David De Cremer – Leadership by Algorithm: Book Review & Audio Summary

Book Info

• Book name: Leadership by Algorithm: Who Leads and Who Follows in the AI Era?
• Author: David De Cremer
• Genre: Business & Economics
• Published Year: 2015
• Publisher: Palgrave Macmillan
• Language: English

Audio Summary

Synopsis

In Leadership by Algorithm, David De Cremer explores the inevitable collision between artificial intelligence and workplace management. As AI becomes increasingly sophisticated—from Google’s AlphaGo defeating world champions to algorithms tracking employee performance at JPMorgan Chase—business leaders face critical questions about the future of work. De Cremer argues that while AI excels at management tasks like data processing, performance tracking, and compliance monitoring, true leadership remains distinctly human. This thought-provoking examination reveals how AI will add trillions to the global economy while fundamentally transforming how organizations operate, ultimately distinguishing between the managerial functions machines can master and the leadership qualities only humans possess.

Key Takeaways

• AI is uniquely suited to handle management tasks like data processing, performance tracking, and compliance monitoring that many employees find tedious
• The distinction between management (supervising day-to-day operations) and leadership (providing vision and inspiration) becomes crucial in the AI era
• While algorithms can manage efficiently, they lack the human qualities necessary for true leadership—influence, motivation, and the ability to inspire meaning
• AI is projected to add $13 trillion to the global economy over the next decade, making its adoption in business inevitable
• Organizations must prepare for workplaces composed of both AI managers and human leaders working in tandem

My Summary

When Machines Start Making Decisions

I’ll be honest—when I first picked up David De Cremer’s Leadership by Algorithm, I was skeptical. Another book about AI disrupting everything? But De Cremer, a management professor at Rotterdam School of Management, brings something different to the table. He’s not just speculating about a distant future; he’s documenting a transformation that’s already underway in companies like JPMorgan Chase and Google.

The book opens with a fascinating premise that immediately grabbed my attention: the 2016 moment when Google’s AlphaGo defeated the world champion at Go, a game far more complex than chess. This wasn’t just a tech milestone—it was a psychological watershed. For years, people believed that Go required intuition, creativity, and a distinctly human touch. When AI proved them wrong, business leaders everywhere started asking: “What else can machines do that we thought only humans could?”

De Cremer’s answer is both reassuring and unsettling. AI is coming for management, but leadership? That’s still ours to claim.

The Management Nobody Wants to Do

Here’s something that resonated with me personally: De Cremer’s observation that modern workplaces are “over-managed.” Having worked in corporate environments before becoming a full-time book blogger, I’ve felt this firsthand. The endless check-ins, the performance metrics, the compliance reports—it’s exhausting for everyone involved, including the managers themselves.

De Cremer draws a sharp distinction between management and leadership that I found incredibly clarifying. Management, he argues, is about the nuts and bolts: setting budgets, tracking performance, ensuring deadlines are met, and wading through mountains of data. Leadership, on the other hand, is about vision, charisma, and inspiring people to care about their work.

The brilliant insight here is that the very qualities that make management tedious for humans make it perfect for AI. Think about what managers actually spend their time doing. They’re processing data about employee performance—sales figures, attendance records, productivity metrics. They’re checking whether people are following procedures and meeting standards. They’re creating schedules and allocating resources.

All of this involves working with quantifiable information and applying consistent rules. And that’s exactly what algorithms excel at. AI doesn’t get bored reviewing the same types of reports day after day. It doesn’t play favorites or let personal biases cloud its judgment. It can process vastly more information than any human manager and identify patterns we’d never spot.

AI Managers Already at Work

De Cremer provides concrete examples that brought this home for me. JPMorgan Chase uses algorithms to monitor employees and ensure they’re complying with regulations. Other companies deploy AI to track job satisfaction and predict which employees are likely to resign. Some organizations use algorithms to screen job applications, schedule shifts, and even conduct initial performance evaluations.

This isn’t science fiction—it’s happening right now. And the economic incentives are massive. De Cremer cites estimates suggesting AI will add $13 trillion to the global economy over the next decade. With numbers like that, the question isn’t whether businesses will adopt AI management tools, but how quickly.

What struck me most was realizing that this shift might actually improve workplace culture. How many talented professionals have left jobs not because of the work itself, but because of poor management? How many managers feel trapped in roles they never wanted, drowning in administrative tasks when they’d rather be doing strategic thinking or mentoring?

