Abstract/Summary

Artificial Intelligence (AI) has been identified as the driving force behind the digital transformation of service operations in service industries for innovation. Recently, scholars in management have begun conducting their assessments on AI in innovation management. However, innovation management research misses a structured framework mapping out existing study on the drivers and outcomes of AI adoption in the innovation domain. Moreover, little is known about AI adoption in service industries from the service suppliers’ viewpoints for AI-enabled services. Additionally, study lacks on the factors prompting AI adoption for innovation and empirical studies addressing both the drivers and the outcomes of AI adoption for product/service innovation and process innovation in service industries. To bridge the aforementioned research gaps, this thesis establishes that (a) the managerial intellectual efforts linked to AI in innovation research can be effectively classified into seven distinctive clusters (Chapter 2); (b) AI in innovation research can be effectively charted into framework covering the antecedents and consequences of AI adoption for innovation (Chapter 2); (c) within the service industries, through empirical examination deploying an enhanced (TOE) paradigm with a People (P) dimension, successfully identifies the antecedents of AI adoption in service industries (Chapter 3); and (d) establishes AI adoption impact on product/service innovation and process innovation (Chapter 4), confirms the positive effect of AI adoption for AI-enabled services by offering a model of AI adoption in the service industries.