The first step to getting customer-facing staff to use generative AI: an AI that understands the question
Study of 230 customer-facing employees finds query understanding and personalization raise ease of use and usefulness, and organizational AI practices amplify use — published in JOCM
Researchers at the HJ Institute of Technology and Management (HJITM) have published a study analyzing the factors that drive generative AI use among employees who deal directly with customers at B2C companies in the Journal of Organizational Change Management (JOCM, SSCI), an international journal in the field of organizational change management.
The researchers surveyed 230 customer-facing employees across various industries in Korea who use generative AI in their work and analyzed the data using partial least squares structural equation modeling (PLS-SEM). Drawing on the technology acceptance model (TAM), they examined how generative AI’s “query understanding” and “personalization” functions, its effects on simplifying work processes and improving customer service, and organizational AI practices affect use.
The analysis showed that query understanding — the ability to accurately grasp users’ questions — served as the starting point, raising personalization (β=0.455), ease of use (β=0.419), usefulness (β=0.166), process simplification (β=0.261) and customer service improvement (β=0.157). Personalization strongly increased usefulness (β=0.380), and ease of use (β=0.251) and usefulness (β=0.269) in turn led to actual use.
Interestingly, the perception that work had become simpler or customer service had improved did not by itself increase use. Organizational AI practices had mixed effects. The more systematically an organization supported AI use, the stronger the link between usefulness and use (β=0.223), but the weaker the link between perceived customer service improvement and use (β=−0.169). Among the control variables, higher education and higher job rank were associated with greater use.
The study is significant in empirically showing that customer-facing employees’ use of generative AI is determined not only by the tool’s performance but also within the context of organizational strategy and practices. It suggests that companies should choose AI that accurately understands questions and provides personalized answers, and should also put in place guidelines and support systems that help employees connect AI’s usefulness to work performance.
HJITM continues to conduct research on organizational adoption of generative AI and digital transformation.
Key findings
- Query understanding → personalization (β=0.455), ease of use (β=0.419), usefulness (β=0.166), process simplification (β=0.261) and customer service (β=0.157)
- Personalization → usefulness (β=0.380); ease of use (β=0.251) and usefulness (β=0.269) → use
- Perceived process simplification and customer service improvement have no direct effect on use
- Organizational AI practices: strengthen usefulness → use (β=0.223), weaken customer service → use (β=−0.169) · N=230
- Paper
- What influences employee engagement with generative AI in B2C? The moderating role of organizational practices
- Authors
- Hyeon Jo
- Journal
- Journal of Organizational Change Management (Emerald, SSCI), Vol. 38(6), pp. 1117–1143, 2025
- DOI
- 10.1108/JOCM-02-2024-0094
- Cite
- Hyeon Jo (2025). What influences employee engagement with generative AI in B2C? The moderating role of organizational practices. Journal of Organizational Change Management, 38(6), pp. 1117–1143.
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