Anticipatory innovation of professional services: The case of auditing and artificial intelligence

Masashi Goto

Research Policy, 2023, vol. 52, issue 8

Abstract: With the rise of artificial intelligence (AI), professional services firms (PSFs) need to innovate their services to adapt to AI. However, traditional ad hoc innovations driven by individual professionals have limitations in incorporating new technology outside their expertise. Although service R&D—an organizational function for centralized coordination of service innovations in strategically targeted areas—is potentially effective, studies on service R&D have still been scarce. This case study aims to fill the gap by examining how PSFs can establish and utilize service R&D to innovate services, overcoming the challenges of AI adoption. An in-depth qualitative study was conducted on the process by which the Big Four audit firms incorporated AI into their external audit service in Japan in the 2010s. The analysis shows the detailed process of how newly created service R&D organizations advanced AI adoption in the case firms. This study contributes to the literature on innovations in services and PSFs by (1) demonstrating the neglected but critical role of service R&D as an innovation enabler beyond the existing expertise of service firms, (2) constructing a three-phase model of the evolution of the service R&D function, and (3) suggesting the significance of innovation process design for the legitimation of innovations. This study also expands our knowledge of AI adoption, presenting a process tailored to address the challenges inherent in AI adoption for PSFs.

Keywords: Artificial intelligence; Professional service firms; Service innovation; Service R&D; Case study (search for similar items in EconPapers)
JEL-codes: O31 O32 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:respol:v:52:y:2023:i:8:s0048733323001129

DOI: 10.1016/j.respol.2023.104828

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