AI will replace you – review | Ziptone

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With the title of the book of Paul Jostra en Martin Verschuere You can go in any direction, but it doesn't sound very reassuring. Then they start the preface with the antiphrase "You don't really need this book." Fortunately, nothing else in the rest of the book is unintentionally turned upside down. As a result, AI will replace you largely readable as an AI cookbook or AI manual.

After those initial reassuring words, the book quickly returns with warnings. All the CEOs Joustra (SVP Digital Innovation & Gen-AI Transformation at TP) spoke with wanted to do something with AI, but had varying excuses for why they couldn't get started yet. Anyone who doesn't prefer to move at AI speed runs the risk of a twelve-year-old eating your lunch. In this AI era, that notion isn't entirely unreasonable. Gen-A grows up with AI as if it were a mobile phone: always on.

AI is a platform

Joustra and Verschuere (the latter is a lecturer, speaker, and author) begin with the enormous potential of generative AI. Information is no longer scarce, and GenAI isn't a chatbot, but a platform you can rely on. Furthermore, conversational AI is the new interface. Finally, the authors present agentic AI as the third trend, which can save time and simplify things in an accessible way.

The boat you can't miss

The biggest pitfall is starting with AI and then looking for a problem. The authors therefore offer a helpful first step: reformulating your mission and vision in relation to AI. Because AI is definitely not an optimization tool, but a means that enables transformation. Incidentally, the latter was also said of the cloud. Anyone who missed digital transformation in the cloud era would end up like the next Kodak or Nokia, but both companies still exist. And speaking of optimization: that's what the use of AI in customer contact has been all about so far. From a BPO perspective, optimization through AI is still a common appetizer. Transformation? We'll do that later. The question is whether, after all the talk about exponential organizations, scaled agile, cloud-first, digital-first, moonshots, Big Hairy Audicious Goals, and MVPs, leaders still feel sufficient urgency about AI as a transformative technology.

Mindset

Anyone who wants to get started with AI will have to build knowledge, starting from scratch. Verschuere therefore advocates for a learning mindset and provides practical tips and concrete exercises. It's good that Verschuere emphasizes that AI is different for consumers (your company's customers) than for your employees. For some, it's (hopefully) an asset; for others, it's a competitor that (potentially) takes over tasks or jobs. Verschuere therefore advocates categorizing your own teams into, loosely translated, cowards, ostriches, and AI enthusiasts. They're all stakeholders who influence your AI project, so you have to do something with them.

Fast – good – cheap

Joustra then explains how he established an innovation network within TP (500.000 employees), which began as a small group of analysts and technicians and evolved into a scalable delivery model for AI solutions. Talking about AI is fun, but clients want to see execution power. Learning is also a matter of doing, and Joustra and Verschuere offer the brilliant triangle of "fast – good – cheap." As everyone knows, any combination of two comes at the expense of the third, but for each pair, they provide a workable model that demonstrates the ways in which AI can be implemented.

What's on the horizon?

Exactly halfway through the book, things get tricky. Joustra and Verschuere offer recipes ("let's cook some AI"), and we know that the shelf life of the ingredients in AI is very limited. Therefore, they provide a detailed framework in which they first examine the most important ingredients (classical, generative, and agentic AI). The latter is called "the promising frontier." This poses risks, in kitchen terms: I needed ice but came home with water.

Joustra and Verschuere then move on to the "buy or build" question and collaboration options. Not entirely unexpectedly, the partnership between flagship customer Samsung and TP is discussed, making it a bit of a TP chapter.

Those who scale up discover the real challenges

The third and final part is about scaling (the first two were about inspiring and facilitating). Fortunately, this immediately addresses the notion of scaling, as was the case with cloud computing back then: "add a few servers, give people some SaaS, and your organization will grow exponentially." A successful AI pilot doesn't guarantee a successful rollout at scale, a sentiment increasingly heard.

When scaling up, AI can reveal errors, mistakes, and unreliability, and can even ruin your happy flow. That's why they're also developing a practical model to provide guidance. Joustra and Verschuere's framework shows what goes wrong if one of the necessary building blocks is missing. "You can race for a while without seatbelts, but if you crash..."

Is AI an opportunity, a choice or a threat?

Joustra and Verschuere conclude with a series of predictions about the future. They address work, leadership, the role of algorithms in our society, digital twins, hybrid roles (human + agent), and even physical robots. These predictions are addressed somewhat late in the book. However, the authors do conclude with the reassuring words: AI will replace "You" isn't a threat, but a choice. But we all know that technology ultimately forces choices, and AI is likely no exception.

Finally: is this book recommended? It's not the first book on AI. The great thing about 'AI Will Replace You' is that it starts with the basics, making it a kind of cookbook for beginners: broad in scope, yet practical and goal-oriented. It's completely non-technical, which, given the subject matter, is practically impossible. One minor shortcoming: the missing glossary. AI could have easily added that. So, you can only look it up in the e-book.