India’s GCCs Build AI and Cloud Teams Around Experienced Technology Talent

India’s GCCs Build AI and Cloud Teams Around Experienced Technology Talent

India’s Global Capability Centres are changing the way they build technology teams as artificial intelligence, cloud computing and product engineering become increasingly central to global corporate operations.

Rather than relying primarily on large-volume hiring, many GCCs are moving toward smaller and more specialised engineering teams staffed by experienced professionals capable of owning complex AI systems, cloud platforms, enterprise architecture and product development.

India is expected to host more than 2,100 GCCs employing approximately 2.36 million people and generating close to $100 billion in revenue by the end of FY26, underscoring the scale of the sector. But the underlying hiring model is becoming increasingly selective. (Reuters)

The shift represents an important evolution in India’s technology economy: global companies are no longer using GCCs primarily to access large pools of lower-cost technology workers. They are increasingly building teams in India to take ownership of sophisticated global technology platforms.

GCCs Shift From Scale Toward Specialisation

For much of the past two decades, the GCC expansion model was strongly associated with headcount growth.

Large multinational companies established centres in India and gradually moved technology, finance, operations and support functions into them.

That model is evolving.

Recent industry analysis shows companies placing greater emphasis on engineering quality, specialised skills and strategic ownership rather than sheer team size. (The Times of India)

A 500-person general technology team may increasingly be replaced by a much smaller group of specialists working on strategically important platforms.

AI Is Driving the Talent Shift

Artificial intelligence is one of the strongest reasons for this change.

AI systems require employees with expertise across areas such as:

• Machine learning

• Data engineering

• MLOps

• LLMOps

• AI architecture

• Model governance

• Enterprise integration

These are not always roles that can be filled through large-scale entry-level recruitment.

Companies increasingly need professionals who have already operated complex systems in production.

That puts greater value on experienced engineering talent.

Nearly Two-Thirds of New GCC Hiring Is Linked to AI Skills

AI skills have become disproportionately important within GCC recruitment.

Recent hiring data indicated that nearly two-thirds of new GCC hiring in India involved AI-related capabilities, even while the broader white-collar employment market remained relatively subdued. (The Economic Times)

This does not mean every new employee is an AI scientist.

AI increasingly affects adjacent functions including:

• Data platforms

• Cloud engineering

• Software development

• Cybersecurity

• Automation

• Product engineering

The result is a broader technology workforce increasingly organised around AI-enabled systems.

India Already Has More Than 250,000 GCC AI Professionals

India has developed substantial depth in AI talent within the GCC ecosystem.

Zinnov estimates that Indian GCCs employ more than 250,000 AI and machine-learning professionals, representing nearly 28% of global GCC AI talent. (Zinnov)

More than 1,200 Indian GCCs now operate AI or machine-learning capabilities, while more than 250 have established dedicated AI/ML Centres of Excellence. (Zinnov)

That installed talent base is one reason multinational companies increasingly assign larger AI mandates to Indian centres.

Experienced Talent Becomes More Valuable

The shift toward AI changes the economics of hiring.

A junior developer may be capable of performing clearly defined tasks with supervision.

An experienced AI-platform engineer may be responsible for decisions involving:

• Model deployment

• Production reliability

• Data security

• Cloud infrastructure

• Governance

• Cost optimisation

Mistakes at this level can affect entire enterprise systems.

Companies are therefore increasingly willing to pay a premium for professionals with proven experience.

AI/ML Salary Growth Reflects Scarcity

Talent scarcity is already visible in compensation.

Zinnov data indicates that while average salary increases across GCCs are around 9.8%, AI and machine-learning roles are receiving increases of approximately 21.1%. (Zinnov)

That difference illustrates how the labour market is becoming segmented.

Companies are not simply competing for technology workers.

They are competing intensely for specific high-value capabilities.

Cloud Engineering Remains Foundational

Artificial intelligence cannot scale inside large enterprises without cloud infrastructure.

AI systems need access to:

• Computing

• Storage

• Databases

• Networking

• Security

• Deployment platforms

This means cloud expertise remains closely linked to AI expansion.

EY notes that India’s large pool of cloud-ready and AI-skilled professionals allows global cloud programmes to be architected and operated from India rather than merely supported from the country. (EY)

GCCs Are Taking Ownership of Global Platforms

The most important change is not simply the technologies being used.

It is the level of responsibility assigned to Indian centres.

GCCs increasingly own:

• Global applications

• Cloud platforms

• AI systems

• Product engineering

• Data architecture

• Enterprise automation

This is a major departure from earlier operating models in which core technology decisions frequently remained with global headquarters.

