AI Doctor

CHAPTER 4Drivers of AI Adoption in Healthcare

WE'RE FORTUNATE IN THAT there are many factors driving the development and adoption of artificial intelligence (AI) healthcare solutions (Figure 4.1). Before we talk about anything else, we should start by noting that the main driver of AI adoption in the healthcare industry is the fact that more data than ever before is available in digital formats. Without that, we wouldn't have much to talk about. Then we can move on to topics like improved machine learning (ML) methodologies, increased computing power, cloud computing, healthcare resource shortages, the opportunity to reduce costs, precision medicine, and more.

We'll start with technical issues, such as the availability of data and increasing computing power, because without these, we wouldn't be able to use AI to improve outcomes and cut costs. The issues of outcomes and costs aren't new and will continue into the distant future if we don't use AI or other technologies to address them. However, given the huge amounts of money we invest in healthcare and the fact that our outcomes aren't commensurate with our investments, there's an increasing appetite for any technologies that could address this imbalance.

The main macroeconomic drivers for growth in healthcare AI include ever‐increasing individual healthcare expenses, aging populations, and the imbalance between patients and the healthcare workforce. In 2014, the global expenditure on healthcare increased to 9.9% of the total ...