Artificial Intelligence is rapidly transforming industries, public services and everyday life, creating new opportunities while raising important questions about trust, regulation and responsible innovation. Addressing these challenges, JProf Dr Thomas Schmid has co-authored a major new scientific publication with Springer Nature titled Managing and Understanding Artificial Intelligence: From Classical to Generative AI – A Practice Guide for Decision-makers, Developers and Regulators in the Age of the EU AI Act.
Published by Springer Nature in 2026, the book was written by Thomas Schmid, Wolfgang Hildesheim and Taras Holoyad. It provides a comprehensive overview of artificial intelligence, covering both foundational concepts and the latest developments in generative AI. Designed as a practical guide, the publication aims to support managers, AI developers, compliance officers, policymakers, public sector professionals and anyone seeking a deeper understanding of AI technologies and their societal implications.
The book explores a wide range of contemporary AI applications, including self-driving vehicles, medical diagnostics, robotic process automation, customer service chatbots and urban planning. Particular attention is given to generative AI and the disruptive impact of Transformer-based architectures, which have significantly advanced the capabilities of modern AI systems and accelerated innovation across multiple sectors.
A central theme of the publication is the implementation of the European Union’s AI Act. The authors examine how organisations can navigate emerging regulatory requirements while fostering innovation and public trust. The book argues that achieving digital sovereignty and trustworthy AI in Europe requires close collaboration between policymakers, industry leaders and academic institutions.
One of the publication’s key contributions is the introduction of the AI=MC² framework, a classification matrix that evaluates AI systems according to their Methods, Capabilities and Criticality. Building on this framework, the authors propose an “AI Label” transparency seal, designed to support the future classification and assessment of AI products and services. The concept aims to help organisations, regulators and users better understand the capabilities and potential risks associated with AI solutions.
To demonstrate the practical value of the framework, the book presents detailed real-world case studies, including AI-powered customer service virtual assistants, AI-based object recognition systems used in the public sector and generative AI applications for text and image creation. These examples illustrate both the opportunities and the governance challenges associated with deploying AI technologies in practice.
In addition to discussing regulation and standardisation, the publication offers concrete recommendations for stakeholders across politics, industry and academia. Special focus is given to highly regulated sectors such as medical devices, where trust, transparency and compliance are essential.
By combining technical foundations, practical applications and regulatory guidance, Managing and Understanding Artificial Intelligence seeks to provide readers with the knowledge required to make informed decisions in an increasingly AI-driven world. The publication represents a significant contribution to ongoing discussions about the responsible development and governance of artificial intelligence in Europe and beyond.