Indian teams are moving closer to the centre of enterprise technology strategy. (Express Computer)

Product Engineering Is Growing in Importance

Product development provides another example.

Historically, some multinational centres in India primarily maintained or supported software developed elsewhere.

Increasingly, GCC teams are responsible for:

Design → Build → Test → Deploy → Operate

That represents full product ownership.

The shift requires experienced engineers capable of making architecture and product decisions rather than simply following centrally defined specifications.

Smaller Teams Can Produce More Output With AI

Generative AI is also changing the productivity of technology workers themselves.

Developers can increasingly use AI tools for:

• Code generation

• Testing

• Documentation

• Debugging

• Research

As individual productivity increases, companies may not need the same number of people to complete certain technology projects.

The result could be:

Fewer employees + Greater expertise + More AI tools = Higher output per engineer

This helps explain why some GCCs are becoming smaller even while their strategic importance increases.

Headcount Is No Longer the Main Measure of Success

This change creates a different way of evaluating GCC growth.

Previously, a company might highlight that its India centre had grown from 5,000 employees to 10,000.

Increasingly, the more meaningful question is:

What does the India centre actually own?

A smaller team responsible for a company’s global AI platform could be strategically more important than a much larger team performing routine back-office work.

GCC Hiring Volumes Have Moderated

The shift toward quality is visible in hiring volumes.

Zinnov estimates that GCC hiring volumes declined nearly 28% between the first and second halves of FY26, even as demand for specialised AI skills remained strong. (Zinnov)

That apparent contradiction is important.

Lower overall hiring does not necessarily mean weaker GCC investment.

It can mean companies are recruiting fewer people while increasing the complexity and value of the work performed.

Automation Is Reducing Routine Work

Artificial intelligence is also automating some functions traditionally performed within technology centres.

Tasks involving:

• Basic coding

• Testing

• Support

• Documentation

• Reporting

can increasingly be partially automated.

That reduces demand for some entry-level or repetitive roles.

At the same time, it creates more demand for people who can build and manage the automation itself.

Entry-Level Technology Hiring Could Face Pressure

This creates a significant challenge for India’s traditional IT employment model.

For decades, the technology industry absorbed large numbers of engineering graduates.

AI could weaken that model if companies require smaller numbers of more capable employees.

The broader Indian IT sector is already facing pressure as automation reduces demand for routine work while AI integration and product engineering become more important. (Financial Times)

Experienced Engineers Gain Bargaining Power

Professionals with production experience in scarce technologies can benefit from the shift.

Companies increasingly need people capable of handling:

• Enterprise AI deployment

• Cloud migration

• Cybersecurity

• Data governance

• Platform engineering

Those professionals can become difficult to replace.

This strengthens their bargaining power around compensation and career opportunities.

Retaining High Performers Becomes a Major Challenge

The competition is not limited to hiring.

Retention is increasingly important.

Zinnov estimates overall GCC attrition at approximately 16%, while high-performer attrition is around 16.5%. (Zinnov)

Losing a highly specialised architect or AI engineer can be particularly disruptive because the employee may possess deep knowledge of company systems.

GCCs Are Differentiating Compensation

Companies are therefore becoming more selective in how they reward employees.

Instead of giving relatively uniform salary increases, GCCs increasingly provide higher compensation to employees in scarce roles or with stronger performance.

Zinnov reports that more than 85% of GCCs have moved toward differentiated compensation structures. (Zinnov)

This reinforces the transition from volume employment toward specialised talent markets.

AI Adoption Is Already Widespread Across GCCs

The talent strategy reflects a broader shift in corporate AI adoption.

EY’s GCC survey found that 58% of Indian GCCs were already investing in agentic AI, while another 29% planned to scale investments. Around 83% were investing in generative AI. (EY)

This means AI is moving beyond isolated pilot programmes.

It is increasingly becoming part of the operating model of multinational companies.

Agentic AI Requires Stronger Technical Teams

Agentic AI increases the complexity of enterprise deployments.

Traditional AI tools might generate recommendations.

AI agents can potentially:

• Access systems

• Make decisions

• Execute workflows

• Update records

That increases requirements around:

• Security

• Governance

• Reliability

• Monitoring

Experienced technology professionals become essential when AI systems begin operating directly inside enterprise workflows.

Cloud Skills Become More Strategic as AI Scales

AI workloads can consume substantial computing resources.

