From Intention To Actual Use: Explaining The Adoption Of Generative-AI Whatsapp Chatbots For Financial And Health Information With An Extended UTAUT2 Model And Behavioral Log Data
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Abstract
Generative artificial intelligence is increasingly embedded in familiar messaging platforms, expanding access to intelligent information services. This study develops an extended UTAUT2 model to examine adoption of an AI-enabled WhatsApp bot integrating deterministic information utilities with a Gemini-powered stock analysis feature. The model distinguishes behavioural intention from actual use and adds trust in AI-generated information, perceived risk, and perceived information accuracy. Its main methodological contribution is linking survey-based perceptions with pseudonymised behavioural records, enabling direct assessment of intention behaviour correspondence without treating self-reported use as observed interaction. The open-source artifact, wa bot quote, provides cryptocurrency, stock, health and fitness, football, QR-code, and other utilities, while its repository documents Gemini integration for stock analysis. The manuscript therefore separates capabilities verified from the repository from outcomes requiring future empirical deployment. It specifies a reproducible protocol covering informed consent, data minimisation, secure logging, measurement validation, partial least squares structural equation modelling, measurement invariance, multi-group analysis, predictive assessment, and robustness testing. By integrating perceptions with behavioural evidence, the framework supports transparent evaluation of technology acceptance, user-group differences, and discrepancies between stated intentions and actual interactions. Accordingly, the manuscript constitutes a rigorous empirical research framework rather than a completed results paper and avoids presenting uncollected evidence or fabricated findings.
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