Towards sustainable hybrid intelligence in healthcare: insights from predictive AI adoption in US hospitals, Jacqueline Anena, Rahaman Hasan
Jacqueline Anena
DBA Research Scholar
Rushford Business School
Switzerland
ORCID: 0009-0002-7124-3416
Rahaman Hasan
Canterbury Christ Church University
United Kingdom
ORCID: 0000-0003-1690-2458
Type of Paper: Conceptual Paper
Received: 1 June 2026 / Revised: 23 June 2026 / Accepted: 8 July 2026 / Published: 10 July 2026
DOI: 10.47556/J.WJEMSD.22.5.2026.2
Purpose: This study aims to explore the adoption patterns of predictive Artificial Intelligence (AI) in the United States (US) and its impact on human-centric knowledge management in sustainable healthcare systems.
Design/Methodology: This study conducts a conceptual interpretation of 2023–2024 data from the Office of the National Coordinator for Health Information Technology (ONC) hospital survey.
Findings: Adoption of predictive AI has increased in the US hospitals, from 66% in 2023 to 71% in 2024, as predictive AI becomes more embedded in the healthcare sector. Yet large differences still exist between rural and urban hospitals. This study emphasised the growing significance of governance preparedness, ethical supervision, and mixed AI-human decision-making systems in the establishment of sustainable transformation of healthcare.
Originality/Value: The proposed Sustainable Hybrid Intelligence Framework for Healthcare is a novel contribution to the field, integrating predictive AI capabilities, governance oversight, organisational learning, and human-centric decision-making into a single analytical framework for sustainable healthcare transformation.
Research Limitations: The study focuses on data from the ONC Hospital Survey, which may limit generalisation.
Practical Implications: The findings imply that healthcare institutions adopting predictive AI will increasingly require governance-ready organisational structures capable of integrating algorithmic systems with human-centred clinical decision-making. The disparities in institutional readiness may influence the long-term sustainability and equity of predictive AI transformation across healthcare systems.
Keywords: Predictive Artificial Intelligence; Human-Centric AI; Sustainable Healthcare; Governance; Knowledge Management; Office of the National Coordinator for Health Information Technology.
Citation: Anena, J and Hasan, R. (2026): Towards sustainable hybrid intelligence in healthcare: insights from predictive AI adoption in US hospitals. World Journal of Entrepreneurship, Management and Sustainable Development (WJEMSD), Vol. 22, No. 5, pp. 419-432.