Enterprises therefore need engineers capable of managing:

• Cloud architecture

• Compute utilisation

• Storage

• Networking

• FinOps

AI and cloud skills increasingly overlap.

A strong AI engineer without understanding infrastructure costs can produce systems that are technically impressive but economically inefficient.

FinOps Skills Could Gain Importance

Cloud spending has become a significant cost item for many multinational companies.

AI can increase that spending further.

Teams therefore need employees capable of optimising:

Performance + Reliability + Compute Cost

This creates opportunities for cloud-financial-management skills alongside conventional engineering.

Cybersecurity Is Another Critical Capability

As more enterprise workloads move into cloud and AI systems, cybersecurity becomes increasingly important.

AI agents can access sensitive corporate data and applications.

Companies therefore need specialists in:

• Identity management

• Cloud security

• Model security

• Data protection

• Threat detection

This further increases demand for experienced rather than purely entry-level technology workers.

GCCs Are Becoming AI-Native Enterprises

EY describes Indian GCCs as increasingly moving toward AI-native operating models, where AI is embedded across business processes rather than treated as a separate technology project. (EY)

This matters because it changes hiring across entire organisations.

Finance employees may need AI literacy.

Product managers may need to work with models.

Engineers may need to understand agent architectures.

AI capability gradually becomes a baseline business skill.

India’s Talent Density Remains a Major Advantage

India's position remains strong because it combines a large technology workforce with established clusters in:

• Bengaluru

• Hyderabad

• Pune

• Chennai

• Delhi-NCR

• Mumbai

These cities contain dense networks of technology companies, universities, startups and experienced engineers.

Talent density matters because companies need not just individual specialists but entire teams capable of working together across multiple disciplines.

Bengaluru Remains Central but Competition Is Expanding

Bengaluru remains one of the most important locations for advanced technology GCCs.

However, other cities are increasingly competing for investment.

Hyderabad continues attracting new engineering centres, including recent GCC openings focused on product development. (Express Computer)

Pune, Chennai and Delhi-NCR also remain important technology markets.

Tier-II Cities Could Gain Selective Opportunities

Smaller cities may benefit from the next phase of GCC expansion, particularly where companies are seeking lower operating costs or access to new talent pools.

However, highly specialised AI and cloud roles tend to concentrate where mature technology ecosystems already exist.

This means Tier-II expansion may be uneven.

Locations with strong universities, infrastructure and existing technology employers will have an advantage.

States Are Competing Aggressively for GCC Investment

State governments increasingly view GCCs as important drivers of high-value employment.

Several states have introduced dedicated GCC policies and incentives.

CBRE estimates state-level initiatives could support more than 1,300 new GCCs and over 1.1 million jobs by 2031. (The Economic Times)

Competition is therefore expanding beyond companies competing for employees.

States are also competing for the centres themselves.

Large Enterprises Want Strategic Ownership in India

The shift toward experienced talent reflects a deeper change in corporate confidence.

Companies are increasingly willing to place global responsibilities inside their Indian GCCs.

These can include:

• Product ownership

• AI governance

• Platform architecture

• Data strategy

Such mandates require strong leadership teams.

A GCC cannot become strategically important through junior technical talent alone.

Leadership Talent Becomes Scarcer

As GCCs become more important, they need senior professionals capable of leading global teams.

These leaders need expertise in both technology and business.

They may be responsible for:

• Global stakeholders

• Budgets

• Technology strategy

• Talent

• Governance

Competition for such executives can become particularly intense because the available pool is much smaller than the overall technology workforce.

Reskilling Existing Employees Becomes Necessary

Hiring cannot solve every skill shortage.

Companies are therefore investing in reskilling.

An experienced software engineer already understands the company’s systems and business context.

Teaching that employee AI or cloud capabilities can sometimes be more effective than hiring externally.

This can reduce recruitment pressure while preserving institutional knowledge.

Universities Will Need to Adapt

The shift has implications for engineering education.

Employers increasingly want graduates who understand:

• Cloud platforms

• AI tools

• Data systems

• Software engineering

• Cybersecurity

Universities may need to update curricula more quickly as technology changes.

Traditional programming knowledge remains useful, but employers increasingly value the ability to work with AI-enabled development environments.

Fresh Graduates Still Have a Role

The shift toward experienced hiring does not mean entry-level recruitment disappears.

Companies still need future talent pipelines.

However, graduates may need to demonstrate stronger practical capabilities earlier.

Internships, project portfolios and cloud certifications can become more important when employers reduce large-scale campus hiring.

