Generative AI Meets Service Robots
Jochen Wirtz & Ruth Stock
Abstract
We explore the transformative impact of integrating generative artificial intelligence (GenAI) in the form of large language models (LLMs), large behavioral models (LBMs), and agentic AI into physical service robots and how these will transform physical service encounters. This conceptual article first shows that GenAI-powered service robots (also referred to as GenAI robots) will be able to autonomously deliver more complex, customized, and personalized customer service. Second, GenAI’s increasing capacity for no-code programming is expected to democratize robot training, improvement, and fine-tuning by frontline employees, thus improving robot performance. Third, the implications of GenAI robots are outlined for frontline employees (i.e., their work and job scopes, and a new role as citizen developer), customers (i.e., improved customer experiences and service outcomes), and the service firm (i.e., a pathway to cost-effective service excellence, continuous improvement and agility, alleviation of labor shortage, and the introduction of new ethical, fairness, privacy, health, and safety risks into physical service encounters). This article is the first to explore the theoretical and practical implications of GenAI robots in physical service encounters and opens a new stream of service research.
41 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.85 × 0.4 = 0.34 |
| M · momentum | 1.00 × 0.15 = 0.15 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.