Title: The role of trust in generative artificial intelligence in enhancing customer experience and engagement in the healthcare sector

Authors: Hamza Muhammad Dawood; Sharfuddin Ahmed Khan

Addresses: University of Electronic Science and Technology (UESTC), Chengdu, Sichuan, China ' Industrial Systems Engineering Program, University of Regina, Regina, Saskatchewanna, Canada

Abstract: This study investigates how trust shapes adoption of generative AI (Gen AI) in healthcare, examining communication, interaction, intimacy, and empathy as antecedents of trust and their effects on customer experience and engagement. Grounded in computers as social actors (CASA) theory, the paper proposes a conceptual framework and tests it using a quantitative survey of 254 respondents in Pakistan analysed with PLS-SEM. Results show trust in Gen AI positively influences customer experience and engagement; communication, interaction, and empathy significantly enhance trust, while intimacy does not. The study also tests commitment as a moderator between trust and customer outcomes and highlights theoretical contributions by extending CASA to Gen AI chatbots and emphasising anthropomorphic design. Practical implications urge healthcare managers to prioritise user-friendly, trust-building Gen AI systems for both professionals and patients, focusing on effective communication, high-quality interaction, and empathetic interfaces. Limitations include cross-sectional data and a single-country context; future research should pursue longitudinal and cross-cultural studies to validate and extend findings across diverse healthcare environments.

Keywords: generative AI; customer experience; customer engagement; health sector.

DOI: 10.1504/IJGAIB.2026.151804

International Journal of Generative Artificial Intelligence in Business, 2026 Vol.1 No.1/2, pp.210 - 237

Received: 22 Jun 2025
Accepted: 01 Jul 2025
Published online: 20 Feb 2026 *