India’s Enterprise AI Push Now Matching Global Momentum

India’s role in the global artificial intelligence economy is rapidly evolving from being a back-office technology hub to becoming a central engine for enterprise AI deployment, process intelligence, and operational transformation.

What was once largely a market for IT services and outsourced support functions is increasingly becoming a strategic base where multinational corporations build, test, and scale enterprise AI systems. Global Capability Centres (GCCs), Indian enterprises, and mature startups are now collectively driving a new phase of AI consumption, with a greater focus on operational outcomes than on experimentation.

According to Gartner, India’s overall IT spending is expected to reach USD 176.3 billion in 2026, growing 10.6 percent year-on-year, with software spending alone projected to rise 17.6 percent as enterprises accelerate investments in AI-enabled platforms and automation. Meanwhile, Nasscom estimates that India’s technology industry will cross USD 315 billion in revenue during FY26, with AI-led services revenue already estimated at USD 10-12 billion. 

At the center of this shift is enterprise AI consumption, the use of AI not merely as a productivity layer, but as an embedded operational capability across supply chains, finance, customer service, compliance, manufacturing, and business workflows.

For Celonis, which specializes in process intelligence and enterprise operational visibility, India has become one of the company’s most strategic markets globally.

“We often call it the real-time digital twin of this operational context so that both agents and people together can reason correctly, decide in a reliable way, and take the right actions,” said Malhar Kamdar, Chief Growth Officer, Celonis. 

“India has an incredible opportunity to accelerate the adoption of enterprise AI because in many aspects it has the opportunity to leapfrog technology. I see many companies going straight to AI operations. If I compare what’s happening globally across North America and Europe, India has this ability to leverage AI much faster than many other countries,” said Kamdar.

That acceleration is increasingly being powered by India’s GCC ecosystem. According to recent Nasscom and Zinnov data, India now hosts 2,117 GCCs employing more than 2.36 million professionals, with FY26 revenues projected to reach nearly USD 98.4 billion. 

Celonis says it already works with around 260 GCCs operating in India.

“We operate close to around 260 of these GCCs in India which are existing Celonis customers globally and they have a large workforce base here,” said Dilip Khandelwal, Chief Customer Officer, Chairman of Indian Advisory Board, Celonis.

“What is beautiful is that GCCs are evolving from supporting functions to owning those topics and having decision-makers here. A lot of the people who decide operational efficiencies and process ownership now sit in India, and that transformation directly helps us,” said Khandelwal. 

Industry observers say this structural shift is important because enterprise AI requires far deeper integration into operational systems than consumer AI applications. Unlike chatbot deployments or isolated pilots, enterprise AI systems require access to process flows, organizational context, real-time operational data, and governance frameworks.

Kamdar believes this ‘context gap’ remains the biggest bottleneck for enterprise AI globally.

“As strong and powerful as AI technology is, it has blind spots because it does not understand how the business really works. That business context is scattered across systems, departments, and people. The missing piece for AI to deliver on its promise at enterprise scale is that context layer,” said Kamdar.

That challenge is becoming increasingly relevant as companies move from AI experimentation to production-grade deployments. Gartner recently forecast that worldwide AI spending will reach USD 2.52 trillion in 2026, up 44 per cent year-on-year, driven heavily by enterprise infrastructure and AI software investments.

At the same time, India’s enterprise AI rise is also being shaped by its vast engineering talent pool. Celonis says it has partnerships with more than 300 universities in India and has already trained over 100,000 students in process intelligence and AI-related technologies.

Kamdar added, “We believe AI is a force multiplier for talent more than a replacement for talent. The future enterprise will be AI-driven and composable, which means it will be a combination of humans, technology, and agents working together under human supervision.”

The broader market appears to support that thesis. Nasscom estimates India’s tech sector will add a net 135,000 jobs in FY26 despite concerns around AI-led automation. However, companies are also facing mounting pressure to build specialized AI capabilities. A recent Quess report estimated India’s GCC ecosystem faces an AI talent gap of nearly 38-42 per cent. 

For Celonis, India’s opportunity goes beyond selling into enterprises. The company is also betting on India becoming a platform ecosystem for enterprise AI innovation.

Kamdar said, “We have established our innovation hub in India because we want to engage with the ecosystem of customers, partners, enterprises, and startups to co-create. AI economy is a partner economy. We believe in creating a landscape where partners can thrive.”

Khandelwal echoed that view, particularly around India’s startup ecosystem. “Some of the mature startups in India are becoming very large global companies, and they are natural customers for us. At the same time, startups can also use Celonis as a platform to build composable AI applications on top of it. That’s where we will increasingly engage with the Indian startup ecosystem.”

As global enterprises rethink how AI integrates into real-world operations, India’s combination of engineering talent, expanding GCC ecosystems, growing domestic enterprises, and AI-native startups is positioning the country as more than just a technology outsourcing destination.

Instead, India is increasingly becoming one of the places where enterprise AI itself is being operationalized at a global scale.