Suggested reading

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A decade after publication, Leading Digital holds up well. Its central framework — that digital transformation requires both technology capability and the leadership intensity to govern it — remains the clearest lens I know for diagnosing why large programmes succeed or fail. I've worked with organisations that had one without the other. The result is always the same. The book couldn't have anticipated generative AI, which has since raised the stakes considerably. But the questions it asks of boards and executives are still the right ones

The confluence of four technologies--elastic cloud computing, big data, artificial intelligence, and the internet of things --writes Siebel, is fundamentally changing how business and government will operate in the 21st century. 

Siebel masterfully guides readers through a fascinating discussion of the game-changing technologies driving digital transformation and provides a roadmap to seize them as a strategic opportunity. He shows how leading enterprises such as Enel, 3M, Royal Dutch Shell, the U.S. Department of Defence, and others are applying AI and IoT with stunning results. 

Digital Transformation is the guidebook every business and government leader needs to survive and thrive in the new digital age.

The statistic Rogers opens with — 70% of digital transformations failing — will surprise no one who has worked inside one. What's more useful is his diagnosis of why. The five barriers he identifies (vision, priorities, experimentation, governance, and capabilities) map closely to what I see in organisations that struggle: not a shortage of technology ambition, but an inability to make consistent decisions about what matters and build the organisational muscle to deliver it. The roadmap framing is practical without being reductive. Rogers is right that transformation is an organisational challenge before it is a technology one. A useful, honest book.

Most books on surveillance are written for activists or academics. This one attempts something harder — a practical reckoning with a technology reality that most executives, policymakers, and citizens are still rationalising rather than confronting. The core argument is sound: surveillance is no longer a government instrument applied to the few; it is the ambient condition of digital life. The organisations I work with collect extraordinary amounts of data and rarely ask whether they should. That gap between capability and conscience is exactly what this book addresses. The call to informed citizenship is well-placed, if slightly optimistic. Worth reading.

The AI Con is a necessary corrective. I work with organisations navigating real decisions about AI adoption, and the gap between vendor claims and actual capability is frequently staggering. The authors are right that much of what is marketed as AI is statistical pattern-matching dressed in science-fiction language — and that the hype actively obscures genuine risks in healthcare, law enforcement, and hiring. Where the book overreaches is in its blanket scepticism. Some of these tools genuinely work. The problem isn't AI — it's the absence of critical evaluation when purchasing it. On that point, this book is an excellent starting guide.

The opening provocation, that data alone is not a market discriminator, is one I wish more executives had absorbed before commissioning their data lakes. Schmarzo's shift from data-driven to value-driven thinking is the right reframe. I've sat across from leadership teams proud of their data assets who couldn't articulate a single decision those assets had improved. The Big Data Business Model Maturity Index is useful as a diagnostic conversation-starter, though like most maturity frameworks it risks becoming an end in itself. The stronger contribution is the value engineering methodology. Practical, commercially grounded, and long overdue in this space.