Epistemic ethicality and agentic artificial intelligence: exploring cognitive affective ontologies of trust and engagement in omnichannel healthcare ecosystems

Purpose This study examines the impact of the perceived ethicality of agentic artificial intelligence systems on patient trust and engagement in digital healthcare services. In addition, it explores the moderating effect of omnichannel integration in reinforcing these relationships. This study aims to present a theoretically grounded and empirically validated model elucidating how ethical design and experiential coherence enhance trust-based engagement in artificial intelligence–driven healthcare ecosystems. Design/methodology/approach An integrated empirical research design that combines correlational and causal modeling was used for this study. Data were collected from 1,728 digital health users across India, Singapore and the USA through a structured questionnaire adapted from validated scales. Partial least squares structural equation modeling with bootstrapping was used to test direct, indirect and moderated relationships. Reliability, validity and measurement invariance were confirmed through confirmatory factor analysis and MICOM testing. Findings The results indicated that perceived ethicality significantly enhanced patient trust (β = 0.462, p < 0.001) and engagement (β = 0.212, p < 0.001), both directly and indirectly through trust (indirect β = 0.194, p < 0.001). Omnichannel integration positively moderates the relationship between ethicality and trust (interaction β = 0.085, p < 0.001), demonstrating that consistent multichannel service delivery enhances ethical perceptions and strengthens relational confidence. Privacy concerns exerted a significant negative influence on trust, reaffirming the centrality of data security in ethical artificial intelligence engagement. Practical implications The findings underscore the necessity for managers to incorporate ethical design, algorithmic transparency and privacy assurance within artificial intelligence–based healthcare systems. Consistently integrating these ethical principles across digital and physical channels can address chronic trust deficits, enhance patient retention and create new opportunities for personalized health management. The proposed model enables organizations to increase user loyalty, gain a competitive advantage through ethical differentiation and align service innovations with societal expectations for responsible technology. Originality/value To the best of the authors’ knowledge, this study is among the first to empirically link ethical artificial intelligence, patient trust and engagement through an integrated model incorporating omnichannel consistency as a contextual enhancer. It extends service and engagement theories into the emerging domain of AI ethics, demonstrating that ethical perception is both a cognitive and emotional driver of engagement. Methodologically, the study introduces cross-cultural testing and moderated mediation analysis to establish a replicable framework for future research on ethical technology management.