How Generative AI could help Indian workers save 51 million hours a week

New research from Pearson, the world’s leading learning company, shows the massive potential of Generative AI to boost workplace productivity by helping Indian workers to save 51 million hours a week on the routine and repetitive tasks that often fill their day and lead to burnout. 

The latest instalment of Pearson’s Skills Outlook series, ‘Reclaim the Clock: How Generative AI Can Power People at Work’ – looks ahead to 2026 and identifies the top 10 job tasks with the most time saved by using the technology, in five countries (Australia, Brazil, India, UK and US).

Pearson’s workforce planning platform, powered by generative AI, finds that the work Gen AI can most effectively support is focused on tasks related to maintaining records, data collection, or researching and compiling information for others.

According to this research the ten work tasks with the most hours saved by Gen AI by 2026 in India are: 

1. Promote products, services, or programs (4,386,799 hours)
2. Collect data about consumer needs or opinions (3,874,794 hours)
3. Develop marketing or promotional materials (3,513,913 hours)
4. Identify business or organizational opportunities (3,219,578 hours)
5. Explain technical details of products or services (3,095,700 hours)
6. Maintain current knowledge in area of expertise (2,625,409 hours)
7. Maintain operational records (2,602,099 hours)
8. Communicate with others about operational plans or activities (1,798,296 hours)
9. Examine materials or documentation for accuracy or compliance (1,575,060 hours) 
10. Evaluate the quality or accuracy of data (1,568,961 hours)

The same sudy found that in Australia, workers could reclaim nearly 6 million hours a week on routine tasks like presenting research, record keeping and data collection by using generative AI to help them on the job.

Similarly the ten work tasks, according to this research, with the most hours saved by Gen AI by 2026 in Australia are:

1. Develop educational programs, plans, or procedures (233,000 hours)
2. Maintain health or medical records (222,000 hours)
3. Maintain current knowledge in area of expertise (184,000 hours)
4. Maintain operational records (170,000 hours)
5. Present research or technical information (166,000 hours)
6. Monitor individual behaviour or performance (156,000 hours)
7. Develop safety standards, policies, or procedures (150,000 hours)
8. Teach academic or vocational subjects (150,000 hours)
9. Explain regulations, policies, or procedures (138,000 hours)
10. Advise others on products or services (132,000 hours)

By augmenting basic tasks with generative AI, companies and their workers can reallocate time to focus on the high-value work that humans do best: strategic thinking, collaboration, caring for others, decision-making, innovation, problem-solving, empathy, and leadership. 

At an individual level, even small amounts of time saved with Generative AI can help people feel more in control of their job and achieve a better work-life balance. 

Oliver Latham, VP of Strategy and Growth for Pearson Workforce Skills, said: “In nearly every workplace, people spend their day on common, time-consuming tasks that eat away at productivity or their work-life balance. If those tasks could be augmented with generative AI, employers and their workers could reallocate time to the things that need a more human touch and mean more to their customers.”

“Employers should consider how to incorporate this new technology into their teams and redesign roles to free people up to focus on more valuable, human tasks.  They should also consider the need for training and support for employees, so they can use it effectively and responsibly,” he added.

Pearson believe that the future of work can be one where people and Gen AI can collaborate by using AI as a tool to enhance human potential. For this study, they used census and other workforce datasets to create a single view of the current workforce in the US, UK, Australia, India and Brazil. Using Pearson’s proprietary occupations ontology of 5,600 jobs and 76,000 tasks, each job can be viewed as a collection of tasks. This allows their machine learning algorithms to calculate future technology impact at a task level.

Pearson looked at hours currently spent, countrywide, on work tasks each week, and then calculated what this would be in three years’ time as Gen AI technology is adopted into the workplace.  They then identified the tasks which would have the greatest hours reduced by the technology (specifically LLM Chatbots and AI Text-to-Visual Media Generators).

Pearson is the world’s leading learning company, serving customers in nearly 200 countries with digital content, assessments, qualifications, and data.

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