Artificial intelligence is increasingly being integrated into healthcare, offering new ways to detect disease, support clinical decisions and improve patient care, according to analysis by the World Economic Forum.
According to the World Health Organization, billions of people worldwide still lack access to essential healthcare services, highlighting the need for more efficient and scalable solutions. In that context, AI is being explored as a way to support clinicians, particularly in diagnostics and early intervention.
Earlier and more accurate diagnosis
One of the most significant uses of AI is in medical imaging, where systems can identify patterns that may not be visible to the human eye. In stroke care, for example, AI tools can analyse brain scans to help determine when an event occurred, a key factor in deciding treatment.
Research is also moving diagnosis further upstream. A model developed by scientists at the University of Oxford can estimate a patient’s risk of developing heart failure years before symptoms appear. By analysing subtle changes in tissue around the heart, the system provides a personalised risk score that could allow for earlier monitoring and intervention.
In large-scale testing across hospitals in England, the tool predicted risk over a five-year period with an accuracy of 86%, offering a potential step towards more preventive care.
Supporting care and reducing workload
AI is also being used to support decision-making in time-sensitive settings such as emergency care. Data-driven models can help identify which patients are more likely to require hospital treatment, improving consistency while easing pressure on services.
At the same time, healthcare providers are exploring AI tools to reduce administrative workload, including systems that generate clinical notes and organise patient records. This could allow clinicians to spend more time on direct patient care.
A shift towards prevention
By analysing large volumes of health data, AI is helping researchers identify early indicators of disease, raising the possibility of moving healthcare towards earlier intervention rather than reactive treatment.
Risks and limits
Despite its potential, the use of AI raises concerns around accuracy, bias and data privacy. Experts stress that such systems must be carefully validated and used alongside clinical judgement.
Regulation is evolving to address these challenges. In the United States, the Food and Drug Administration oversees AI-based medical tools to ensure they are safe and effective.
A supporting role
AI is widely seen as a complement to healthcare professionals rather than a replacement. While it can process large amounts of data quickly, human expertise remains essential in interpreting results and making decisions.
As the technology develops, its role in healthcare is expected to grow, particularly in early diagnosis, system efficiency and preventive care.