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      • Profile Photo
        Profile photo of Sinchana Adiga
        Artificial Intelligence
        Sinchana Adiga 5 days ago

        Top 20 AI Books to Read in 2025–2026

        Artificial Intelligence is transforming every industry—faster than any technology we’ve seen before. Whether you’re stepping into AI for the first time, advancing your technical expertise, or leading teams through AI-driven change, the right books can accelerate your journey.

        This curated list brings together the most insightful, practical, and future-ready AI books, covering fundamentals, machine learning, deep learning, business strategy, governance, and the rise of agentic AI. Each book has been selected for its clarity, relevance, and long-term impact.

        If you’re planning to upskill in 2025–2026, start here.

        1. Artificial Intelligence: A Guide for Thinking Humans — Melanie Mitchell

        A clear, engaging introduction to how AI works and what it still cannot do.
        🔗 https://www.amazon.com/dp/0374257833

        2. The Alignment Problem — Brian Christian

        A powerful narrative on AI alignment, safety, and human behavior.
        🔗 https://www.amazon.com/dp/0393635821

        3. Life 3.0 — Max Tegmark

        Explores possible futures shaped by AI and advanced intelligence.
        🔗 https://www.amazon.com/dp/1101970316

        4. Prediction Machines — Agrawal, Gans & Goldfarb

        Perfect for understanding AI’s business and economic implications.
        🔗 https://www.amazon.com/dp/1633695670

        INTERMEDIATE (For Students & Professionals)

        5. AI Superpowers — Kai-Fu Lee

        Insights into global AI competition and real-world applications.
        🔗 https://www.amazon.com/dp/132854639X

        6. Architects of Intelligence — Martin Ford

        Interviews with the world’s most influential AI pioneers.
        🔗 https://www.amazon.com/dp/1789954534

        7. Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow — Aurélien Géron

        One of the best practical guides for ML and DL practitioners.
        🔗 https://www.amazon.com/dp/1098125975

        8. Grokking Deep Learning — Andrew Trask

        A friendly and intuitive approach to understanding deep learning.
        🔗 https://www.amazon.com/dp/1617293709

        ADVANCED (Technical & Research)

        9. Deep Learning — Goodfellow, Bengio & Courville

        The definitive textbook — foundational for deep learning researchers.
        🔗 https://www.deeplearningbook.org/

        10. Reinforcement Learning: An Introduction — Sutton & Barto

        The essential resource for RL theory and practice.
        🔗 http://incompleteideas.net/book/the-book-2nd.html

        11. Probabilistic Machine Learning — Kevin Murphy

        A rigorous, comprehensive guide to ML theory.
        🔗 https://probml.github.io/

        12. The Hundred-Page Machine Learning Book — Andriy Burkov

        Fast, compact, but deeply insightful.
        🔗 https://www.amazon.com/dp/199957950X

        AI FOR BUSINESS, STRATEGY & LEADERSHIP

        13. The AI Advantage — Thomas Davenport & Rajeev Ronanki

        A practical guide for implementing AI in real organizations.
        🔗 https://www.amazon.com/dp/0262039176

        14. Competing in the Age of AI — Marco Iansiti & Karim Lakhani

        Explains how digital-first, AI-driven enterprises operate differently.
        🔗 https://www.amazon.com/dp/1633697622

        15. Human + Machine — Paul Daugherty & James Wilson

        A human-centric view of AI-powered work.
        🔗 https://www.amazon.com/dp/1633693864

        AI ETHICS, GOVERNANCE & SOCIETAL IMPACT

        16. Ethics of Artificial Intelligence and Robotics — Patrick Lin et al.

        A comprehensive dive into AI ethics and responsible innovation.
        🔗 https://www.amazon.com/dp/1138691945

        17. Weapons of Math Destruction — Cathy O’Neil

        Reveals how algorithms reinforce bias and inequality.
        🔗 https://www.amazon.com/dp/0553418815

        18. Atlas of AI — Kate Crawford

        A global perspective on the social, economic, and ethical impacts of AI.
        🔗 https://www.amazon.com/dp/0300209576

        AI TRENDS, AGENTS & THE FUTURE OF WORK

        19. The Coming Wave — Mustafa Suleyman

        Explores the rise of agentic AI and its global consequences.
        🔗 https://www.amazon.com/dp/1529153477

        20. Power and Prediction — Agrawal, Gans & Goldfarb

        A sharp analysis of AI’s economic disruption and predictive capabilities.
        🔗 https://www.amazon.com/dp/1647824778

        Final Thoughts

        AI is no longer a niche skill — it is a critical career advantage across every industry. Whether you’re a leader, engineer, student, HR professional, strategist, or entrepreneur, these books will equip you with the mindset and mastery needed for the AI-driven decade ahead.

        incompleteideas.net

        Sutton & Barto Book: Reinforcement Learning: An Introduction

        Sutton & Barto Book: Reinforcement Learning: An Introduction

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