From crisis to resilience: human-AI collaboration for sustainable healthcare systems post-COVID-19, Sunday Clement, Abdullah Khataan

Sunday Edem Clement
DBA Research Scholar, Rushford Business School
NSIA-LUTH Cancer Centre
Nigeria
ORCID: 0009-0005-1242-6011
Dr Abdullah M. Khataan
College of Management and Technology, Arab Academy for Science, Technology & Maritime Transport
Egypt
ORCID: 0009-0004-6279-1685

Purpose: The COVID-19 pandemic exposed critical vulnerabilities in global healthcare systems while simultaneously accelerating the adoption of Artificial Intelligence (AI). This study aims to examine how collaboration between AI and human intelligence can transform crisis-driven responses into resilient and sustainable healthcare systems in the post-COVID-19 era. It seeks to explore the complementary roles of AI efficiency and human judgment in enhancing long-term healthcare sustainability.
Design: The study is based upon a Systematic Literature Review (SLR) of 35 peer-reviewed articles published in the English language during 2016-2026, focusing on AI applications, human decision-making, and sustainability in healthcare with respect to COVID-19. The studies were included to synthesise the key findings and draw the conclusions on the basis of the set inclusion and exclusion criteria. The selected studies were analysed to perform thematic analysis using Braun and Clarke’s method, which includes the following six steps: familiarisation, coding, generating themes, reviewing themes, defining themes and writing the report.
Findings: The review identifies key themes, including AI-driven efficiency, human-centric ethical and contextual decision-making, limitations of AI (bias, transparency, trust), constraints of human-only systems (scalability, cognitive bias), the emergence of hybrid intelligence, the role of governance and ethical oversight, and sustainability as a long-term outcome. The findings are likely to highlight that collaborative intelligence offers a more effective pathway to resilient and sustainable healthcare than isolated reliance on either AI or human judgment. It further highlights that reliance solely on AI may lead to issues such as algorithmic bias, lack of transparency, and trust deficits, whereas exclusive dependence on human judgment may limit scalability and efficiency. Based on the synthesised insights, the study develops a conceptual framework that integrates AI capabilities, human intelligence, governance mechanisms, and sustainability outcomes.
Originality: It integrates crisis-response insights from COVID-19 with sustainability and knowledge management perspectives, proposing a comprehensive framework that has both theoretical and practical relevance.
Implications: The proposed framework provides a strategic guide for designing resilient healthcare systems that leverage AI capabilities while preserving human-centric values such as empathy, trust, and ethical accountability, ensuring sustainability in future healthcare crises
Keywords: COVID-19; Healthcare System; Artificial Intelligence; Framework; Pandemic.