Michael Wessel ([email protected]; corresponding author) is chaired Professor of Business Information Systems, especially E-Commerce and Digital Business at the Friedrich Schiller University Jena, Germany and Associate Professor at the Department of Digitalization, Copenhagen Business School, Denmark. He holds a PhD in Information Systems from the Technical University of Darmstadt, Germany. Dr. Wessel’s current research projects, which are mainly empirical and quantitative, include the management of digital platforms, the design of consumer-oriented e-commerce solutions, the development of digital and data-based business models, the potential of digital entrepreneurship, and the interaction between humans and AI/algorithms. His work has been published in such journals as Journal of Management Information Systems, Journal of Information Technology, Information Systems Journal, Decision Support Systems, and others. He serves as Associate Editor for the European Journal of Information Systems.
Martin Adam ([email protected]) is chaired Professor of Information Systems, especially Smart Services, at the University of Goettingen, Germany. His research interests include user-AI collaborations as well as the digital transformation of work and people. Dr. Adam’s work has been published in such journals as Information Systems Research, Journal of the Association for Information Systems, Information Systems Journal, European Journal of Information Systems, and many others. He serves as an Associate Editor for Information Systems Journal, Business & Information Systems Engineering, and Electronic Markets.
Alexander Benlian ([email protected]) is chaired Professor of Information Systems and E-Services at Technical University Darmstadt, Germany. He holds a PhD in Business Administration and Management Information Systems from LMU Munich, Germany. Dr. Benlian’s research interests include human-AI collaboration, algorithmic management, platform ecosystems and digital transformation. His work has appeared in such journals as, Information Systems Research, Journal of Management Information Systems, MIS Quarterly, and several others. He is Associate Editor of Information Systems Research, Senior Editor of the European Journal of Information Systems, Department Editor of Business & Information Systems Engineering, and serves the Editorial Review Board of MIS Quarterly Executive and Electronic Markets.
Ann Majchrzak ([email protected]) is Professor Emerita of Digital Innovation at Marshall School of Business, University of Southern California. She received her PhD degree in Social Psychology from University of California, Los Angeles. Dr. Majchrzak has authored or coauthored extensively and serves on the editorial boards of many journals in the field. She has held concurrent appointments at Esade Business School (Spain), Ramon Llull University (Spain), and Luiss Business School (Italy). Her research interests include virtual large-scale collaborations for innovation.
Ferdinand Thies ([email protected]) is Professor at the Institute for Digital Technology Management at the Bern University of Applied Sciences, Switzerland. He holds a PhD in Information Systems from the Technical University of Darmstadt, Germany. Dr. Thies’ research interests include digital platforms, entrepreneurship, and AI. He has published in Journal of Management Information Systems, Journal of Business Venturing, Entrepreneurship Theory and Practice, Information Systems Journal, Journal of Information Technology, among others. He serves as Associate Editor for the European Journal of Information Systems.
IntroductionThe emergence of generative artificial intelligence (GenAI) represents a watershed moment in the evolution of digital platforms. GenAI introduces unprecedented capabilities that transform how digital platforms operate and create value [65]. Unlike traditional AI systems, which are focused on pattern recognition and prediction, GenAI can understand context, learn from examples, and create novel outputs across domains such as text, code, images, and video [5, 64].
The timing and importance of examining the impact of GenAI1 on platforms stems from both technological maturity and widespread adoption. Particularly since the introduction of ChatGPT by OpenAI in 2022, major platform providers such as Microsoft, Google, and GitHub have begun to integrate GenAI capabilities into their core offerings, while new platforms built specifically around GenAI are emerging [20, 86]—as exemplified by OpenAI’s platform strategy of opening its application programming interface (API) to third-party developers. As AI-generated content already comprises nearly 20% of Google’s search results,2 these developments are reshaping platform dynamics—from how value is created and captured [20, 40], to who participates in value creation and who faces displacement [47, 106], and how platform governance and quality control are managed [19, 101].
This Special Issue explores how GenAI is transforming platform operations and strategy across multiple stakeholder groups. For platform owners, who organize and manage these digital platforms, it opens up new opportunities to scale operations and create novel value propositions. For complementors—third-party participants who contribute complementary products, services, or content that extend the platform’s core functionality—it enables new forms of value creation while potentially disrupting existing business models [47, 65]. For end users and society at large, it presents both opportunities for innovation and challenges related to governance, equity, and potential job displacement. While all platform stakeholders can leverage GenAI to optimize operations and enhance the user experience in various platform settings, we are only beginning to understand the transformative value of the technology for digital platforms.
