Innovation and Technology
10 Must-Read Tech Books Of 2025

Bookshelf: The Future of Artificial Intelligence
Must-Reads for Navigating the AI-Driven World
The past year was a transformative one in technology, dominated by advancements in artificial intelligence. From the proliferation of new generative AI applications and the rise of AI agents to questions about technology governance and the future of work, the following books offer essential perspectives from industry pioneers, leading academics, and veteran tech journalists, helping readers navigate an increasingly AI-driven world.
Co-Intelligence: Living and Working with AI
Wharton professor and “One Useful Thing” newsletter author Ethan Mollick provides guidance to help individuals thrive in the age of AI. He examines how to effectively partner with AI as a co-worker, co-teacher, and coach while offering practical insights for preserving human identity and creating positive outcomes in this new era of human-AI collaboration.
Supremacy: AI, ChatGPT, and the Race that Will Change the World
In this Financial Times and Schroders Business Book of the Year Award winner, Bloomberg technology writer Parmy Olson provides an insider’s look at the high-stakes competition between OpenAI and DeepMind, revealing the complex dynamics shaping AI’s future. Through exclusive access to industry sources, she examines the rivalries, ethical challenges, and potential threats that emerge when AI development is driven by powerful tech companies and CEOs.
Nexus: A Brief History of Information Networks from the Stone Age to AI
Nexus, by Yuval Noah Harari, examines humanity’s fraught relationship with information, tracing its influence from the Stone Age to the modern era of AI. Through historical milestones like religious canonization, witch-hunts, and totalitarian regimes, Harari unpacks how societies have wielded information as both a tool for progress and a weapon of control. As we confront ecological collapse, rampant misinformation, and the rise of artificial intelligence, the book challenges us to rethink the balance between truth, wisdom, and power, offering a hopeful perspective and calling for rediscovering our shared humanity amid the complex interplay of information and existential threat.
The Corporate Life Cycle: Business, Investment, and Management Implications
NYU professor and valuation expert Aswath Damodaran presents a universal framework for understanding how companies evolve through different stages of the corporate lifecycle. His work helps readers recognize crucial transition points in corporate finance and adjust their strategies accordingly, offering vital insights for optimizing management and investment decisions. He also explores the tactics and tradeoffs companies face as they leverage technology, acquired or homegrown, to scale up quickly.
Burn Book: A Tech Love Story
Veteran tech journalist Kara Swisher delivers an insider’s chronicle of Silicon Valley’s most influential figures. Drawing from three decades of interviews with leaders like Steve Jobs, Jeff Bezos, and Mark Zuckerberg, she provides a candid look at how tech visionaries have both contributed to and hindered progress in the digital age.
All Hands on Tech: The AI-Powered Citizen Revolution
This book explores the transformative power of citizen developers—business domain experts leveraging democratized technology to drive innovation. Through compelling case studies, the authors reveal how empowering employees to create applications, automations, and analytics enhances organizational agility and minimizes IT bottlenecks. The book provides a practical framework for integrating citizen development into digital strategies while aligning with corporate goals and mitigating risks. A must-read for leaders and innovators, it redefines the future of work, showcasing how technology can unlock the ingenuity of all employees for a more innovative and efficient enterprise.
AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference
Computer scientists Arvind Narayanan and Sayash Kapoor cut through AI hype and misinformation to provide a clear understanding of AI’s true capabilities and limitations. They examine AI’s impact across areas like education, medicine, hiring, and criminal justice, helping readers understand potential risks and make informed decisions about AI adoption in both professional and personal contexts.
The Singularity Is Nearer: When We Merge with AI
A renowned futurist, Kurzweil returns with a fresh perspective on technological advancement, examining his earlier predictions and exploring how exponential growth in AI and biotechnology will transform human life. He tackles controversial topics from job automation to life extension, offering both optimistic visions and consideration of potential perils.
The Nvidia Way: Jensen Huang and the Making of a Tech Giant
This business history book reveals how Nvidia transformed from a gaming-focused startup to a powerhouse driving the AI revolution. Drawing from more than 100 interviews, including conversations with CEO Jensen Huang and his cofounders, Kim uncovers the company’s unique culture and strategic decisions that enabled Nvidia to outmaneuver tech giants and position itself at the forefront of the AI era.
