Since the introduction of blockchain technology, both academic and practical discourse has explored its impact on intermediation. Early research emphasized the notion of disintermediation, removing traditional intermediaries through decentralized trust and automated coordination. Yet, more recent studies highlight that blockchain systems often give rise to new forms of intermediation. These roles may not resemble legacy intermediaries but nonetheless fulfil essential functions such as compliance, governance, and technical integration. 

Based on a multiple case study, we investigated how and why such re-intermediation occurs in blockchain ecosystems. Our analysis identifies three recurring drivers, system integrity and resilience, boundary and interface management, and governance efficiency, that structurally necessitate new coordination layers. This study thereby contributes to electronic markets and blockchain literature by offering a refined conceptualization of intermediation dynamics in distributed systems.

I am happy that our paper "Beyond disintermediation: A multiple case study of emerging intermediary roles in blockchain applications" has been accepted for publication in Electronic Markets and is now available online (open access).

Google is investing billions in German data Centers – a strong signal for Germany as a business location. But what at first glance looks like a clear locational advantage could, on closer inspection, prove to be a double-edged sword for Europe's digital sovereignty.

On the one hand, such investments secure access to modern digital infrastructure, create jobs, and give the economy an important boost. They stand for progress and dynamism. So, first of all, it's great that Google is investing in Hesse!

On the other hand, with every new data center built by a US corporation, we are also relinquishing another piece of our digital independence. If Europe wants to be a creator rather than just a user in the digital world, we must specifically promote our own investments and strong European alternatives.

I had the opportunity to briefly comment on this topic in my interviews for hessenschau and SAT.1 news.

Artificial intelligence (AI) is reshaping the way organizations operate, make decisions, and create value. As AI systems become increasingly embedded in business processes, the challenge lies not only in understanding the technology but in managing it effectively. This book provides a comprehensive and structured overview of the principles, strategies, and practices required to integrate AI into modern organizations.

It spans the full AI lifecycle, from foundational concepts and learning methods to the identification of use cases, the implementation of AI strategies and governance mechanisms, as well as the design and development of AI applications. It examines how to design meaningful human-AI interactions, navigate workforce transformation, and operate AI systems at scale. Ethical, legal, and social dimensions are addressed to ensure that AI adoption aligns with values such as transparency, fairness, and accountability.

The book is written for decision-makers, professionals, and students who are not only curious about AI – but who want to actively shape its role in organizations. Whether you’re leading AI initiatives or preparing for the future of work, it provides essential guidance for leveraging AI in a strategic and impactful way. After all, AI hasn’t (yet) figured out how to manage itself.

While artificial intelligence (AI) technologies offer much potential for a wide range of AI uses in organizations, identifying use cases involves making many decisions amidst influencing complications. While nascent methods for identifying such AI use cases seem promising, we know very little about their proven efficacy to actually guide decisions during the use case identification process.

To investigate this efficacy, we conducted action design research at EnBW, one of Europe’s largest energy suppliers. We draw on interviews and an intervention at EnBW’s practices to develop a method, derive six design principles, and describe factors that increase our method’s efficacy. We therefore contribute a novel theoretical perspective on decision-making in contexts of organized anarchy, explaining how organizations can navigate the complexities of decisions in AI use case identification.

I am happy that our paper “Identifying Artificial Intelligence Use Cases: Toward a Method that Facilitates Garbage Can Innovation Processes” has been accepted for publication in Information & Management and is now available online (open access).