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Friday, May 31, 2024
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artificial intelligence automation workforce

5 workforce and automation trends to reckon with in the early generative AI era

Weighing opportunities vs. challenges presented by AI and automation, business analysts have found Europe and the United States in pretty much the same boat.

However, America may begin to pull away with the opportunities on the strength of three differentiators: its broader base of private-sector tech companies, that sector’s momentum in AI innovation and Washinton’s relatively lighter touch with technology regulation compared with the more cautious climates in Brussels and London.

These are among the key insights ascertained from a reading of a McKinsey Global Institute report posted May 21.

“Amid tightening labor markets and a slowdown in productivity growth, Europe and the United States face shifts in labor demand spurred by AI and automation,” the McKinsey experts write. “Our updated modeling of the future of work finds that demand for workers in STEM-related, healthcare, and other high-skill professions [will] rise, while demand for occupations such as office workers, production workers, and customer service representatives [will] decline.”

Projecting that as much as 30% of current hours worked may be automated by the end of this decade—thanks largely to generative AI—McKinsey advises watching for shifts in employment demand to soon enough become the new normal. Here are five highlights from an online summary of the full report.

1. Demand will change for a range of occupations through 2030, including growth in STEM- and healthcare-related occupations, among others.

Europe and the United States face shifts in labor demand spurred not only by AI and automation but also by efforts to achieve net-zero emissions, an aging population, infrastructure spending, technology investments and growth in e-commerce, the May 21 report states. More:

‘Our analysis finds that demand for occupations such as health professionals and other STEM-related professionals [will] grow by 17% to 30% between 2022 and 2030.’

2. Automation boosted by generative AI will force millions of occupational transitions by 2030.  

McKinsey’s economic modeling suggests that roughly 20% of hours worked could be automated even without gen AI, “implying a significant acceleration,” the authors write. By 2030, they project, Europe could require up to 12 million occupational transitions, affecting 6.5% of current employment. In the United States, required transitions could reach almost 12 million, affecting 7.5% of current employment.

‘Unlike Europe, this magnitude of transitions is broadly in line with the prepandemic norm.’

3. Organizations will need a major skills upgrade.

The occupational transitions noted above herald substantial shifts in workforce skills in a future in which automation and AI are integrated into the workplace, the authors remark. Demand for social and emotional skills could rise by 11% in Europe and by 14% in the United States, they add.

‘Underlying this increase is higher demand for roles requiring interpersonal empathy and leadership skills. These skills are crucial in healthcare and managerial roles in an evolving economy that demands greater adaptability and flexibility.’

4. Retraining will be key to supplying needed skills and adapting to the new work landscape.

Executives surveyed by McKinsey for the May report tend to worry they won’t be able to find the right skills by 2030. More than 25% of respondents believe failing to capture needed skills “could directly harm financial performance and indirectly impede efforts to leverage value from AI.” To acquire the skills they need, McKinsey points out, organizations have three main options—retraining, hiring and contracting.

‘Executives are looking at all three options, with retraining the most widely reported tactic planned to address the skills mismatch. On average executives so inclined said they would retrain 32% of their workforce.’

5. Enhancing human capital at the same time as deploying technology could boost annual productivity growth.

Organizations and policy makers have choices to make. The way they approach AI and automation, along with human capital augmentation, will affect economic and societal outcomes, the McKinsey report authors comment. “Making full use of the advantages on offer from technology,” they emphasize, “will require paying attention to the critical element of human capital.” The authors conclude:

‘In the best-case scenario, workers’ skills will develop and adapt to new technological challenges. Achieving this goal in our new technological age will be highly challenging—but the benefits will be great.’

The executive summary includes a link to a PDF of the full report.

 

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Google AI overviews

Industry Watcher’s Digest

Buzzworthy developments of the past few days.

  • You’ve heard it before and you’ll hear it again: Healthcare AI can free up clinicians to concentrate on patient care. An academic physician who founded a healthcare AI startup gives the promise a new fleshing-out in an interview posted online May 30. “You want doctors to do what they’re meant to do—provide care—and let technology handle the administrative aspects,” Michael Gao, MD, tells Pymnts.com. Gao left his work in internal medicine and healthcare innovation at Weill Cornell Medicine in 2020 to launch SmarterDx. The company supplies AI-equipped software to hospitals interested in improving revenue integrity. SmarterDx made news earlier this month when it closed a $50 million funding round. The interview is conducted by Pymnts’s chief content officer, John Gaffney. It runs 17 minutes and is worth a watch.
     
