Case Study of the Role of AI in Service Development : AI Capabilities in Service Development - Discourse Analysis on Annual Reports
Year: 2026
Type: dissertation
Abstract: This thesis aims to study the role of AI in service development by exploring the potential supportive impact of AI capabilities and AI applications on service development. The current research seems to focus on investigating AI capabilities and AI applications as separate concepts. The prior research studies AI capabilities in service development, yet it does not connect AI applications to this discussion. Therefore, in order to reach a comprehensive understanding of AI capabilities and the possible supportive impact on service development, it is important to research the possible benefits achieved through AI applications in service development. The thesis is based on a multiple-case study of five multinational technology companies. The selected multiple case study was chosen as a methodology, because it is a recommended research strategy to study a modern phenomenon. It allows the researcher to compare the prior theory with the findings and to find novel insights, possibly. The selected case companies' core businesses focus on offering AI capabilities through AI applications, which allowed us to make a comparison between their AI offerings. The empirical data were collected from online material using the case companies’ annual reports as primary data and other online data sources as secondary data. The empirical data were first analyzed using within-case analysis, followed by cross-case analysis, allowing a discourse between theory and data insights. Although the potential supportive impact of AI capabilities, especially in relationalized service, and AI applications in service development is somewhat unclear in the literature, the empirical findings of this study offer a novel insight into the connection. Consequently, both the theory and empirical findings suggest that there are AI capabilities and AI applications that can support service development through productivity and customer experience improvements. Accordingly, AI’s conversational and personalization capabilities seem to respond to relationalized service characteristics at some level, and support service process in the service interaction stage. Another research insight is that AI has capabilities for content creation, reasoning, decision-making, data analysis, and multimodal understanding, which all support the service process. Empirical findings are in line with the literature by suggesting that automation, data insights, predictions, and recommendations are part of supporting AI capabilities. Another novel finding is that software-based AI applications are used to support service development by offering assistance for productivity and customer experience improvement. Moreover, it seems that generative AI, machine learning, and predictive AI are the most popular AI types for AI applications to support service development. The empirical findings emphasize that agentic AI is slightly used in both productivity and customer experience improvement, and, however, the theory suggests that it is becoming more popular. Final insight is that it seems that AGI has not been implemented, and based on the literature, it is seen as the AI of the future.
Source: Osuva (University of Vaasa)
Author: Sirniö, Sanni
Language: English
Topic: AI in Service Interactions
Subfield: Marketing
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7198821281