According to a report from The Brookings Institution, the healthcare sector’s integration of AI has been more lackadaisical than anticipated, though medical professionals still see the tech tool as an ideal means of both improving health outcomes as well as gaining key diagnostic and treatment insights.
Indeed, actual adoption metrics may be on the low end, but AI is still a topline consideration in many leading companies’ plans for the near future. Optum, a health insurer, revealed toward the end of 2021 that roughly 85% of health leadership have baked AI into their strategy, and approximately half of executives have tapped into the technology. The COVID-19 pandemic has also played a significant role in bringing digital transformation to the fore.
There is much work to be done in harnessing the full potential of AI in healthcare, however. Specific areas where the tech has yet to show the breadth of its powers are for chronic illness treatment development, helping address workforce shortages, and automating arduous processes for clinicians.
Investment in AI and machine learning solutions typically aims to bring top-tier iterations of these technologies into these considerations. Moreover, seeing as 97% of healthcare data goes unused due to lack of adequate structuring, AI holds the potential to revolutionize care quality by strengthening data comprehension and use in clinical settings.
