A4 Refereed article in a conference publication
Generative AI as a Socio-Technical Facilitator: A Case Study of AI-Supported Group Formation and Co-Creation
Authors: Pohjola, T.; Maijanen, E.; Sjöberg, M.
Editors: Babic, Snjezana; Car, Zeljka; Cicin-Sain, Marina; Ergovic, Pavle; Galinac Grbac, Tihana; Gros, Stjepan; Jovic, Alan; Jurekovic, Darko; Katulic, Tihomir; Koricic, Marko; Kralj, Nenad; Mornar, Vedran; Petrovic, Juraj; Skala, Karolj; Skvorc, Dejan; Sruk, Vlado; Tijan, Edvard; Valacich, Joe; Vrcek, Neven; Vrdoljak, Boris
Conference name: MIPRO ICT and Electronics Convention
Publication year: 2026
Journal: International Convention on Information and Communication Technology, Electronics and Microelectronics
Book title : 2026 49th MIPRO ICT and Electronics Convention (MIPRO)
Volume: 49
First page : 1178
Last page: 1183
ISBN: 979-8-3315-6310-3
eISBN: 979-8-3315-6309-7
ISSN: 1847-3938
eISSN: 1847-3946
DOI: https://doi.org/10.1109/MIPRO70003.2026.11591640
Publication's open availability at the time of reporting: No Open Access
Publication channel's open availability : No Open Access publication channel
Web address : https://ieeexplore.ieee.org/document/11591640
While generative AI is widely adopted as an individual productivity tool, its potential to recognize competences and orchestrate collective processes (e.g., group formation and collaborative innovation) remains underexplored. This paper presents a case study examining how a custom AI facilitation tool supported co-creation among diverse creative professionals at a European workshop event. Research connects to Service-Dominant logic and the concept of operant resource integration. First, the AI tool structured conversational assessments to map participants' competencies, goals, and constraints-generating individualized "upskilling profiles" that captured both explicit skills and tacit professional orientations. Second, it used these profiles to form heterogeneous working groups with complementary expertise and shared intentions, then facilitated iterative co-creation through reflective prompts, structural suggestions, and real-time synthesis. Our empirical data comprises 34 AI-participant interaction logs and 8 group facilitation transcripts, analyzed using thematic analysis. Findings suggest that AI-supported profiling accelerated resource mapping and reduced barriers to articulating tacit knowledge. Secondly, algorithmically formed groups demonstrated productive complementarity, though success depended on participants' engagement with the AI interface. The paper contributes a concrete example for AI-enhanced collaboration that preserves participant agency while enabling collective sense-making in a digital economy where dynamic team formation and resource integration are critical.