Pearson’s Research Finds White Collar Roles at Most Risk from Generative AI
Pearson’s latest research suggests that white-collar roles are more at risk from generative AI than blue-collar roles. The study analyzed the impact of generative AI on over 5000 jobs across five countries. These countries included Australia, Brazil, India, the US, and the UK. The findings indicated that around 30% of some white-collar roles may be done by generative AI, while less than 1% of time spent on tasks in blue-collar jobs could be automated.
Much of the time spent on repetitive tasks in white-collar roles, such as appointment scheduling and call answering, can be replicated by generative AI. On the other hand, blue-collar roles, such as landscaping and mechanics, involve manual labor and customer service elements that can’t easily be replicated by AI.
In the US, white-collar jobs most impacted by generative AI include medical secretaries, statement clerks, and accounting clerks. On the other hand, blue-collar roles such as farm products buyers and amusement attendants are among the most affected.
According to Mike Howells, President of Pearson Workforce Skills, understanding which jobs are at risk from AI is crucial for both workers and employers. He emphasized the need to prepare for the future and consider how new roles might be created by generative AI. Howells also stressed the importance of utilizing AI to handle repetitive tasks so that people can focus on high-value activities.
The research also highlighted the least impacted jobs, with chief executives and civil engineers being among the least affected white-collar roles. The study also identified blue-collar jobs such as bus and truck mechanics and dishwashers as being least impacted by generative AI.
Pearson’s research serves as a reminder that the integration of generative AI into the workplace is inevitable and poses both challenges and opportunities for the future of work.
Photo source: Pearson (Facebook Page)
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