THE AI PARADOX IN HEALTHCARE: Investigating the Non-Linear Relationship Between Artificial Intelligence Adoption and Patient-Perceived Empathy in Hospitals in Tricity Area in Punjab - Pathania, Garima; Bansal, Dr. Ashok (International Journal of Aquatic Research and Environmental Studies, 2026)
Background: The rapid infusion of Artificial Intelligence (AI) into hospital ecosystems has generated substantial discourse around efficiency and clinical accuracy. However, a critical and underexplored tension exists between technological optimization and the fundamentally human dimension of healthcare — empathy. This paper investigates the non-linear, potentially paradoxical relationship between AI adoption intensity and patient-perceived empathy across private super specialty hospitals in the Tricity region (Chandigarh, Mohali, and Panchkula), North India. Methods: Drawing on the Technology-Organization-Environment (TOE) framework for adoption analysis and an adapted SERVQUAL model for service quality measurement, this study employs a mixed-method, multi-stakeholder design. The empirical investigation spans 12 accredited private hospitals (>100 bed capacity) in the Tricity — including Fortis Hospital Mohali, Max Super Speciality Hospital, Sohana Hospital, Grecian Super Speciality Hospital, Ivy Hospital, Shalby Hospital, Paras Hospital Panchkula, Alchemist Hospital, Ojas Super Speciality Hospital, Healing Hospital Chandigarh, Eden Critical Care Hospital, and Cloudnine Hospital. Quantitative data are collected from approximately 400 patients (Cochran's formula, n=385) and 70-80 management/staff respondents; qualitative insights emerge from 15-20 semi structured interviews with hospital CEOs and Medical Directors. Key Argument: We posit an "Optimization-Satisfaction Paradox": while AI adoption demonstrably improves Responsiveness, Reliability, and Tangibility dimensions of SERVQUAL, its relationship with patient-perceived Empathy follows an inverted-U curve. Moderate AI integration — where AI augments rather than replaces human interaction — is associated with peak empathy scores. Beyond a tipping point, excessive automation erodes the emotional fabric of care, depressing patient satisfaction despite operational excellence.
Keywords: AI adoption in healthcare, Patient empathy, SERVQUAL, TOE framework, Tricity hospitals, Healthcare 4.0, Human-AI interaction, Optimization-Satisfaction Paradox, Private super-specialty hospitals, North India