Artificial intelligence (AI) has the potential to transform healthcare into a more sustainable, efficient, and equitable system. By analysing vast amounts of data quickly and accurately, AI can support clinical decision-making, reduce unnecessary investigations, and help personalise treatment plans—leading to better patient outcomes and fewer resource-intensive interventions. Early detection of disease through AI-enabled diagnostics can reduce the burden on health services and improve long-term public health.
In sustainable healthcare, AI can also optimise workflows, predict demand, and reduce waste. For example, machine learning algorithms can improve supply chain logistics, anticipate staffing needs, or monitor energy consumption in healthcare facilities—cutting both carbon emissions and costs. In digital pathology and radiology, AI tools can streamline processes, allowing clinicians to focus their time where it’s needed most.
Importantly, AI can also help address health inequities by identifying gaps in care or tailoring services to underserved populations. Remote monitoring tools powered by AI can extend care into the community, reduce unnecessary hospital admissions, and support ageing populations to live healthier, more independent lives.
However, AI must be implemented thoughtfully. Ethical concerns around data privacy, algorithmic bias, and transparency must be addressed, and systems should be co-designed with healthcare professionals and patients to ensure trust, fairness, and clinical relevance.
Ultimately, AI is not a replacement for human care, but a tool to enhance it. When used responsibly, it can support the shift toward sustainable healthcare systems that are resilient, preventative, and capable of meeting the needs of both people and the planet.
