Global Capability Centers have changed significantly. What began as simple offshore operations focused on saving money has become something far more important. Today’s GCCs work as places where companies build products, make digital changes happen, and create new technology solutions across the world.
India’s experience shows this change clearly. The GCC ecosystem now has 1.9 million workers and makes $64.6 billion in revenue each year as of FY2024. Almost 9 out of 10 centers now run at a mature level, handling worldwide rollouts, rules and regulations, and product work completely.
The shift is intentional and measurable. Companies no longer judge success only by how much money they save. They look at GCC success through new products created, value added to the business, and how quickly they can launch new ideas.
The Evolution of GCCs: Major Trends Reshaping the Landscape
The evolution of GCCs shows a real chance for companies worldwide. By 2030, India’s GCC sector is expected to reach $105 billion, employ 2.8 million people, and run 2,400 to 2,550 centers. This big growth shows how companies are changing the way they organize people and work.
Three main forces push this change.
- First, artificial intelligence is now absolutely necessary.
- Second, companies want GCC teams to own entire products from start to finish.
- Third, modern business models need quick, spread-out teams that can innovate, something that old ways of working cannot do.
The future of global capability centers depends on three shifts. Companies want teams to work faster and smarter. The next generation GCCs will shape how companies compete and grow. Technical leaders must understand these trends to make smart decisions about where to put resources and talent.
AI and Automation
Artificial intelligence is changing GCCs right now, not just in the future. 70% of new GCCs make AI a top priority from day one. This shows a big shift in how centers plan their work and build their teams.
GCCs are adding AI in many ways:
- Smart automation: Moving past simple copy-paste automation to AI that improves workflows, letting teams do more important work.
- Predicting what comes next: Using machine learning to guess business trends, improve supply chains, and make customer experiences better at company scale.
- Building new things with AI: Setting up special groups where teams test new AI tools, write content automatically, and try out hard business ideas.
- AI that helps decisions: Analyzing large amounts of information to give real-time suggestions for business choices.
Over 70% of GCCs put money into AI right now. Most focus on customer experience (69%), business operations (57%), and keeping systems safe (47%). This spending shows AI moved from the side to the center of plans.
The gains are real and measurable. India’s AI workers grew 252% between 2016 and 2024, with 126,600 people now working in AI jobs across GCCs. This big group of skilled people gives companies a real edge when building GCC work in India.
Product Engineering Centers
The evolution of GCCs now focuses heavily on product engineering and having teams own the full picture. GCC teams are moving from doing tasks to owning what products do, how people use them, and how much money they make. This basic change affects how companies win.
Product-focused GCCs bring real benefits:
- Getting products done faster: Teams working together on design, building, and launch shrink release time from months to weeks.
- Making new technology: Centers now build special software, data products, and solutions that help the company make money directly.
- Doing the same thing everywhere: Engineering teams in GCCs can try new solutions in one place and use them all over the world, cutting repeated work.
- Working all day long: Teams in different time zones let work happen 24 hours a day and solve problems quicker.
Engineering GCC operations grow 1.3 times faster than normal GCC growth. Big companies like Hitachi Energy, Medtronic, and Walmart built real engineering power in India’s GCCs. These centers now matter to their worldwide product plans.
The data shows this shift is real. More than half of GCCs now handle full product work, from the first idea through launch. By 2030, most mature GCCs will work this way.
Digital-First Enterprises
New companies cannot compete using old ways of working. Digital-first businesses need speed that spread-out, AI-powered teams provide. GCCs become key support for business speed rather than just helpful extras.
Digital-first companies need three main things from GCCs:
- Cloud systems and platform building: Making systems that grow, stay strong, and handle fast testing without old limits. This takes teams that know modern cloud tools, containers, and API-first design.
- Real information and smart analysis: Getting useful facts from live information to help make choices right away. GCCs now build systems that collect data, analyze it, and help with decisions.
- Safety and business backup: Running spread-out teams in different areas that protect against problems in one place. This spread-out approach is now a business plan, not just a way to save money.
Enterprise agility is closely linked to GCC skill level. Companies with mature GCC models cut costs about 20% more than old-way companies, keeping money for new ideas and growth. More importantly, they launch products faster and work in a more flexible way.
Core Technologies Driving GCC Transformation
The technology used in future GCCs is very different from what existed just three years ago. Four new technologies are making big changes in the GCC world.
1. Generative AI and Agentic AI
Generative AI is moving from pilot projects to production systems. 58% of GCCs in India are already investing in agentic. By 2030, agentic AI, artificial intelligence that operates autonomously, makes plans, and executes multi-step tasks without constant human oversight, will define operational capability in leading GCCs. These systems will orchestrate workflows, manage customer interactions, detect compliance violations, and optimize resource allocation continuously.
2. Cloud-Native and Hyperautomation Architecture
Cloud-first infrastructure is essential. GCCs will operate on distributed cloud platforms with built-in security, automatic scaling, and compliance infrastructure. Hyperautomation uses AI, machine learning, and robotic process automation (RPA) to take over routine process work, so teams can focus on strategy and innovation instead of day-to-day execution.
3. Data Engineering and Predictive Intelligence
Next-generation GCCs embed data engineering and predictive analytics into every function. Real-time dashboards, predictive modeling, and AI-driven insights inform every business decision. Data becomes both the primary asset GCCs create and a key revenue generator.
