A Study on the Effect of Voicebot Quality on Intention to Continuous Use in AI Contact Centers in the Financial Sector

• Taekryong Han,
• Dongho Kim,
• Joonyoung Ahn,
• Kijung Ryu,
• Sangmin Lee,

Vol. 19, No. 3, March 31, 2025
10.3837/tiis.2025.03.017, Download Paper (Free):

• AI Contact Center(AICC)
• Expectation Confirmation Model(ECM)
• Intention to Continuous Use
• IS success model
• Voicebot.

Abstract

The COVID-19 pandemic has increased demand for non-face-to-face financial services, leading to the adoption of AI contact centers by financial companies. Large-scale AI models like ChatGPT are accelerating this transition, replacing human agents with AI services expanding to complex tasks beyond traditional chatbots. However, a significant portion of customers still prefer human agents, hindering widespread AI contact center adoption. Existing research focuses on text-based chatbots or voice-activated AI speakers, neglecting AI contact center voicebots' intention to continuous use. This study empirically analyzed the effect of AI contact center voicebot quality on user intention. Results show that while informativeness influences perceived usefulness, accuracy primarily affects expectation confirmation. Accuracy alone does not drive perceived usefulness, suggesting the need for services beyond simple information provision. Delivering sufficient and accurate information through financial sector voicebots is crucial for continuous use, while interaction quality through personalized and anthropomorphic services enhances satisfaction and fosters continued usage.

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