In recent years, health and healthcare have seen significant advancement and innovation across various dimensions, including scientific findings, biomedical research and development, digital technology, processes and systems. However, healthcare faces significant mounting challenges, including a severe shortage of frontline healthcare workers, widening health disparities in wealthy and low- and middle-income countries, and all-time-high health spending that has failed to deliver the health outcomes countries are targeting for their citizens.

These issues do not have to be intractable. Artificial intelligence (AI), powered by machine learning (ML) and deep learning (DL) techniques, has been hailed as a potential solution to many of these global healthcare challenges. Use cases exist today that are both feasible and hold massive potential for impact – if responsible and ethical approaches are fully considered in their implementation.

For this report, more than 400 attainable AI examples and applications have been synthesized, with the potential to change global health outcomes. The collaboration involved over 50 experts from biopharma leaders, healthcare providers, insurers, technology firms and innovators, government, academia, and non-governmental organizations to gain insights on the enablers of adoption. The body of work presents promising use cases for AI in healthcare, identifies barriers to implementation and provides supporting principles for acceleration.