  • Can you name three things AI can do to improve clinical care? Let Chenyang Lu, PhD, help you. The Washington University professor of engineering and applied science is partial to AI’s ability to help 1) unobtrusively screen for depression, 2) tirelessly monitor cancer patients for deterioration and 3) accurately predict surgery patients’ risk for post-op complications. In a conversation with HIMSS Media, Lu reminds fellow AI enthusiasts that “We are still at the early stage of AI in healthcare. Looking forward, it is imperative to lower the hurdles for implementing AI models in our infrastructure.” Read the rest.
     
  • The healthcare AI market was valued at more than $11 billion in 2021. That estimate impressed a lot of people when it first came out. Then came investment analysts forecasting the market valuation will soon dwarf that sum, reaching $164 billion by 2029. The physician-writer Arjun V.K. Sharma, MD, makes prosaic note of the projection by way of offering poetic perspective on what it all means. “I often think about what gives meaning to the help we offer patients, how that might be shaped by the precision and calculations of a looming revolution from a novel technology,” he writes in a genuinely lovely piece published by Undark. “How do messy human problems fit into a future of healthcare that strives to be so tidily packaged, helmed by the algorithms of artificial intelligence that many are so eager to adopt?”
     
  • In an AI hospital, virtual doctors treat virtual patients. It’s a real thing in China. At one such institution, human physicians and trainees work with gen AI-simulated patients too, improving their skills alongside their AI counterparts doing the same. The AI doctors can treat 10,000 patients in just a few days, reports the Global Times, a daily tabloid newspaper published by the Chinese Communist Party. The outlet notes that the AI hospital’s “evolved doctor agents” topped 93% accuracy on a U.S. Medical Licensing Exam covering major respiratory diseases. “We cannot deny that AI healthcare can surpass human physiological and intellectual limits in certain aspects, enhancing the precision and efficiency of healthcare services,” the article states. “However, one thing is certain: AI can never replace humans.” Well that’s a relief. Read the whole thing.
     
  • In theory, healthcare AI and genomic medicine should play well together. At some point, they probably will. For now there’s still some ways to go. The UK-based outlet Diginomica has gathered thoughts on the matter from experts in both fields. One of the watchers is Dr. Richard Scott, CEO of Genomics England, a company set up by Britain’s Department of Health and Social Care. “We are in a period where we can see that AI and machine learning will—or could—bring some really substantial changes for the current uses of genomics.” Read the rest.
     
  • Google has enticed two notable cloud execs to defect to Mountain View—one from Redmond and one from Seattle. The Information is reporting that Saurabh Tiwary, a former corporate vice president at Microsoft, will join Google Cloud June 3 as general manager of cloud AI, a newly created role, while Raj Pai, a former vice president at AWS, is set to oversee product management of Google’s cloud AI team, reporting to Tiwary.
     
  • Meanwhile Google is explaining itself on those gen AI overviews its searches have been serving up. They’re probably feeling stung by the criticisms the items have elicited. That would be understandable. Some of the takedowns have been borderline cruel. Others seem to have come from users trying to trick Google Search into flubbing up. In any case, Google’s head of search, Liz Reid, posted a blog entry tackling the subject head-on May 30. “At the scale of the web, with billions of queries coming in every day, there are bound to be some oddities and errors,” Reid writes. “We’ll keep improving when and how we show AI Overviews and strengthening our protections. [W]e’re very grateful for the ongoing feedback.” Reaction was swift and, in places, unforgiving. Sample snark from The Verge: “If Google is going to compete, it has to move fast. But it also needs to maintain user trust. That could be difficult to regain after AI Overviews told us all to eat Elmer’s glue.” (Don’t feel bad. I laughed too.)
     
  • Recent research roundup:
     
  • Funding news of note:
     
  • From AIin.Healthcare’s news partners:
     

 

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