If AI can handle the bureaucratic burden, it could free humans to focus on what we’re actually good at—and what we actually enjoy.

What Machines Can’t Lead

But here’s where De Cremer’s argument gets really interesting, and where I found myself nodding along enthusiastically. Leadership, he argues convincingly, is fundamentally different from management. And it’s something AI simply cannot replicate.

Leadership isn’t about processing data or enforcing rules. It’s about influence—the ability to convince others to follow you, to adopt your vision, to commit themselves to a shared goal. It’s about motivation—inspiring people to bring their best selves to work, to push through challenges, to innovate and take risks.

Most importantly, leadership is about meaning. Great leaders help employees understand why their work matters, how it connects to something larger than themselves. They create narratives that transform mundane tasks into meaningful contributions.

Can an algorithm do this? De Cremer argues no, and I’m inclined to agree. Leadership requires emotional intelligence, empathy, and the ability to read social dynamics in real-time. It requires understanding what motivates different individuals and adapting your approach accordingly. It requires authenticity—people follow leaders they trust, and trust is built through genuine human connection.

The Human Touch in an Automated World

Think about the leaders who’ve inspired you in your own life. For me, it was a college professor who saw potential in me I didn’t see in myself, and a former boss who took the time to understand my career aspirations and helped me develop skills I didn’t even know I needed. Could an algorithm have done that? Could a program have sensed my insecurity and known exactly when to offer encouragement versus when to push me harder?

De Cremer points out that leadership often involves making judgment calls in ambiguous situations where there’s no clear “right” answer. It requires balancing competing values—short-term profits versus long-term sustainability, individual needs versus team cohesion, innovation versus stability. These aren’t mathematical problems with optimal solutions; they’re human dilemmas that require wisdom, experience, and yes, a bit of intuition.

Moreover, effective leadership requires leaders to be vulnerable, to admit mistakes, to show they’re human. This builds trust and psychological safety, creating environments where people feel comfortable taking risks and speaking up. An algorithm can’t be vulnerable because it has no self to expose. It can’t admit mistakes because it doesn’t experience doubt or regret.

Practical Applications for Today’s Workplace

So what does all this mean for those of us navigating the current business landscape? De Cremer’s framework offers several practical takeaways that I think are worth considering.

Embrace AI for What It Does Best

First, organizations should actively look for opportunities to delegate management tasks to AI. If you’re spending hours each week compiling performance reports, scheduling meetings, or tracking compliance metrics, ask whether these tasks could be automated. The goal isn’t to eliminate jobs, but to eliminate the tedious parts of jobs that drain energy and morale.

I’ve seen this principle at work in my own blogging business. I use AI tools to handle routine tasks like scheduling social media posts, analyzing traffic patterns, and even generating initial drafts for certain types of content. This frees me to focus on what I actually bring unique value to—developing my voice, building relationships with readers, and curating book selections that match my audience’s interests.

Invest in Leadership Development

Second, as AI takes over management functions, leadership skills become more valuable, not less. Organizations should invest heavily in developing these distinctly human capabilities: emotional intelligence, strategic thinking, communication, vision-setting, and the ability to inspire and motivate.

For individual professionals, this means focusing your development efforts on skills that AI can’t replicate. Learn to tell compelling stories. Practice active listening. Develop your ability to read a room and understand group dynamics. Build authentic relationships. These are the skills that will differentiate you in an AI-augmented workplace.

Rethink Organizational Structures

Third, companies need to fundamentally rethink how they’re structured. If AI handles day-to-day management, you might need fewer middle managers but more senior leaders who can provide strategic direction and maintain culture. You might need to create new roles focused on human-AI collaboration, ensuring these systems work together effectively.

This also means being thoughtful about which decisions to delegate to algorithms and which to reserve for human judgment. De Cremer doesn’t provide a detailed roadmap here, which is one limitation of the book, but he raises the right questions.

Address Employee Concerns Transparently

Fourth, leaders need to communicate openly about AI adoption. Employee anxiety about being replaced by machines is real and justified. Leaders should be transparent about which tasks will be automated, how this will affect roles, and what new opportunities will emerge.

The narrative shouldn’t be “AI is replacing you” but rather “AI is handling the tedious stuff so you can focus on more meaningful work.” Of course, this only works if it’s actually true—if organizations genuinely invest in helping employees transition to higher-value activities rather than simply cutting headcount.

Cultivate Meaning and Purpose

Finally, in a workplace where algorithms handle routine management, the human need for meaning becomes even more critical. Leaders must help employees understand how their work contributes to something larger. This is especially important for younger workers who increasingly prioritize purpose over paychecks.

