanced understanding of GenAI.
● Recognize the transformative potential of AI in business and how to harness it
● Navigate the ethical and operational challenges posed by AI with confidence
● Implement actionable strategies to integrate AI into your organizational culture
● Step confidently into the role of an AI value creator, equipped to lead and innovate
This insightful guide by industry leaders Rob Thomas, Paul Zikopoulos, and Kate Soule goes beyond the basics, offering real-life success stories and learned lessons to provide a blueprint for meaningful AI engagement. Whether you're a novice or a seasoned expert, you'll come away with an enhanced understanding of GenAI.
● Recognize the transformative potential of AI in business and how to harness it
● Navigate the ethical and operational challenges posed by AI with confidence
● Implement actionable strategies to integrate AI into your organizational culture
● Step confidently into the role of an AI value creator, equipped to lead and innovate
297 pages, Paperback
Published May 6, 2025
22 people are currently reading
48 people want to read
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Displaying 1 - 5 of 5 reviews
April 9, 2025
This book is fresh out of the oven, updated with the latest in the GenAI space (including DeepSeek R1) and a good read for engineering and business leaders. Like all tech books, parts of it may get dated very soon - but right now it is a fantastic read.
The authors talk about adoption of AI in the enterprise to generate value for their customers, which is something I don't believe 99% of the "AI-powered" crap peddlers understand. Almost everything you read and watch about AI today is dumbed down, so books like this are a fresh breathe of air.
Among other things, the book talks about gradual AI adoption ("+AI to AI+"), governance challenges and customization. Though none of these are mind-blowing ideas, the book presents a coherent picture of how businesses may evolve by leveraging AI effectively.
Some bits are unnecessarily verbose and the humor feels somewhat forced at times but nevertheless it is a good book. Treat this a good set of essays and you won't be disappointed.
The authors talk about adoption of AI in the enterprise to generate value for their customers, which is something I don't believe 99% of the "AI-powered" crap peddlers understand. Almost everything you read and watch about AI today is dumbed down, so books like this are a fresh breathe of air.
Among other things, the book talks about gradual AI adoption ("+AI to AI+"), governance challenges and customization. Though none of these are mind-blowing ideas, the book presents a coherent picture of how businesses may evolve by leveraging AI effectively.
Some bits are unnecessarily verbose and the humor feels somewhat forced at times but nevertheless it is a good book. Treat this a good set of essays and you won't be disappointed.
May 31, 2025
A good introduction to the ways artificial intelligence is shaping modern business and innovation. The book touches on some interesting case studies and provides a few useful frameworks for thinking about value creation in the AI era. For readers new to the topic, it might serve as a reasonable starting point.
My expectations were a deeper dive into the value creation if utilization of business data to help bring value faster to the organization. Many of the insights were more surface-level, and some sections repeated. There were a few items shared that were more like promotional material for IBM, but that is the environment the authors knew best.
It is a positive read. If you are curious about AI and business, you will find a few nuggets in these pages, but for the seasoned AI readers this will be a review till you get to the final chapter and then there is more sharing of the next possible steps in the Generative AI space.
My expectations were a deeper dive into the value creation if utilization of business data to help bring value faster to the organization. Many of the insights were more surface-level, and some sections repeated. There were a few items shared that were more like promotional material for IBM, but that is the environment the authors knew best.
It is a positive read. If you are curious about AI and business, you will find a few nuggets in these pages, but for the seasoned AI readers this will be a review till you get to the final chapter and then there is more sharing of the next possible steps in the Generative AI space.
July 27, 2025
The main take away of the book is to move from +AI to AI+ and make AI a core part of the business. Here, it is crucial to not give your data away and feed it thoughtlessly into ChatGPT & Co. Less than 1% of today's enterprise data resides in LLM, hence, making it the businesses most valuable asset.
For me, the book was a good read. It gives an introduction to LLMs, though it stays too much on the surface level and there are many parts which read like IBM promotion and always reading "this should not be IBM" promotion read like it. I acknowledge that this is the environment the authors know best, though not always highlighting it would be less distracting.
For me, the book was a good read. It gives an introduction to LLMs, though it stays too much on the surface level and there are many parts which read like IBM promotion and always reading "this should not be IBM" promotion read like it. I acknowledge that this is the environment the authors know best, though not always highlighting it would be less distracting.
June 24, 2025
Good concept and mindset about GenAI but nothing in terms of actual execution and implementation
August 12, 2025
Too much fluff. There are a couple of interesting chapters describing SLMs and musing about the nature of “generative computing”, but even there it’s more about product marketing of IBM.
Displaying 1 - 5 of 5 reviews