The AI-Savvy Leader: Nine Ways to Take Back Control and Make AI Work
De Cremer’s book is a compelling guide for leaders to take charge of AI transformation in their organizations. It highlights how many leaders have abdicated their roles, risking organizational failure in navigating the complexities of human-machine collaboration. Focusing on nine actionable steps rooted in core leadership skills like vision-setting, communication, and strategic execution, the book equips leaders to integrate AI responsibly and effectively. Rather than delving into technical AI details, it emphasizes the need for visionary leadership to align AI initiatives with organizational goals for sustainable growth and success.
The books listed above offer a comprehensive look at the AI landscape, covering topics from AI’s impact on work and society to the strategies and challenges of implementing AI in organizations. By reading these books, leaders, innovators, and individuals can gain a deeper understanding of AI’s potential and limitations, as well as the ways to harness its power for positive change.
Q: What are some of the most important AI trends?
A: Some of the most important AI trends include the rise of generative AI, the increasing use of AI in healthcare, and the growing concern about AI bias and ethics.
Q: What are some of the benefits of AI?
A: Some of the benefits of AI include increased efficiency, improved accuracy, and enhanced decision-making capabilities.
Q: What are some of the challenges of AI?
A: Some of the challenges of AI include data quality issues, AI bias, and the need for high-quality training data.
Q: How can I get started with AI?
A: You can get started with AI by taking online courses, attending conferences, and reading books on AI. You can also start by exploring AI tools and technologies that interest you.
Innovation and Technology
Are AI Product Managers The Role Of The Future?

As artificial intelligence continues to reshape industries, a new role is emerging at the intersection of technology, strategy, and innovation: the AI Product Manager. This isn’t just a passing trend—it’s a reflection of how integral AI is becoming in the development and optimization of modern products.
To succeed in this evolving role, AI product managers must do more than understand traditional product lifecycles. They’ll need to navigate complex AI and machine learning (ML) systems, evaluate performance metrics, and ensure responsible, ethical deployment of technology. That requires a unique blend of technical acumen, data fluency, and cross-functional leadership.
Core Competencies of Future-Ready AI Product Managers
To lead in this space, product managers should develop proficiency in the following key areas:
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AI-Specific Technical Competence – Understanding how models are built, trained, tested, and deployed.
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Data Science Knowledge – Ability to interpret data, partner with data teams, and drive data-informed decisions.
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Model Performance Evaluation – Knowing how to measure, optimize, and communicate model performance.
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Ethics, Bias, and Regulation – Staying informed about legal and societal implications of AI systems.
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Education and Influence Management – Evangelizing AI within the organization and aligning diverse stakeholders around AI initiatives.
Why Every Product Manager Needs AI Skills
Just as “internet product managers” were once a niche, only to evolve into the standard model of digital product management, AI is on track to become a core element of every product manager’s toolkit.
According to Forrester, AI will become so embedded in product development that PMs who lack foundational AI knowledge may find themselves at a disadvantage. Generalist product managers won’t need to be AI engineers, but they will need to understand how to integrate AI into product features, make informed trade-offs, and iterate based on user feedback and AI performance.
How Product Leaders Can Prepare Their Teams
Leadership plays a crucial role in preparing product teams for the AI-powered future. That means more than just encouraging learning—it means building a culture that values experimentation, continuous education, and hands-on practice.
Here’s how leaders can start:
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Offer AI literacy programs tailored for non-technical professionals.
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Create hands-on experiences through internal projects, hackathons, or partnerships with AI teams.
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Provide access to online, interactive courses and workshops that blend theory with application.
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Recognize and reward team members who take the initiative to upskill.
Conclusion
AI isn’t just a buzzword—it’s rapidly becoming a foundational element of modern product strategy. As such, the AI product manager role is not only growing but evolving into a key pillar of the future workforce.
Product leaders who invest in upskilling today will set their teams up for long-term success, ensuring they’re not only keeping up with the market but helping to define it.
FAQs
Q: What skills do AI product managers need?
A: They should develop AI-specific technical knowledge, data science fluency, the ability to evaluate AI performance, a strong understanding of ethics and regulation, and the ability to educate and influence across teams.
Q: Why is AI knowledge becoming essential for all product managers?
