AI Reading List: Eight Data and AI Books to Inspire You in Business & Life in 2024

In our fast-paced, information-heavy world, the deep learning that comes from reading books is especially valuable, particularly in complex areas like Data and Artificial Intelligence (AI). Francis Bacon once said, “Reading maketh a full man; conference a ready man; and writing an exact man.”

At Infocepts, our ‘On the Same Page’ book club is dedicated to nurturing a culture of reading, and our book lovers regularly share insights from their latest book discoveries. This blog brings together reviews and insights from our global teams, spotlighting current books in the data and AI field.

AI Reading List

Our AI reading list is a selection of recent, influential works tailored to keep you abreast of the rapidly evolving Data and AI landscape.

1. “Competing in the Age of AI” by Marco Iansiti and Karim R. Lakhani

   In this book, the authors, both Harvard Business School professors, explore how AI-driven decision engines are transforming major companies like Google, Facebook, and Netflix. They present AI as a fundamental shift in business operations, surpassing traditional labor constraints. The book offers a comprehensive exploration of the changing business terrain, shedding light on the contrasting dynamics between digital enterprises and their traditional counterparts.

   Ben Dooley, our North American Business Leader, endorses the work for its insights into the operational, structural, and strategic impacts of AI in business. He highlights the book’s examination of the “AI-factory” model adopted by tech leaders, which fosters new opportunities, efficiency, and investment strategies. This model, as Dooley emphasizes, is critical for maintaining competitiveness in the modern market. He finds the case studies of Amazon, Microsoft, and Ant Financial particularly useful, showcasing AI’s potential for driving transformative business innovations. Explore how Infocepts can empower your business with a bespoke Data & AI Strategy perfectly aligned with your unique objectives.

2. “AI for Business” by Doug Rose

   This book provides an easy-to-understand introduction to Artificial Intelligence and Machine Learning for non-technical readers. The book traces AI’s development from the 1950s and explores how advancements like GPS and social media have fueled machine learning with big data. Rose demystifies AI and ML, focusing on practical examples to showcase their potential in transforming business and policymaking.

   Subhash Kari, Chief Innovation Officer at Infocepts, recommends the book to understand the broad applications of AI in business. He appreciates its ability to make AI and ML accessible to non-technical leaders, focusing on practical solutions over technical complexity. Kari emphasizes the book’s role in developing crucial skills for translating AI benefits into business contexts, positioning it as a starter guide for future-focused leaders. Read how you can harness the power of data efficiently to empower AI systems.

3. “Life 3.0: Being Human in the Age of Artificial Intelligence” by Max Tegmark

   I had the opportunity to read and discuss “Life 3.0” with book club enthusiasts at Infocepts. This book delves into the future of AI and its impact on humanity. Tegmark explores the concept of “Life 3.0” – beings capable of transforming both their software and hardware. Tegmark’s fictional narrative, where a team develops ‘Prometheus’, an ultra-intelligent AI surpassing human intelligence, vividly illustrates the potential trajectory of AI.

   I found Tegmark’s exploration of Artificial General Intelligence (AGI) and the possibility of an “intelligence explosion” particularly impactful. His views, encapsulated in a quote, “To learn our goals, an AI must figure out not what we do, but why we do it”, resonates deeply with me. What struck me is how Tegmark’s once seemingly fictional concepts are now edging closer to reality, especially with advancements (such as the rumored Q*) hinting at AGI. Tegmark’s work is a call to carefully consider and shape a future where AI aligns with humanity’s best interests – an imperative today.

4. “Telling your Data Story” by Scott Taylor – The Data Whisperer

   The book provides a practical approach to communicating data management’s strategic value for an organization using data storytelling, offering strategies to align data management with business goals (which is a core tenet of data modernization). The book guides readers in understanding, framing, and effectively communicating the value of data in business contexts​.

   Subhash Kari appreciates Taylor for his unique approach to mastering business data language. He underscores Taylor’s emphasis on establishing data “Truth before Meaning”, prioritizing data quality and master data management before advancing to areas like AI. Kari suggests that Taylor’s insights are crucial for leaders and CFOs to understand the importance of foundational data work and recommends inviting Taylor to speak at your company, especially for advocating funding for data management projects.

5. “The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You” by Mike Walsh

   The book presents ten key principles derived from Walsh’s research and interviews with business leaders, AI experts, and data scientists. It aims to equip readers with a transformative mindset and skillset for better decision-making, problem-solving, and leadership in a world increasingly influenced by algorithms and AI technologies.

   Rahul Apte, Group Manager at Infocepts, highly values the book for its forward-looking take on AI’s role in future work and leadership. He appreciates its exploration of human-machine collaboration for innovation and value creation. Apte finds the book’s practical advice, exercises, and self-assessment tool for evaluating algorithmic leadership skills especially beneficial.

6. “Artificial Intelligence and the Future of Power: 5 Battlegrounds” By Rajeev Malholtra

   In this book, Malhotra balances the benefits and risks of AI, including its technological enhancements and growing influence on human reliance on digital networks. The book focuses on five crucial areas: economy, geopolitics, societal impacts, personal identity, and country-specific challenges.

   Faiz Wahid, our EMEA Business Leader, regards it as a thorough exploration of AI’s role in shaping the future. He highlights the book’s focus on AI’s uneven societal impact and novel themes like “Data Capitalism” and “Digital Colonization.” Wahid values the book’s in-depth examination of key issues like economic development, global power shifts, psychological influence, and metaphysics.

7. “AI & Data Literacy: Empowering Citizens of Data Science” by Bill Schmarzo

   Bill Schmarzo’s guide aims to enhance data science literacy in an AI-centric world. It prepares readers with essential skills to excel in AI-driven environments, blending practical AI and data literacy with business insights. The book uses real-world scenarios to showcase how these competencies can effectively address current and future challenges.

   I’ve been impressed by Schmarzo’s concept, “Citizen of Data Science,” which emphasizes the importance of active involvement and shared responsibility in shaping AI’s future. This idea resonates with me, as it transforms passive criticism into active, constructive engagement. The book also touches on the societal aspects of AI, making it a valuable resource for anyone interested in Responsible AI—the responsible development and use of AI technologies.

8. “Data Science for Business” by Foster Provost and Tom Fawcett

   This book is an insightful guide for applying data science in business contexts. It teaches how to extract meaningful insights from data, emphasizing the importance of data-analytic thinking. It explains various data-mining techniques and uses real-world examples from Provost’s MBA course at New York University. The book also discusses effective strategies to enhance the communication between business stakeholders and data scientists.

   Abhijeet Sarkar, Solution Consultant at Infocepts, commends the book for its effective simplification of data science complexities. He values its instructional approach that avoids overly technical mathematical explanations, making the material accessible and enlightening. Sarkar also appreciates the book’s foundational insights into data science and its strategic guidance on applying data science methods to resolve business challenges.

We hope our AI reading list inspires your thinking about AI in life and business. Humanity’s relation to AI is likely in a crucial stage. The decisions that we make now may dramatically shape the future. This AI Reading List is curated to provide readers with the insights businesses need to leverage AI effectively.

Happy reading!