While we expect these numbers to rise over time-both in and out of health care-health care appears to lag. Still, they allow for a systematic comparison across industries.
The skills listed in job postings are just one measure of technology adoption. This is lower than other skilled industries such as professional, scientific, or technical services, finance and insurance, and educational services. 8 Even for the relatively-skilled job postings in hospitals, which includes doctors, nurses, medical technicians, research lab workers, and managers, only approximately 1 in 1,250 job postings required AI skills. The relatively low rate of AI in job postings is not driven by social assistance. Just above construction is health care and social assistance, where 1 in 1,850 jobs required AI skills. The next few industries-manufacturing, mining, and agriculture-may be a surprise to those that have been less focused on how AI has enabled opportunities in robotics and distribution.
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Professional services and finance also rank relatively high. More than 1 in 100 of all jobs in the information industry require some AI-related skills. At the top of the figure is the information industry, which includes large technology companies such as Google and Microsoft. 6 This data, collected by Burning Glass Technologies, 7 is based on over 40,000 online job boards and company websites. job advertisements that require AI-related skills by industry (defined by two-digits NAICS codes) for the years 2015-2018. 5 As a technology evolves and spreads across application sectors, labor demand adjusts to include the type of skills required to adopt the technology, up to a point when the technology is sufficiently pervasive that such skills are no longer explicitly listed in job postings.įigure 1 shows the percentage of U.S. Job advertisements provide a window into technology diffusion patterns.
job advertisements that require AI-related skills.
We provide an early glance into AI adoption patterns as observed through U.S. However, despite the hype and potential, there has been little AI adoption in health care. 4 If AI technologies have a similar impact on healthcare as in other industries such as retail and financial services, then health care can become more effective and more efficient, improving the daily lives of millions of people. health care spending is higher per capita than other OECD countries. In 2019, 11% of American workers were employed in health care, and health care expenditures accounted for over 17% of gross domestic product. These sentiments have been detailed in numerous reports from nonprofits, private consultancies, and governments including the World Health Organization and the U.S.
The major medical journals have all dedicated space to research articles and editorials about AI. ML4H and CHIL, in contrast, provide forums for scholars to present the latest advances in academic research. For example, AI Med and the Ai4 Healthcare Summit are two of many conferences dedicated to facilitating the adoption of AI in health care organizations. There are dozens of academic and industry conferences dedicated to describing the opportunity for AI in health care. The progress and promise of clinical AI algorithms range from image-based diagnosis in radiology and dermatology to surgery, and from patient monitoring to genome interpretation and drug discovery. For instance, Eric Topol’s “Deep Medicine: How Artificial Intelligence can make Health Care Human Again,” highlights AI’s potential to improve the lives of doctors and patients.
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