A: AI is becoming a standard part of digital products. PMs will need to understand how to apply AI responsibly and effectively to remain competitive and meet evolving customer expectations.
Q: How can leaders support their teams’ AI/ML development?
A: Provide access to literacy courses, create hands-on learning opportunities, encourage cross-functional collaboration, and foster a culture of curiosity and continuous learning.
Innovation and Technology
The Importance of Data and Analytics in Digital Transformation

Data and analytics are no longer just about crunching numbers and generating reports. They are now a key driver of business success, helping organizations to optimize operations, improve decision-making, and stay competitive in a rapidly changing world.
Why Data and Analytics Matter
Data and analytics help organizations to:
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- Gain insights into customer behavior and preferences
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- Identify areas for improvement and optimize operations
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- Make data-driven decisions, rather than relying on intuition or anecdotal evidence
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- Stay ahead of the competition by being more agile and responsive to changing market conditions
The Challenges of Data and Analytics
While the benefits of data and analytics are clear, many organizations struggle to implement effective solutions. This can be due to a range of factors, including:
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- Limited resources, including budget and personnel
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- Complexity and technical difficulties in implementing and maintaining data analytics solutions
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- Lack of expertise and knowledge in data analysis and interpretation
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- Resistance to change and cultural barriers to adopting new technologies and processes
Overcoming the Challenges of Data and Analytics
While the challenges of data and analytics are real, there are many ways to overcome them. This can include:
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- Seeking expert guidance and support to help implement and maintain data analytics solutions
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- Investing in employee training and development to build in-house expertise
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- Starting small and gradually building up capabilities and expertise
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- Building a strong business case and demonstrating the value of data and analytics to stakeholders
Conclusion
Data and analytics are no longer optional, but a crucial part of any digital transformation strategy. By gaining insights into customer behavior, identifying areas for improvement, and making data-driven decisions, organizations can stay ahead of the competition and achieve their goals.
Innovation and Technology
5 Employee Experience Mistakes Companies Will Make This Year

Lagging In HR AI And Automation
There are lots of great ways companies can use AI within HR to drive improvements in EX. Did you know, for example, that 54% of respondents to one survey said they had given up on applying for a job they wanted due to poor communication from the employer?
Other opportunities include providing personalized onboarding, reducing administrative work by automating repetitive tasks, engagement tracking and improving many aspects of performance management.
Over-Automating Employee Experience
On the other hand, AI still presents a huge number of challenges, particularly when it’s mixed with humans! And while many companies will make the error of under-investing, just as many will, unfortunately, end up using it in ways that are potentially damaging.
Failing To Offer Personal Development Opportunities
This is critical for both retaining existing employees and attracting new talent. Technology is quickly reshaping industries, but workforces need trained and skilled employees to take advantage of this. Offering career progression planning, upskilling and retraining aimed at empowering them to use technology helps people feel they are investing in their own futures by sticking with a business.
Failing To Measure EX ROI
Investing in EX initiatives without a clear plan or milestones in place for measuring success risks wasting money without delivering tangible benefits.
Neglecting Employee Mental Health And Wellness
Workplace stress and burnout are at an all-time high. In fact, the World Health Organization reports that the US economy loses $1 trillion every year thanks to lost productivity caused by depression and anxiety.
Final Thoughts
Employees are a company’s most important resource, and neglecting EX in 2025 means they will quickly start looking elsewhere. This can be a disaster when business success is more dependent than ever on attracting and retaining the right people!
Conclusion
The message I want to get across is that every business should take a strategic approach to EX, taking care to understand how success or failure will impact goals and overall performance. Invest in staff through training, professional development and wellbeing initiatives, and they will pay you back with loyalty, growth and business success!
FAQs
- What is employee experience (EX)?
- EX is the sum of all experiences an employee has in a company, including their interactions with colleagues, supervisors, and the organization itself.
- Why is EX important?
- EX is important because it can directly impact employee productivity, retention, and overall job satisfaction.
- What are some common pitfalls companies make when it comes to EX?
- Some common pitfalls include lagging in HR AI and automation, over-automating employee experience, failing to offer personal development opportunities, failing to measure EX ROI, and neglecting employee mental health and wellness.
- How can companies improve EX?
- Companies can improve EX by providing personalized onboarding, reducing administrative work, offering career progression planning, and prioritizing employee mental health and wellness.
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