Gartner argues medicine, law and IT may be affected by the rise of the robots by 2022
Gartner has given a tentative guideline of 2022 as when smart machines and robots may replace highly trained professionals in medicine, law and IT, according to the firm’s latest missive.
The analyst house argues there is a fear of skilled practices becoming ‘utilities’ through the rise of artificial intelligence (AI). One example Gartner uses is through law; if an enterprise uses a smart machine which substitutes for a lawyer, after the first long and expensive period of training, the enterprise can add as many other smart machines as it wants for minimal cost.
“The economics of AI and machine learning will lead to many tasks performed by professionals today becoming low-cost utilities,” said Stephen Prentice, vice president and Gartner fellow. “AI’s effects on different industries will force the enterprise to adjust its business strategy. Many competitive, high margin industries will become more like utilities as AI turns complex work into a metered service that the enterprise pays for, like electricity.”
This analysis comes after a study from Adecco last month, which found that almost half of employees surveyed believed AI would enable them to work more flexibly. 58% of respondents believed that, contrary to AI making them redundant in a matter of years, they would be able to outsource the more mundane aspects of their work to robots and devote more time to creative outlets in the process.
Gartner broadly agrees with this view, although adding AI will inevitably affect employment levels in some industries, saying ‘many others will benefit as AI and automation handle routine and repetitive tasks, leaving more time for the existing workforce to improve service levels, handle more challenging aspects of the role and even ease stress levels in some high-pressure environments’.
“Ultimately, AI and humans will differentiate themselves from each other,” added Prentice. “AI is most successful in addressing problems that are reasonably well-defined and narrow in scope, whereas humans excel at defining problems that need to be solved and at solving complex problems. They can collaborate with one another, and when situations change significantly, humans can adjust.”
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