New Pearson research shows Generative AI will have a greater impact on white-collar jobs than blue-collar jobs in the next 10 years

The latest installment of Pearson’s Skills Outlook series looks at ‘Gen AI Proof Jobs’ – analyzing the impact of generative AI on more than 5000 jobs in five countries – Australia, Brazil, India, the US, and the UK.

The report suggests that the variation in impact between white-collar and blue-collar roles is attributed to the nature of tasks performed by each role. Many administrative roles contain repetitive tasks – such as scheduling appointments or answering and directing calls – that can be easily replicated by generative AI. The report cites that, in India, around 30% or more of the time spent on tasks involved in the working week of some white-collar roles could be done by generative AI. In comparison, less than 1% of a blue-collar worker’s job in a working week could be done by generative AI.

This trend is especially notable in India, where the report highlights a significant 29% difference in the task-level impact between the most affected white-collar and blue-collar jobs in India. In contrast, the report reveals that the five least impacted blue-collar jobs have no tasks affected, while the least impacted white-collar jobs all have around 10% or more of time spent on tasks affected.

In India, the most impacted jobs are (by % of time spent on tasks that can be automated or augmented by generative AI):

White Collar Jobs

1. Accounting and Book Keeping Clerks- 46%
2. Word Processor and Related Operators- 40%
3. Administrative Secretaries and Related Associate Professionals- 38%
4. Stall and Market Salespersons- 30%
5. Accountants- 28%

Blue Collar Jobs

1. Weavers, Knitters and Related Workers- 17%
2. Basketry Weavers, Brush Makers and Related Workers- 17%
3. Weaving and Knitting Machine Operators- 16%
4. Waiters and Bartenders- 15%
5. Bakers, Pastry Cooks and Confectionery Makers- 15%

Mike Howells, President, Pearson Workforce Skills, said: “As employees look to the future, understanding which jobs are at risk from AI allows them to prepare. They should also consider where new roles might be created by Gen AI. Workers and employers should look at how they can ride this wave of change by using the best of AI and the best of human skills together – whether that is using the technology to take over repetitive tasks, so people can focus on high-value activities, or enhancing those uniquely human skills like creativity, communication and leadership.”

 The least impacted jobs in India (by % of time spent on tasks that can be automated or augmented by generative AI) are:

White Collar Jobs

1. Working Proprietors, Directors and Executives in Transport and Communication-10%
2. Working Proprietors and Directors, Lodging and Catering Services-10%
3. Sales and Marketing Managers-10%
4. Working Proprietors and Directors, Manufacturing, Wholesale & Retail-10%
5. Lawyer-10%

Blue Collar Jobs

1. Bricklayer and Stone Masons-0%
2. Construction & Maintenance Labourers, Roads, Dams and Similar Constructions-0%
3. Hand Launderers and Pressers-0%
4. Sewers, Embroiderers and Related Workers-0%
5. Varnishers and Related Painters-0%

For this Skills Outlook research report, Pearson used tools based on generative AI to analyze the specific tasks related to more than 5,000 jobs and how much time is currently spent on each. Then calculated how much of a job’s work, by time spent on individual tasks, would be affected by generative AI. This gives the percentage of time saved due to Generative AI by 2032, per task – and, so, which jobs will be most or least impacted.   With nearly 1,400 enterprise clients, Pearson has a strong foundation and unique expertise in the workforce skilling market.