ARTIFICIAL INTELLIGENCE IN DIGITAL SERVICE ECOSYSTEMS – A TAXONOMY APPROACH

Artificial intelligence (AI) is increasingly integrated into modern service encounters, shifting from traditional dyadic customer-provider interactions to polyadic interactions between multiple actors in digital service ecosystems. These ecosystems, compromising human and non-human actors (e.g., AI chatbots or service robots), fundamentally alter the nature of value co-creation. Although existing literature examines human-to-human interactions, non-human-to-human, and non-human-to-non-human interactions still need to be explored. Especially, wisdom on AI's roles in service ecosystem interaction is still scarce. To address this research gap, we develop a taxonomy that explores key AI actor attributes, laying the foundation for identifying future AI actor archetypes within digital service ecosystems. Thus, our findings contribute to service science by offering insights into (1) the data that AI relies on, (2) how AI can be integrated into digital service ecosystems, (3) its perceived behavior, and (4) the value it can deliver across digital service ecosystems.

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Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-06-18
Primary Topic
Education, Innovation and Language Studies
Type
article
Field-Weighted Citation Impact
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article

ARTIFICIAL INTELLIGENCE IN DIGITAL SERVICE ECOSYSTEMS – A TAXONOMY APPROACH

Journal of the Association for Information Systems
Education, Innovation and Language Studies
article

ARTIFICIAL INTELLIGENCE IN DIGITAL SERVICE ECOSYSTEMS – A TAXONOMY APPROACH

article en

Abstract

Artificial intelligence (AI) is increasingly integrated into modern service encounters, shifting from traditional dyadic customer-provider interactions to polyadic interactions between multiple actors in digital service ecosystems. These ecosystems, compromising human and non-human actors (e.g., AI chatbots or service robots), fundamentally alter the nature of value co-creation. Although existing literature examines human-to-human interactions, non-human-to-human, and non-human-to-non-human interactions still need to be explored. Especially, wisdom on AI's roles in service ecosystem interaction is still scarce. To address this research gap, we develop a taxonomy that explores key AI actor attributes, laying the foundation for identifying future AI actor archetypes within digital service ecosystems. Thus, our findings contribute to service science by offering insights into (1) the data that AI relies on, (2) how AI can be integrated into digital service ecosystems, (3) its perceived behavior, and (4) the value it can deliver across digital service ecosystems.

Journal of the Association for Information Systems
Paderborn University (DE)
Life in Land
Openalex Percentile: Top 37%
Education, Innovation and Language Studies
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