![]() ![]() “In the short term, we clearly see the prompt engineers, but then in the longer term, I think the full industries will be readjusted here.” Four tasks with most value add “Many new tasks and jobs will be created,” he continued. “How do you create a better piece of art? How do you write a better book? How do you produce a better movie? How do you actually create the solution for the world to recover from the worst natural disasters?” Sukharevsky asked, rhetorically, citing some examples of tasks that could be “augmented” by all kinds of AI. The former is already here and disrupting the white-collar workforce, while the latter is also here but takes longer to deploy due to the physical machinery required, and will likely have longer-tail impacts further down the road, especially with projections that much of the current workforce will age out over the coming half-century, and there won’t be enough younger people coming up to replace them. That’s because generative AI and the large language models (LLM) at the center of the uptake of this technology are well-suited for certain kinds of white-collar, so-called “knowledge worker” roles and tasks, as opposed to general AI, robotics, and automation technologies, which may be more useful for more physical tasks such as manufacturing, construction, engineering, transportation, mining and search and rescue. “When people talk today about GenAI, they sometimes view it an interchangeable with AI and robotics, but it is important to be precise,” Sukharevsky said. While generative AI has captured the public interest and imagination, McKinsey believes other AI applications and technologies will also play a major role in reshaping the global economy. If worker transitions and other risks can be managed, generative AI could contribute substantively to economic growth and support a more sustainable, inclusive world.”Īlso, the advent of accessible GenAI has pushed up McKinsey’s previous estimates for workplace automation: “Half of today’s work activities could be automated between 20, with a midpoint in 2045, or roughly a decade earlier than in our previous estimates.” Jobs and tasks most likely to be automated by generative AI and AI, generally However, as the report notes, “workers will need support in learning new skills, and some will change occupations. What that translates to is an addition of “0.2 to 3.3 percentage points annually to productivity growth” to the entire global economy, he said. “You basically could make it significantly faster to perform these jobs and do so much more precisely than they are performed today,” Sukharevsky told VentureBeat. This upward revision is due to the incredibly fast embrace and potential use cases of GenAI tools by large and small enterprises.įurthermore, McKinsey finds “current generative AI and other technologies have the potential to automate work activities that absorb 60 to 70% of employees’ time today.”ĭoes this mean massive job loss is inevitable? No, according to Alex Sukharevsky, senior partner and global leader of QuantumBlack, McKinsey’s in-house AI division and report co-author. The $2.6 trillion to $4.4 trillion economic impact figure marks a huge increase over McKinsey’s previous estimates of the AI field’s impact on the economy from 2017, up 15 to 40% from before. ![]() Register Now A bigger impact on an accelerated timeline ![]()
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