
Generative AI (GenAI) is expected to significantly impact India’s workforce and economy by 2030, according to a new EY India report. The report suggests that AI could transform 38 million jobs, boosting the country’s productivity by 2.61% in the organized sector, with an additional 2.82% potential gain in the unorganised sector.
It highlights that 24% of tasks across industries can be fully automated, while another 42% can be enhanced using AI, freeing up 8-10 hours per week for knowledge workers. The services sector is expected to see the largest productivity gains, while manufacturing and construction will have a smaller impact. The report also looks at AI talent and adoption across businesses. A survey of over 125 top executives found that a lack of skilled talent remains a major barrier to AI adoption. Only 3% of Indian businesses have enough in-house expertise to make the most of AI, while the other 97% struggle with talent shortages.
From trial to full use
Despite its potential, AI adoption in India is still in its early stages. Just 15% of companies have GenAI in production, while 34% have completed proof of concepts (POCs), and 11% are working on scaling successful POCs. However, 8% of companies that tried GenAI have struggled to see real results. Additionally, 36% of businesses have not yet begun experimenting with AI. Data readiness is another challenge. Only 3% of businesses are fully prepared for AI, and 23% are not ready at all.
Gen AI’s impact on productivity
EY’s analysis of over 10,000 tasks across industries shows significant productivity gains. Call centre management is expected to see an 80% boost, while software development could see a 61% increase. Other areas with large gains include content creation (45%), customer service (44%), and sales and marketing (41%).
The IT/ITeS sector could see a 19% productivity boost, followed by healthcare at 13%, and banking/insurance at 8-9%. The automotive and pharmaceutical sectors are likely to see a smaller 2% increase due to their limited labor contribution.
The report also created a ‘productivity uplift’ indicator, analysing tasks based on their potential to be automated, augmented with AI, or enhanced. OI and AI Cost Reductions Measuring Return on Investment (ROI) is critical for businesses considering GenAI. The survey found that many companies struggle to fully measure and allocate AI-related costs. Of the 15% of companies with GenAI in production, only 8% can accurately measure AI costs. This points to the need for clearer frameworks to predict and assess AI’s impact before it becomes more widespread.
On a positive note, the cost of AI has dropped significantly, thanks to the rise of open-source tools and specialized small language models. Foundational model API prices have fallen by 80% in the past two years, making AI more affordable, especially for small and medium enterprises. With deployment costs as low as `120 per hour, AI is becoming increasingly accessible.