TLDR: Despite substantial investments and a vast potential for Artificial Intelligence (AI) to revolutionize India’s economy, the nation is grappling with a ‘hidden productivity gap.’ Reports indicate that while AI could significantly boost productivity and transform millions of jobs by 2030, enterprise adoption rates remain low, and a severe shortage of skilled talent hinders the realization of AI’s full potential. Challenges in measuring ROI, addressing data privacy, and algorithmic bias are key factors contributing to this disparity.
India stands at a pivotal moment in the global Artificial Intelligence (AI) era, marked by both immense promise and a perplexing ‘hidden productivity gap.’ Despite significant capital outlays and a burgeoning ecosystem of innovation, the tangible outcomes in terms of widespread productivity enhancement across various sectors appear limited, according to recent analyses.
The EY India report, ‘The AIdea of India: 2025,’ highlights that Generative AI (GenAI) is poised to revolutionize India’s workforce, with the potential to transform 38 million jobs by 2030. This could drive a 2.61% productivity boost in the organized sector, with an additional 2.82% possible from GenAI adoption in the unorganized sector through basic task automation in areas like logistics, informal retail, and agri-processing. The report also notes that 24% of tasks across industries could be fully automated, and another 42% can be enhanced by AI, potentially freeing up 8-10 hours per week for knowledge workers.
However, this optimistic outlook is tempered by current realities. The EY survey, which engaged over 125 C-suite participants, reveals that enterprise adoption rates of GenAI remain notably low. Only 36% of Indian enterprises have allocated budgets and begun investing in GenAI, with another 24% testing its potential. Crucially, a mere 15% have GenAI workloads in production, and only 8% are able to fully measure and allocate AI costs. This inability to demonstrate clear Return on Investment (ROI) is a significant barrier to broader adoption.
Talent shortage emerges as a critical impediment. A staggering 97% of executives cite a lack of in-house talent and resources as a primary hurdle to maximizing AI’s benefits. This skills gap underscores the need for robust talent development and upskilling initiatives.
Rajiv Memani, Chairman and CEO, EY India, emphasized, “GenAI is transforming India’s economic landscape by unlocking unprecedented opportunities across sectors. This revolution will fundamentally reshape jobs, driving productivity and innovation. Building talent pipelines and prioritizing upskilling must be at the forefront of every organisation. By fostering public-private collaborations and investing in talent development, India can also become a global hub for AI skilled talent.”
While India is recognized for its strong foundation in AI usage and service provision, particularly with its vast population serving as the world’s largest user base and significant contributions to AI research and data, there’s a recognized need to shift from merely consuming AI to creating core technologies. Investment in AI infrastructure is comparatively lower than global leaders, with the India AI mission’s proposed 1.3 billion USD being a fraction of what leading AI companies spend.
The impact on the workforce is a growing concern. Investment bank Jefferies predicted in September that India’s call centers could face a 50% revenue hit, and other back-office functions around 35%, from AI adoption over the next five years, potentially leading to near-term job losses. Sumita Dawra, a former labor ministry secretary, suggested that while AI offers productivity gains and new job creation, India might need to consider stronger social security measures, such as unemployment benefits, to assist those displaced during this transition.
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Despite these challenges, experts believe the game is still wide open for India. Opportunities lie in leveraging its market, data, and talent to build new AI solutions and transition from being a ‘back office’ to the world’s ‘AI factory’ by capitalizing on demand for AI engineers and automation deployment. The government is also taking initiatives to develop foundational models, indicating a concerted strategy to address the existing gaps and accelerate meaningful AI adoption.
