AI Capable of Automating 46% of Accountants’ and Bookkeepers’ Tasks, Posing Job Threat in India

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As generative AI becomes increasingly integrated into the global economy, concerns regarding its potential to replace human jobs have amplified. While AI undoubtedly optimizes tasks and boosts productivity, it also disrupts traditional job roles, leading to uncertainties about the future of employment. Occupations reliant on data analysis, like basic financial evaluation or specific research areas, face a higher likelihood of automation due to AI’s ability to process and interpret data far more rapidly than humans.

A recent report from Pearson, a British multinational publishing and education company, highlights the growing risk of generative AI impacting white-collar jobs more than blue-collar ones as this technology further embeds itself in the global workforce. Focused on over 5,000 jobs across Australia, Brazil, India, the UK, and the US, Pearson’s study assessed the potential impact of generative AI on ‘Gen AI Proof Jobs.’

The report indicates that white-collar roles, often involving repetitive tasks, are more susceptible to automation by AI. In India, for example, over 30% of tasks in specific white-collar positions could be automated, while less than 1% of tasks in blue-collar roles involving physical labor are at risk.

Interestingly, the study notes that none of the tasks in the least impacted blue-collar jobs are prone to automation. However, even the least affected white-collar positions still have approximately 10% of their tasks that could be automated.

To illustrate, here are examples of jobs and the percentage of their tasks that could potentially be automated:

White-collar jobs at risk:

  1. Accounting and Bookkeeping 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%

Meanwhile, here are blue-collar jobs in India susceptible to AI takeover:

  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 of Pearson Workforce Skills, emphasizes a collaborative approach leveraging both human and machine capabilities. He encourages professionals to adopt AI for automating repetitive tasks and focus on areas demanding distinctly human skills such as creativity, communication, and leadership. Howells suggests that this strategic amalgamation of technology and human expertise will not only enhance productivity but also elevate the value of human contributions.

“Workers and employers should explore ways to harness both AI and human skills for mutual benefit,” says Howells, advocating for an approach that combines the strengths of both.

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