India’s AI and ML Talent Market (2025–2026)

This second blog in the series examines the macroeconomic and labor-market forces shaping the AI and ML talent ecosystem in India. While the broader technology market is stabilizing, AI-related roles continue to experience unprecedented volatility, aggressive poaching, and compensation inflation.

When technology grows, talent doesn’t just adapt it accelerates.

While the broader tech market is stabilizing, the AI talent economy is operating in fast-forward

Two Contradictory Market Realities

The Indian labor market is showing signs of normalization. Attrition is falling. Salary increases across sectors are predictable. Hiring patterns are stabilizing after three years of volatility. Yet, beneath this stability lies a sharply different reality for AI and ML talent. These roles operate in a market defined by scarcity, speed, and intense competition, creating salary and attrition patterns that diverge sharply from the rest of the industry.

These roles are governed by scarcity, not surplus and by competition, not caution.

National and Sectoral Salary Projections

Salary projections for 2026 highlight the contrast between general market growth and AI-specific inflation.

Key findings include:

1. India’s overall salary projection for 2026 is 9 percent.

2. Technology Product and Platform companies are projected to grow at 9.4 percent.

3. Technology Consulting and Services will see the lowest increase at 6.8 percent.

Product-first organizations are quietly pulling ahead by building proprietary IP and rewarding AI talent accordingly.

Product and platform organizations, which rely heavily on proprietary intellectual property, continue to attract and retain top AI and ML talent with better compensation growth. In comparison, IT services firms face shrinking margins and limited capability to match AI salary inflation.

IT services firms face shrinking margins and limited capability to match AI salary inflation.

Attrition Dynamics: The AI Talent War

India’s total attrition rate reduced to 17.1 percent in 2025 from 18.7 percent in 2023. The overall tech labor market appears calmer. But this trend does not apply to the AI sector.

AI and ML roles face:

1. Significantly higher attrition compared to the national average.

2. Attrition rates between 15 and 20 percent in GCCs, often higher in specialized AI teams.

3. Heavy poaching within GCCs, where nearly 60 percent of hiring comes from rival centers.

This is not hiring, it’s redistribution. Companies are swapping the same scarce talent at rising prices

This aggressive hiring pattern has become one of the primary drivers of AI salary spikes. Lateral movement in AI is far more frequent compared to traditional engineering roles, as companies seek immediate availability of experienced specialists.

Lateral movement in AI is far more frequent compared to traditional engineering roles

AI as a Retention Driver

A new and surprising trend has emerged in India’s workforce: employees increasingly rely on AI tools to support decision-making and workflow efficiency.

Studies indicate that:

1. Over 70 percent of professionals in India now use AI tools for problem solving, idea testing, and task automation.

2. Younger professionals, often referred to as skill nomads, prefer opportunities that provide AI-enabled workflows and continuous learning

Employees no longer ask, ‘Do you use AI?’ They ask, ‘How deeply is AI embedded in your workflows?

This shift has major implications for retention. Employees expect employers to offer access to advanced tools, experimentation environments, and cutting-edge AI platforms.Companies that restrict access to advanced AI tools, experimentation environments, or modern platforms risk losing talent even if they pay competitively.

Reward Disparity and Strategic Talent Differentiation

As competition intensifies for AI talent, organizations are increasingly adopting differentiated reward strategies that prioritize skills and measurable impact.

Key patterns include:

1. Top performers receive 1.5 to 1.8 times higher payouts than average performers.

2. Compensation models are shifting from pay for role to pay for skills and impact.

3. Companies are redesigning performance systems to justify high reward disparities while maintaining internal equity.

In AI, the difference between an average engineer and a high-impact specialist is not incremental it’s exponential

This shift is particularly strong in AI and ML teams, where the gap between an average engineer and a high-impact specialist is significant. Organizations are willing to pay substantial premiums for individuals who can design, scale, and deploy AI systems that deliver measurable business value.

Organizations are increasingly willing to pay steep premiums for individuals who can architect, deploy, and scale AI solutions that directly move revenue, efficiency, and market advantage.

The Road Ahead for India’s AI Labor Market

The AI and ML job landscape in India continues to evolve faster than any other technology segment. While the broader tech industry stabilizes, AI compensation remains volatile and aggressively competitive.

For employers, success in 2025 and 2026 will depend on:

1. Ability to predict salary inflation in niche roles.

2. Willingness to differentiate compensation for high-impact talent.

3. Capability to offer advanced AI tools and learning opportunities as core retention levers.

4. Strong strategies to navigate intra-GCC poaching and attrition.

The next phase of competition will not be about who pays more but who builds the strongest AI ecosystem for talent to thrive

The next blog explores the most requested topic in this series, a detailed breakdown of AI and ML salaries by experience level across India.