Information systems (IS) scholars have made important contributions to the literature on digital platforms [e.g., 18, 23, 25, 67, 74, 80, 92], much of which has been focused on the complex relationship between the triad of users, complementors, and the platform owner, which together form the platform ecosystem. Similarly, IS research has provided important insights regarding the implications of AI for business as well as how the technology could and should be managed [8]. However, with the emergence of GenAI, new research avenues are opening up, providing IS scholars with the opportunity to conduct cutting-edge research on the transformative and value-creating capabilities of this intriguing technology, particularly with respect to digital platforms [65]. As a disruptive technology, GenAI could threaten entire platform industries, while creating groundbreaking opportunities for others by enabling truly innovative services and business models that engage platform stakeholders in novel ways.
To frame these transformations and guide future research, we present an integrative framework that focuses on four key mechanisms through which GenAI is reshaping digital platforms: intelligent automation, democratization, hyper-personalization, and collaborative innovation. In the following, we first establish the theoretical foundation by examining key research perspectives and stakeholders in digital platforms. We then analyze how the four mechanisms reshape platform operations and stakeholder dynamics, situating the special issue papers within this framework. Finally, we outline a research agenda exploring how GenAI transforms relationships between key platform stakeholders in this rapidly evolving domain.
Notes
1.We use the terms “GenAI” and “AI” interchangeably throughout the remainder of the text.
2.https://originality.ai/ai-content-in-google-search-results
3.https://github.com/features/copilot
4.https://investors.upwork.com/news-releases/news-release-details/upwork-expands-ai-innovation-and-unveils-new-solutions-better
5.https://www.tiktok.com/transparency/en-us/content-moderation/
6.https://www.shopify.com/magic
7.https://powerapps.microsoft.com/en-us/ai-builder/
8.https://www.canva.com/magic-design/
9.https://newsroom.spotify.com/2023-02-22/spotify-debuts-a-new-ai-dj-right-in-your-pocket/
10.https://netflixtechblog.com/artwork-personalization-c589f074ad76
11.https://aws.amazon.com/personalize/
12.https://github.blog/news-insights/product-news/github-copilot-chat-beta-now-available-for-all-individuals/
13.https://www.adobe.com/products/firefly.html
14.https://openai.com/research/musenet
15.https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
Acknowledgments
We would like to thank the many anonymous reviewers and the following Associate Editors whose contributions were instrumental in advancing the papers in this Special Issue: Ivo Blohm, Alec W. Cram, Ben Eaton, Jens Förderer, Andreas Fügener, Dominik Gutt, Thomas L. Huber, Philipp Hukal, Thomas Kude, Harris Kyriakou, Gene Moo Lee, Wietske Van Osch, Jella Pfeiffer, Jingchuan Pu, Roopa Raman, Mark de Reuver, Anne-Francoise Rutkowski, Stefan Seidel, Timo Sturm, Christoph Weinert, Markus Weinmann, Martin Wiener, Hong Xu, and Michael Andreas Zaggl. We also thank Philipp Hukal, Thomas Kude, and Carsten Sørensen for reviewing earlier drafts of this Special Issue introduction. Any errors remain ours.
We also benefited greatly from the valuable suggestions and advice of the members of the Special Issue Advisory and Editorial Board: Carmelo Cennamo, Panos Constantinides, Oliver Hinz, Kai-Lung Hui, Robert J. Kauffman, William J. Kettinger, Abhay Mishra, Carsten Sørensen, Shirish C. Srivastava, Bernard C.Y. Tan, Monideepa Tarafdar, Jason Thatcher, Ofir Turel, and David Xu.
Finally, we are grateful to the Editor-in-Chief, Vladimir Zwass, for recognizing the importance of this topic and for his continued support throughout the process.
Disclosure statement
No potential conflict of interest was reported by the author(s).
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Key words and phrases: Generative artificial intelligence, generative AI, GenAI, artificial intelligence, large language model, digital platforms, intelligent automation, platform democratization, hyper-personalization, collaborative innovation