In my own work with Books4soul.com, I’ve found that articulating a clear mission—helping readers find books that enrich their lives—makes even mundane tasks feel worthwhile. When I’m optimizing SEO or troubleshooting technical issues, I’m not just fixing problems; I’m removing barriers between readers and books that might change their perspectives.

Where the Book Falls Short

While I found Leadership by Algorithm thought-provoking, it’s not without limitations. Published in 2015, some of De Cremer’s predictions about AI capabilities feel dated now. The technology has advanced even faster than he anticipated, and we now have examples of AI doing things—like generating creative content—that seemed firmly in the “humans only” category just a few years ago.

The book also focuses heavily on the theoretical distinction between management and leadership without providing much practical guidance for organizations navigating this transition. How do you actually implement AI management systems? What are the pitfalls to avoid? How do you maintain workplace culture when algorithms are making decisions about people’s performance and careers?

Additionally, De Cremer doesn’t deeply explore the ethical implications of AI management. What about privacy concerns when algorithms track employees’ every move? What about bias in AI systems that might discriminate against certain groups? What recourse do employees have when an algorithm makes a mistake that affects their career?

These are critical questions that deserve more attention than they receive in the book. For a more comprehensive look at AI ethics, you might want to pair this with books like Cathy O’Neil’s Weapons of Math Destruction or Hannah Fry’s Hello World.

Comparing Perspectives on AI and Work

It’s worth noting how De Cremer’s perspective compares to other thinkers in this space. Unlike more alarmist authors who predict massive unemployment and societal upheaval, De Cremer takes a relatively optimistic view. He sees AI as a tool that can make work more fulfilling by eliminating drudgery, rather than as a threat that will make humans obsolete.

This contrasts with books like Martin Ford’s Rise of the Robots, which paints a darker picture of widespread job displacement. It also differs from more techno-utopian visions that imagine AI solving all our problems without significant disruption.

De Cremer occupies a middle ground: AI will fundamentally change how organizations operate, but humans remain essential. The key is understanding what each does best and structuring work accordingly. I find this balanced perspective more credible than either extreme, though it may be less emotionally satisfying than a clear-cut “AI is good” or “AI is bad” narrative.

Questions Worth Pondering

As I finished Leadership by Algorithm, I found myself sitting with several questions that I think are worth discussing:

If AI handles most management tasks, what happens to the traditional career ladder where people gain management experience on their way to leadership roles? How do you develop leaders if they never have to manage?

And here’s another one: De Cremer argues that leadership requires uniquely human qualities like empathy and emotional intelligence. But as AI becomes more sophisticated at reading and responding to human emotions, will this distinction hold? Are we perhaps overestimating what makes leadership “human”?

I don’t have definitive answers, and I suspect neither does anyone else at this point. We’re all figuring this out in real-time.

Why This Book Matters Now

Despite its limitations, I think Leadership by Algorithm offers a valuable framework for thinking about AI’s role in the workplace. The distinction between management and leadership is genuinely useful, and it helps clarify which human skills we should be developing and protecting as automation advances.

For business leaders, this book provides a lens for making strategic decisions about where to invest in AI and where to double down on human capabilities. For employees at any level, it offers guidance on which skills to cultivate to remain valuable in an AI-augmented workplace.

Most importantly, De Cremer reminds us that technology doesn’t determine outcomes—humans do. We get to choose how we integrate AI into our organizations, what values we prioritize, and what kind of workplace culture we want to create. The AI revolution may be inevitable, but how we respond to it isn’t.

Finding Your Place in the AI Era

As someone who’s built a career around something deeply human—sharing my authentic reactions to books and connecting with readers—I found Leadership by Algorithm both reassuring and challenging. Reassuring because it confirmed that certain human capabilities remain valuable and irreplaceable. Challenging because it pushed me to think harder about what those capabilities actually are and how to cultivate them.

Whether you’re a CEO deciding how to implement AI in your organization, a middle manager worried about your job security, or an individual contributor trying to navigate your career path, this book offers valuable perspective. It won’t give you all the answers—the situation is evolving too quickly for any book to do that—but it will help you ask better questions.

I’d love to hear your thoughts on this. How is AI already changing your workplace? What management tasks do you wish could be automated? And what aspects of leadership do you think will always require a human touch? Drop a comment below and let’s continue this conversation. After all, discussing complex questions with real people—that’s something no algorithm can replace.