Applying artificial intelligence in healthcare: Lessons from the COVID-19 pandemic

The COVID-19 pandemic exposed vulnerabilities in global healthcare systems and highlighted the need for innovative, technology-driven solutions like Artificial Intelligence (AI). While AI holds transformative potential in healthcare, previous research on the topic has been limited and fragmented, leading to an incomplete understanding of the ‘what’, ‘where’ and ‘how’ of its application, as well as its associated benefits and challenges. This motivated this research, which proposes a comprehensive AI framework for healthcare and assesses its effectiveness within the UAE’s healthcare sector. The study provides valuable insights into AI applications for healthcare stakeholders that range from the molecular to the population level. It covers the different computational techniques employed, from machine learning to computer vision, and the various types of data inputs fed into these techniques, including clinical, epidemiological, locational, behavioural and genomic data. Additionally, the research highlights AI‘s capacity to enhance healthcare‘s operational, quality-related and social outcomes, and recognises regulatory policies, technological infrastructure, stakeholder cooperation and innovation readiness as key facilitators of AI adoption. Lastly, we stress the importance of addressing challenges such as data privacy, security, generalisability and algorithmic bias. Our findings are relevant beyond the COVID-19 pandemic in facilitating the development of AI-related policy interventions and support mechanisms for building stronger, more resilient healthcare systems that can withstand future challenges, whether pandemics or other unforeseen health crises.