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Marketplace for Multi-Party Development of Artificial Intelligence Systems: Perceptions on Value Creation
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0001-9968-2440
University of Applied Sciences Northwestern Switzerland (FHNW), Switzerland.
2025 (English)In: Software Business, ICSOB 2024 / [ed] Efi Papatheocharous, Siamak Farshidi, Slinger Jansen, Sonja Hyrynsalmi, Springer Science+Business Media B.V., 2025, Vol. 539, p. 309-323Conference paper, Published paper (Refereed)
Abstract [en]

The field of artificial intelligence (AI) has yet to fully capitalise on the potential to develop AI systems through collaboration between system developers and data scientists, especially when they belong to different organisations. We studied how using a marketplace creates value in such value chains by allowing organisations to advertise and share AI assets like data and models and enable multi-party development of AI systems while protecting these assets. The paper describes an embedded multi-case study of a marketplace under development, the Bonseyes marketplace. The cases were a collaboration between universities, a large company outsourcing data science, and a small business offering AI models as products. Value creation was linked to reduced development time, streamlined product communication, and protection of shared assets. However, participants required data protection concerns to be addressed, as well as marketplace maturity. The marketplace created value with clear goals for developing an AI system and supporting tools, templates, and examples. Our study benefits researchers wanting to advance AI systems development by offering rich examples of how a marketplace can enable multi-party collaborations.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2025. Vol. 539, p. 309-323
Series
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 539
Keywords [en]
marketplace, AI systems engineering, case study-based evaluation
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-27297DOI: 10.1007/978-3-031-85849-9_25ISI: 001476891400023Scopus ID: 2-s2.0-105001306568OAI: oai:DiVA.org:bth-27297DiVA, id: diva2:1923200
Conference
15th International Conference on Software Business, ICSOB 2024, Utrecht, Nov 18-20, 2024
Part of project
Bonseyes – Platform for Open Development of Systems of Artificial Intelligence
Funder
EU, Horizon 2020, 732204Available from: 2024-12-20 Created: 2024-12-20 Last updated: 2025-09-30Bibliographically approved

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Maksimov, Yuliyan

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