White-collar jobs are likely to be more affected by generative AI than blue-collar jobs, according to a report released Nov. 27 by Pearson plc, a provider of online training, textbooks and skills assessments.

Approximately 30% of white-collar roles could be done by generative AI, Pearson found. However, less than 1% of blue-collar jobs could be done by generative AI.

Many of the most affected white-collar roles contain repetitive tasks such as scheduling appointments or answering and directing calls. On the other hand, white-collar roles that are likely to be least impacted include those involving tasks related to mathematics, such as engineers.

Many blue-collar roles — such as landscapers, mechanics or construction workers — include manual labor or customer service elements that can’t easily be replicated by generative AI.

Pearson’s report analyzed the impact of generative AI on more than 5,000 jobs in five countries: Australia, Brazil, India, the US and the UK.

Pearson listed both the most and least impacted jobs in the US by percent of hours spent on tasks that can be automated or augmented by generative AI.

White-collar jobs

Most impacted:

1. Medical secretaries, 40%
2. Statement clerks, 38%
3. Billing, cost and rate clerks, 38%
4. Loan interviewers and clerks, 38%
5. Bookkeeping, accounting and auditing clerks, 38%

Least impacted:

1. Chief executives, 10%
2. Civil engineers, 10%
3. Electrical engineers, 11%
4. Sales managers, 13%
5. Architectural and engineering managers, 13%

Blue-collar jobs

Most impacted:

1. Farm products buyers, 27%
2. Amusement and recreation attendants, 26%
3. Restaurant, lounge and coffee shop hosts, 24%
4. Food service managers, 22%
5. Computer-controlled machine tool operators, metal and plastic, 21%

Least impacted:

1. Bus and truck mechanics and diesel engine specialists, 0%
2. Dishwashers, 0%
3. Highway maintenance workers, 0%
4. Laundry and dry-cleaning workers, 0%
5. Solderers and brazers, 0%