AI Could Create New Career Paths

New specialised roles are emerging across areas such as:

• AI governance

• Model evaluation

• Prompt and agent engineering

• AI security

• LLMOps

Some of these functions barely existed several years ago.

The technology labour market can therefore simultaneously eliminate older roles and create new ones.

Global Companies Can Use India for 24-Hour Development

India also provides a geographic advantage for multinational technology organisations.

Teams operating across India, Europe and North America can work through overlapping global schedules.

Complex software development can continue across time zones.

When combined with experienced technical teams, this can increase development speed.

Cost Still Matters, but It Is No Longer the Main Argument

India remains less expensive than several major Western technology markets for comparable technical roles.

That still influences investment.

But industry consultants increasingly describe access to specialised talent as more important than simple labour-cost arbitrage. (Zinnov)

The shift can be summarised as:

Old GCC logic: Lower cost.

New GCC logic: Access to capability.

AI Could Make India’s Talent Advantage More Valuable

AI automation may appear to reduce the need for large technology workforces.

Paradoxically, it could increase the strategic value of India's strongest engineers.

If every multinational needs smaller numbers of highly specialised AI and cloud professionals, markets with deep technical ecosystems become even more important.

India’s challenge is ensuring the quality of specialist talent grows fast enough to meet demand.

Talent Shortages Could Slow GCC Expansion

A shortage of experienced engineers could become one of the principal constraints on the sector.

Companies can build offices quickly.

Developing senior AI architects takes years.

If demand grows faster than the supply of experienced professionals, businesses may face:

• Longer hiring cycles

• Higher salaries

• Greater attrition

Talent availability could therefore influence where future GCCs are established and how rapidly they scale.

Smaller Teams Can Still Create More Economic Value

The transition also changes how policymakers should evaluate technology employment.

A smaller group of high-skilled professionals earning higher salaries and controlling global products may create substantial economic value.

Growth should therefore not be measured exclusively by absolute employment.

Important indicators increasingly include:

• Salary levels

• Intellectual property

• Product ownership

• Global responsibility

This is a more sophisticated model of technology-sector development.

GCC Growth Could Reshape India’s IT Industry

The rise of global in-house centres also creates competitive pressure for traditional Indian IT-services companies.

Both groups seek similar talent.

GCCs may recruit experienced engineers directly to work on internal global platforms.

IT services firms, meanwhile, need those same professionals to deliver AI and cloud transformation projects for clients.

This can intensify wage competition.

GCCs Could Become Major Innovation Hubs

The long-term trend points toward GCCs taking a larger role in research and innovation.

India is already moving beyond execution work into areas including:

• Product design

• Data science

• AI research

• Platform development

If that trajectory continues, the distinction between a GCC and a global R&D centre could become increasingly blurred.

What Businesses Should Watch

The evolution of India's GCC talent market puts several developments in focus:

• AI hiring intensity

• Cloud engineering demand

• Senior technology salaries

• GCC headcount growth

• Productivity gains from AI

• Talent attrition

• Tier-II GCC expansion

• Product ownership

• Agentic AI deployment

• IT-services competition

The most important indicator may increasingly be the sophistication of work being moved to India rather than simply the number of employees hired.

Outlook

India remains the world's largest GCC ecosystem, but the next stage of growth is likely to look very different from the last one.

The sector has moved from cost-driven expansion toward capability-led investment, with AI, cloud, data and product engineering becoming core priorities. (Reuters)

Companies are increasingly building smaller teams composed of experienced specialists rather than maximising headcount.

At the same time, AI automation is raising employee productivity and reducing demand for some routine technology roles.

The combination could produce fewer jobs per GCC than earlier expansion cycles while increasing the strategic and economic value of those roles.

Conclusion

India's Global Capability Centres are entering a new stage in which technology depth is becoming more important than workforce scale.

With more than 2,100 centres, 2.36 million employees and close to $100 billion in annual revenue, the GCC ecosystem has already become a major part of India's technology economy. (Reuters)

The next phase is being shaped by artificial intelligence and cloud computing.

Companies increasingly need senior engineers, AI specialists, cloud architects and product leaders capable of owning global systems rather than simply executing predefined tasks.

That shift creates significant opportunities for experienced technology professionals but also raises challenges around salary inflation, retention and entry-level hiring.

For India, the long-term opportunity is substantial. If the country can continue deepening its specialist AI, cloud and engineering talent base, its GCC sector could evolve from the world's largest offshore corporate technology network into one of the most important centres of global enterprise innovation.