Typotex Publishing, 2025
304 pages, 5500 HUF
Artificial intelligence is not a new phenomenon, but large language models (LLMs) have propelled it into pop culture. Today many people call themselves “AI experts,” even though no one yet sees clearly how this technology will integrate into everyday life; everyone is still experimenting with what these tools can actually be used for. According to the authors, not a single line of Artificial Intelligence in the Economy was written by AI, yet AI helped significantly in the writing process. György Bőgel is an economist and professor at the Central European University (CEU), an acclaimed researcher of the ICT market and corporate strategy, both in theory and in practice. Attila Dániel Nagy is a lawyer specializing in data protection, focusing on European data protection and digital technology regulation. They have done what everyone else is doing: experimenting with AI while trying to understand how a diverse ecosystem—professionally speaking, a new “stack”—is being built step by step.
After a brief historical introduction, the authors tackle major questions: for whom and in what ways will AI become an advantage (or disadvantage)? For example: how will automation affect the labor market? What role does government regulation play in a data-driven economy? And how will the private sphere transform when control extends from personal data all the way to algorithms? Is the AI market moving toward monopoly? How much of what we see is genuine innovation, and how much is marketing noise? Where will true dominance lie: with chip manufacturers, infrastructure providers, or model developers? The authors show objectively that often the “most elegant algorithm” does not win; the winner is the one who controls manufacturing capacity, the cloud, or the data. They contrast exaggerated expectations with reality. Instead of a sudden productivity explosion, they emphasize a slower maturation process and the importance of hidden costs, noting that electrification or the internet also reshaped the economy over decades, not overnight.
The final chapters examine how education, science, the creative industries, politics, and warfare are being transformed. They do not predict the future; rather, they raise dilemmas: how can we simultaneously encourage innovation and manage risks? How much further can models scale? What happens if we run out of data, energy, or regulatory patience?
The book offers not only a theoretical framework but also a rich set of examples showcasing changing markets, the actors of the startup and corporate worlds, as well as the issues of regulation and ethics. The authors’ style is light yet intellectually stimulating: each chapter poses one or two questions that reach beyond the daily technological hype. This book is neither a prophetic manifesto nor an apocalyptic pamphlet, but a calm, factual, and broad-minded analysis. A compass for anyone who wants to understand how technology, economics, politics, and law converge in the age of AI.