GCCs offer a median salary of ₹18.4 LPA, maintaining a clear lead over non-GCC employers.
Finding 1 of 5
PeMa Quadrant · 1st edition · Published March 23, 2026
35 vendors evaluated on market penetration and technology maturity. 17 qualify as Leaders.
35
Vendors evaluated
17
Leaders
First edition of this PeMa Quadrant.
17 Leaders · 9 Seasoned · 9 Challengers

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Market penetration →
Positions from 2025 are read from the chart AIM published that year. Source →
What the report finds
GCCs offer a median salary of ₹18.4 LPA, maintaining a clear lead over non-GCC employers.
Finding 1 of 5
The most significant salary jump occurs in the 6 to 10 year range, where compensation more than doubles.
BFSI records the highest median salary at ₹30.1 LPA, significantly ahead of Industrial and Manufacturing.
AI ML roles outpace cybersecurity roles across sectors, driven by increasing adoption of generative AI capabilities.
Emerging cities offer 40 to 49 percent lower salaries, making them attractive hubs for cost-efficient GCC expansion.
Vendors evaluated
| Vendor | Placement | Headquarters | Vendor passport |
|---|---|---|---|
| Accenture | Leaders | — | Passport → |
| ANSR | Leaders | — | Passport → |
| Capgemini | Leaders | — | Passport → |
| CGI | Leaders | — | Passport → |
| Cognizant | Leaders | — | — |
| Deloitte | Leaders | — | Passport → |
| EY | Leaders | — | Passport → |
| HCL Technologies (HCLTech) | Leaders | — | Passport → |
| Hexaware | Leaders | — | Passport → |
| IBM | Leaders | — | Passport → |
| Infosys | Leaders | — | Passport → |
| KPMG India | Leaders | — | Passport → |
| PwC India | Leaders | — | Passport → |
| Tech Mahindra | Leaders | — | Passport → |
| Vestian | Leaders | — | Passport → |
| Wipro | Leaders | — | Passport → |
| Zinnov | Leaders | — | — |
| Fidel Softech | Seasoned | — | — |
| MindPool Tech. | Seasoned | — | — |
| Nexdigm | Seasoned | — | — |
| NLB Services | Seasoned | — | — |
| Opteamix | Seasoned | — | — |
| SRKay Consulting | Seasoned | — | — |
| Systems Plus | Seasoned | — | — |
| Torry Harris | Seasoned | — | — |
| Yash Technologies | Seasoned | — | — |
| Ace Software | Challengers | — | — |
| Astravise Services | Challengers | — | — |
| BridgePath Innovations | Challengers | — | — |
| Cushman & Wakefield | Challengers | — | — |
| JSS Pro | Challengers | — | — |
| SA Technologies | Challengers | — | — |
| SansoviGCC by GoodWorks | Challengers | — | — |
| TekWissen | Challengers | — | — |
| TrueFirms | Challengers | — | — |
Showing 10 of 35 ·
Abstract
The report on Global Capability Centers (GCCs) Salary Trends in India 2026 provides a comprehensive analysis of salary benchmarks within India's GCCs, highlighting compensation trends, regional variations, and high-paying roles.
It reveals that GCCs are increasingly becoming innovation hubs, commanding a premium over non-GCC employers. Experience is a significant driver of compensation, with mid-career roles seeing notable salary inflections. Sector dynamics also influence pay, with industries like BFSI and Software & Product Development offering higher compensation due to the complexity and strategic nature of work. Geographic location further affects pay, with leading metros offering higher salaries compared to emerging hubs. Role specialization, particularly in advanced technology roles, attracts a premium, while educational qualifications also impact compensation outcomes. The report's findings are based on data collected from various salary platforms, ensuring a broad and diverse sample reflective of the current compensation landscape. It serves as a directional guide for GCC leaders and talent strategists, providing insights into evolving compensation structures within India's GCC ecosystem.
Methodology
The research was conducted using salary data gathered from reputable platforms focused on the Indian job market.
X axis
Y axis
The research was conducted using salary data gathered from reputable platforms focused on the Indian job market. The sample includes data across roles, experience levels, sectors, and locations within GCC India. Data was cleaned to remove outliers and inconsistencies, and advanced statistical methods were applied to derive insights. Findings were cross-validated with multiple data sources and benchmarked against public compensation studies to ensure accuracy.
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