Raphael Thys
Generative AI to replace jobs as soon as 2030
A new report published by Forrester forecasted the future impact of generative artificial intelligence and how the technology will mainly impact white-collar jobs.
The report description of generative AI stated:
“A set of technologies and techniques that leverage massive corpuses of data, including large language models, to generate new content (e.g., text, video, images, audio, code). Inputs may be natural language prompts or other non-code and nontraditional inputs.”
Forrester alluded to the finding, noting that the technology will replace approximately 2.4 million jobs in the United States by 2030, implying that humans will not be necessary for these tasks and that automated technology will take over.
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Impacting white-collar jobs
Additionally, generative AI may influence another 11 million jobs in the US. The report emphasized that white-collar jobs will be mainly affected. The roles that could be at risk include technical writers, social science research assistants, proofreaders, copywriters, and those in administrative positions.
“Let’s be clear: Generative AI is coming after white-collar jobs,” the report added. “Automation and AI overall will replace 4.9 percent of US jobs by 2030.”
They predicted a loss of 0.6 percent loss owing to automation through 2030. Emphasizing that automation will supersede jobs that are harder to fill, such as in the case of physical robotics being employed to aid frontline workers in 2020 during the COVID-19 pandemic.
Furthermore, Generative AI intends to make up nearly 30 percent of the jobs lost to automation by 2030. “Generative AI will make up a growing percentage of all US jobs lost to automation and AI, climbing from 9.3 percent of jobs lost to automation and AI overall in 2023 to 30.4 percent by 2030,” the report noted.
However, job losses in the next two years will most likely remain subtle until questions on intellectual property rights, copyright, plagiarism, model refresh rates, model bias, ethics, and model response reliability are resolved.
Human-based roles are still necessary
Although, Forrester highlighted that the technology’s potential could also lead to poor performance. For instance, models like ChatGPT often generate “coherent nonsense,” which brings issues of inconsistent customer service to light and as a result, they need to be fixed manually.
The Register cautioned: "Companies will need to hire new, potentially scarce, and expensive talent — developers, business analysts, prompt engineers, even ethicists. The market for this talent will be tight. On the other side, you might lose valuable legacy talent if the pace of change is too fast.”
It’s also possible in some scenarios that automating tasks may yield subpar results but companies may still feel compelled to embrace AI. Firms will have to identify jobs that benefit most from automation to integrate generative AI smoothly.
Employees will have to be trained in skills like prompt engineering and refining input to achieve specific outcomes.