Prof. Frederik Ahlemann, Professor of Information Systems, Digital Innovation and Performance Management at the University of Duisburg-Essen, moderated the panel discussion “Beyond Technology: Lessons, Challenges and Outcomes of AI Transformation,” contributing an impulse on the expected landscape of 2031. The discussion centered on the transition from traditional dispatching toward data-centric systems and service-oriented business models focused on reliability. A key takeaway from the session was that AI transformation should not be viewed as a purely technical challenge; rather, it represents a systemic shift requiring interoperable information systems, integrated data infrastructures, and the active inclusion of the workforce.

The event also highlighted the long-term impact of collaborative research, exemplified by the startup red cable robots. Having emerged from a former ZLV research project within the BMBF Leading-Edge Cluster (EffizienzCluster LogistikRuhr), the spin-off demonstrated how research-driven innovation can evolve into scalable industrial solutions.

For our chair, the event offered an excellent opportunity to connect ongoing research in AI-enabled information systems, digital transformation, and smart infrastructures with current developments in the logistics sector. At the same time, the discussions reinforced that future logistics ecosystems will depend not only on technological capabilities, but also on governance structures, cross-organizational data integration, and human-centered transformation.

At its core, the project focuses on raising awareness among small and medium-sized enterprises (SMEs) regarding the diverse opportunities offered by Artificial Intelligence. Businesses often lack the resources or specific expertise required to implement technological innovations efficiently. This is where the project steps in by providing practical skills that contribute to securing long-term employment and value creation. The support ranges from initial information events to in-depth practical sessions that help companies identify and implement individual AI applications.

The University of Duisburg-Essen plays a central role in this cross-border network, bringing its scientific expertise directly to the region. Key contributors include Prof. Dr. Frederik Ahlemann and Falco Korn, as well as Prof. Dr. Hannes Rothe and Prof. Dr. Marc Eulerich. Together with the other partners—Duisburg Business & Innovation GmbH (lead partner), Rhine-Waal University of Applied Sciences, the Dutch Hogeschool van Arnhem en Nijmegen, and the economic development agencies of the Wesel and Kleve districts—they form a powerful network. This cooperation highlights the importance of technology transfer and demonstrates how collaboration between science and business can create sustainable momentum for the region.

This project is co-financed by the European Union. Interested parties can find more information about the program at www.efre.nrw.

#efrenrw #jtfnrw

Wir untersuchen drei Kernfragen:

• Eintrittswahrscheinlichkeit: Welche KI-Entwicklungen sind bis 2030 wirklich wahrscheinlich?
• Impact: Wie verändern sich Geschäftsprozesse, IT-Landschaften und unsere Arbeitswelt?
• Reifegrad: Wie gut sind Unternehmen heute tatsächlich vorbereitet?

Ihre Expertise ist gefragt! Wir laden Führungskräfte, IT-Verantwortliche und Professionals aller Branchen ein, an der Umfrage teilzunehmen. Ihre Einschätzung hilft uns, Spekulationen von fundierten Prognosen zu trennen:

• Dauer: ca. 15 Minuten
• Hier teilnehmen: Link zur Studie 
• Ihr Benefit: Als Dankeschön für Ihre Teilnahme bieten wir Ihnen auf Wunsch einen exklusiven Vorab-Einblick in die Ergebnisse.

Our contributions reflect this perspective from two different angles:

The first paper, “Mind the Mess: A Matrix of Personal Knowledge Management Challenges across the Knowledge Lifecycle” (Falco Korn, Dennis Kolender, Rafael Ziolkowski, Erik Karger, Frederik Ahlemann), examines how knowledge workers navigate increasingly fragmented digital environments. Based on 27 semi-structured expert interviews, the study identifies 50 distinct challenges in personal knowledge management and structures them into a multi-layered framework spanning cognitive, behavioral, technical, and information-related dimensions. By mapping these challenges onto core knowledge management processes, the paper provides a systematic way to diagnose where and why personal knowledge management breaks—and lays a foundation for designing more effective support systems.

The second paper, “Organizing for Digital Business Model Innovation in Incumbent Firms: Which Digital Innovation Management Configurations Enable or Constrain Digital Business Model Innovation?” (David Hoffmann, Frederik Ahlemann, Rafael Ziolkowski, Erik Karger, Kalle Lyytinen, Stefan Reining), shifts the focus to the organizational level. Drawing on survey data from 251 firms and applying a configurational approach (fsQCA), the study identifies multiple pathways through which firms can successfully—or unsuccessfully—enable digitally driven business model innovation. The findings highlight that different configurations of digital innovation management can complement, substitute, or even counteract each other depending on strategic context and environmental turbulence, offering a more nuanced understanding of how organizations can structure for innovation.

