Resource, actor, beneficiary, or agent? A service-dominant perspective on generative artificial intelligence
TL;DR
The evidence indicates that GenAI is best understood as an operant resource and, depending on design and context, as an actor and agent, and an update to service-dominant logic’s core concepts and understanding is proposed.
Abstract
Generative artificial intelligence (GenAI) challenges core concepts in service science by blurring boundaries among resources, actors, and beneficiaries. Using service-dominant logic (SDL) as a theoretical lens, we review the distinctive properties of these concepts, introduce the agent concept into SDL, and analyze GenAI’s precise role in service exchange processes. We employ a two-phase research approach: First, we conduct a systematic literature review to derive defining properties of resources, actors, beneficiaries, and agents. We then assess eight contemporary GenAI systems against these properties. Our evidence indicates that GenAI is best understood as an operant resource and, depending on design and context, as an actor and agent. Conversely, GenAI does not qualify as a beneficiary, as it is neither individually capable of phenomenologically experiencing and determining value nor a social system of individuals with such capacities. Our findings propose an update to SDL’s core concepts and understanding, as well as a nuanced conceptual clarification of GenAI’s role, offering guidance for researchers and practitioners seeking to understand and design service interactions that incorporate GenAI.