A new Nomura report reveals that India is recording 2.6 AI-related hires for every job lost, marking the nation as a global focal point for workforce shifts. However, a deepening skill gap threatens to leave entry-level workers behind as companies prioritize specialized expertise over mass hiring.

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What Happened

India has emerged as the primary focal point for the impact of artificial intelligence on employment, recording a significant surge in AI-related hiring that currently outpaces job displacement. According to a comprehensive analysis by Nomura, the country witnessed 83,100 AI-related hires between 2022 and August 2026, compared to 31,921 job losses directly attributed to the technology. This creates a ratio of approximately 2.6 new hires for every single position eliminated, suggesting a net positive for the labor market in the short term.

This data, accessed by Bloomberg News, identifies India as 'ground zero' for understanding how automation reshapes the workforce. While the sheer volume of new opportunities is substantial, the report highlights a growing friction point: the workers being displaced are largely unable to transition into the newly created roles, creating a persistent skill gap that threatens to bifurcate the labor market.

Key Details

Economists Sonal Varma and Si Ying Toh conducted an extensive review of 69 employment-related cases across Asia to arrive at these findings. Their research underscores that the impact of AI is not uniform across all sectors, nor is it evenly distributed among all skill levels. The technology sector, which has long been the backbone of India’s economic growth, accounts for more than 90% of the AI-related hiring across the region.

As indicated in the table above, the net positive is clear, but the qualitative nature of these jobs tells a different story. The roles being eliminated are frequently rooted in traditional business-process outsourcing (BPO) and customer support functions, where automated chatbots and machine learning algorithms are now handling tasks that previously required human intervention. Conversely, the roles being created are heavily skewed toward high-end engineering, data science, and specialized AI development.

Context

To understand why India is positioned as 'ground zero,' one must look at the country's historical economic trajectory. For decades, India has leveraged its massive pool of educated, English-speaking workers to dominate global software testing, data processing, and customer support services. This model relied on a steady pipeline of entry-level graduates who could be trained quickly and deployed in mass-hiring initiatives.

However, the current wave of AI adoption is rewriting this playbook. Companies are no longer seeking to hire thousands of generalists for post-onboarding training. Instead, the demand has shifted toward professionals who already possess advanced technical skill sets. The traditional 'training ground' model—where entry-level employees gained experience while performing basic tasks—is rapidly evaporating. This creates a structural mismatch: the workforce currently available, often trained for BPO or basic IT support, lacks the advanced degrees and specialized experience required to build, maintain, or optimize the AI systems that are replacing them.

Why It Matters

This transition points toward the emergence of a two-tier labor market in India. On one side, there is a fierce, high-value competition for experienced professionals who can navigate the complexities of AI engineering. On the other, there is a shrinking pool of opportunities for entry-level workers who traditionally relied on the IT services sector for their first career steps.

• The Displaced Worker Dilemma: Customer support representatives and data entry clerks are finding it increasingly difficult to pivot. The skills required for their current roles are becoming obsolete, and the path to retraining for AI engineering is steep, costly, and time-intensive.
• The Corporate Strategy Shift: Businesses are moving away from mass hiring strategies. Efficiency is now prioritized over headcount, and firms are willing to pay premiums for specialized talent rather than investing in the long-term development of entry-level staff.
• The Regional Ripple Effect: As the largest contributor to both hiring and displacement, India’s experience serves as a bellwether for other emerging economies in Asia that rely on similar labor-intensive service models.

This shift challenges the conventional wisdom that economic growth through technology will automatically provide a ladder for the workforce. Without significant interventions in education and vocational training, the gains from AI adoption may be captured by a small, elite segment of the workforce, leaving a large portion of the population vulnerable to long-term structural unemployment.

Bottom Line

While the 2.6:1 hiring ratio provides a statistical basis for optimism, it masks a deeper, more complex human challenge. The net growth in jobs does not equate to a net benefit for all workers. The fundamental disconnect between the skills of the displaced and the requirements of the new economy suggests that India is entering a period of significant labor market volatility. The future of India’s tech-led growth will depend less on the total number of jobs created and more on the ability of the nation to bridge the widening chasm between its existing workforce and the high-tech demands of the future.

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🔗 Original: https://pneumetron.com/news/technology/indias-ai-hiring-paradox-3b4216

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