Together, both papers contribute to a deeper understanding of how individuals and organizations can better navigate and shape digital complexity—very much in line with the broader ECIS2026 agenda.

This new title better reflects our current research trajectory and our focus on how digital innovation drives organizational excellence.

Along with our new name, we have relocated our offices. You can now find us in R09 R03 (same building, third floor), where we are happy to be sharing the corridor with our colleagues from the Chair of Enterprise Systems, Platforms, and Architectures (EPA).

We look forward to this new chapter and to welcoming you to our new premises!

The ECIS 2026 Doctoral Consortium is a highly selective event: participation is limited to 20 doctoral students, with each university permitted to nominate only one candidate. The consortium will take place June 12–14, 2026, at Villa Gallarati Scotti, a historic 18th-century estate near Milan, ahead of the main ECIS conference (June 15–17).

The dissertation project addresses a pressing challenge of contemporary academic life. Students increasingly procrastinate through social media, a phenomenon Korn conceptualizes as Social Media-Driven Academic Procrastination (SMAP). At the heart of the research is the question of how personalized, digital micro-interventions can reduce SMAP in a sustainable and theoretically grounded way. Methodologically, the project follows the echeloned Design Science Research approach by Tuunanen et al. (2024), which links problem and solution spaces across validated, self-contained stages. Through a combination of methods (e.g. in-depth interviews, structural equation modeling and prototype development), the project aims to develop an empirically grounded understanding of SMAP mechanisms, and from that, a class of archetype-specific, context-sensitive micro-interventions. The resulting design knowledge is intended to be transferable beyond the university context to related application areas.

Inside the Research: A Systematic Deep Dive

Driven by the increasing urgency of the global wildfire crisis, our team conducted a large-scale bibliometric study. By analyzing a dataset of 1,985 peer-reviewed publications sourced from Scopus, we have mapped the evolution of this field and identified the core pillars of current AI-driven fire management.

Our analysis highlights three critical thematic clusters that are shaping the industry:

• Geospatial & Climatic Analysis: Utilizing remote sensing to decode the complex relationship between climate patterns and fire outbreaks.
• Detection & Monitoring: Advancing algorithms that enable faster ignition spotting and real-time surveillance.
• Predictive Modeling: Developing machine learning models that assess risk and simulate fire behavior to stay one step ahead of the flames.

Setting the Agenda for the Future

Our findings underscore that while AI has made significant strides, the field must become even more integrated and transparent. In the paper, we propose a targeted research agenda focusing on three transformative areas:

1. Multimodal Data Integration: Merging diverse data streams for a holistic view of the fireground.
2. Explainable AI (XAI): Building "black box" models that provide understandable insights for human decision-makers.
3. Real-Time Collaboration: Enhancing the synergy between AI systems and emergency responders during active crises.

"With this study, we aim to provide a systematic understanding of the current AI landscape in wildfire research. Our goal is to support the scientific community in developing more robust, technological responses to the escalating challenges of wildland fires."

Read the full paper here: https://link.springer.com/article/10.1007/s44163-026-01087-5

To address this gap, Prof. Dr. Frederik Ahlemann and his research team at the University of Duisburg-Essen have partnered with the management and technology consultancy Campana & Schott to conduct a large-scale empirical study. The goal: building an evidence-based picture of how AI will reshape organizations by 2030.

What the Study Investigates

The study explores three core dimensions that are critical for both research and practice:

• Likelihood of AI developments: Which technological advances in AI are most probable by 2030 — and which are overestimated?
• Organizational impact: How will AI change business processes, IT landscapes, operating models, and the nature of work itself?
• Preparedness: How well-positioned are organizations today to navigate these changes — and where are the critical gaps?

Why This Matters

Despite the growing volume of AI-related predictions, decision-makers still lack a structured, empirically grounded outlook to inform strategic planning. This study aims to separate well-founded expectations from speculative forecasts — providing executives, IT leaders, and transformation teams with a reliable basis for action.

The survey takes approximately 15 minutes. We welcome responses from executives, IT leaders, and professionals across all industries. Your input will help shape a robust, practice-oriented perspective on the future of AI in organizations.
Feel free to share the survey link with colleagues and decision-makers in your network. The more perspectives we capture, the stronger the results will be.

You can visit the survey via this link.

The colloquium featured a rich program spanning a wide range of current research topics — from maturity models and human-AI task delegation to socio-psychological dynamics in virtual environments, digital micro-interventions, CBDC architectures, anthropomorphic digital human agents, and smart city business models.

At the heart of the event were in-depth paper discussions that gave participants the opportunity to reflect on ongoing work, receive constructive feedback, and explore new perspectives. The format once again proved to be a valuable platform for strengthening collaboration and scholarly exchange across institutional boundaries. We extend the thanks to all participating colleagues for the engaging and productive discussions.