4. Security, Compliance, and Automation Integration
Cybersecurity and regulatory compliance cannot remain separate functions. Leading GCCs will embed privacy-by-design, zero-trust security models, and AI-driven threat detection from inception. Regulatory compliance becomes automated and continuously monitored rather than reactive and manual.
Strategic Transformation: Moving from Execution to Ownership
The strategic transformation happening in GCCs changes jobs and duties in basic ways. This shift has multiple parts.
- From following orders to owning products: Teams move from doing what they are told to owning product plans, quality checks, and customer results. This requires different abilities, different rules, and different leadership.
- From doing it by hand to smart machines: Routine work goes away through machines and AI. Jobs that depend on people doing repetitive tasks are going down. As per current observations, nearly 80% of routine tasks are projected to be automated by 2026, pushing enterprises to rebuild their workforce mix
- From lots of people to smart machines: The next-generation GCC way uses machines, not just cheap workers, as its strength. This needs workers to keep learning new skills.
This shift brings both good chances and hard parts. Good chances come for people willing to learn cloud building, data work, AI, and leading products. Hard parts come when groups change how people work and move workers to new jobs.
68% of GCC leaders know where they are going and have a plan. Sixty-seven percent have money to do their changes. But real issues still exist, especially with AI fairness (54% say they are weak) and managing change (50%).
Why Tier-2 and Tier-3 Cities Are Strategic, Not Secondary
One big shift in GCC plans is spreading work to cities besides the big ones like Bangalore and Hyderabad. More than 215 GCC units now work in smaller cities, and by 2030, 39% of India’s GCC workers will be in these places.
This move is not just about saving money. Smaller cities offer:
- More workers ready to hire: Fewer GCCs in one spot means more STEM school graduates who like smaller cities have chances.
- Much lower costs: Saving 40-60% on buildings, tech, and daily costs while keeping work quality high.
- Better worker lives: Lower costs of living and shorter trips to work help keep workers and make them happier.
- Help from states: Karnataka began India’s first GCC plan to get 500 new centers by 2029. Uttar Pradesh wants more than 1,000 centers with help like lower taxes.
The hub model that grows from this spread gives both money savings and strength. Big choices and product work happen in big cities, while routine work grows in smaller cities.
How Will GCC Hiring and Skills Change by 2030?
GCC hiring is growing very fast. The future of global capability centers will need huge growth in workers. The World Economic Forum states that AI alone is expected to bring 1.3 million new jobs between now and 2030.
More than one-third of GCCs plan to hire 20% more workers by 2030. This shows a shift from lean work groups to big places that create new technology.
Workers in 2030 will be very different:
- AI jobs will be most common: People building machine learning, studying data, working with new AI, and making AI answers will be main jobs, not rare ones.
- Old skill jobs are fading: Jobs in old servers, fixing old software, and testing by hand are dropping as machines do this work. Workers must change their abilities.
- Teams work across areas: Product leads, makers of design, builders, and operations workers will work in mixed groups, not separated units.
- Leading people matters more: GCCs need more leaders at all points, tech leaders, product leaders, and business leaders.
Companies that spend on teaching workers new skills and growing leaders now will do better in 2030. Those that wait will not have enough workers and face real risk.
What Should Companies Focus On to Build a Next-Gen GCC?
Companies that want strong next-generation GCCs should focus on five key things:
- Make groups that know special skills in AI, cloud building, making products, and keeping systems safe. These groups become models and places where smart workers want to work.
- Change rules for faster work: Old GCC rules focus on control and following rules. New plans focus on speed and new ideas. This means changing who makes choices, how money is given, and who is in charge.
- Spend money on always learning: Programs that teach cloud building, AI, data work, and leading products are a must. Groups that see learning as extra will fall behind.
- Work with new companies: India has 1000+ new startup companies that have new tech, special workers, and different ideas. GCCs that work with startups move faster with new ideas.
- Make AI rules and safety first: 54% of GCC leaders say AI fairness and safety are weak spots. This is a big gap as AI becomes key. Companies need clear rules about fair treatment, showing work, safety, and rule-following.
Conclusion
The future of global capability centers is taking shape right now. Companies building GCCs that will work in 2030 are getting ahead of their rivals. The mix of AI, product building, digital business, and spread-out worker teams brings big chances.
India’s GCC sector, with 1.9 million workers, strong AI workers, and growing government help, is at the center of this shift. But the race is worldwide. Companies in Europe, North America, and Asia that build GCCs that match what the future needs will grab more of the market and do new things faster.
The question now is not whether to invest in GCCs. The real question is how fast companies can build GCCs that create real new ideas, work quickly, and add real value. Those that do this well will see GCCs become the center of worldwide work, from making products to serving customers to keeping work going. Those that wait will fight against rivals with mature, AI-powered, and smart GCC work.
FAQs
What is a Global Capability Center, and why should my company care?
A GCC is an office in another country that does key business work for the main company. It matters because it gives access to world-class workers, lets work happen all day, helps launch new things faster, and costs less money than onshore teams.
How is AI changing what GCCs do today?
AI is moving from test projects to core work. GCCs now use AI in machines doing work, study information, make products, and help with choices. Eight out of ten new GCCs make AI a top goal from the start, making it key to success.
Should my company open GCC offices in smaller cities?
Yes. Smaller cities have workers that no one is using yet, cut costs by 40-60%, and help keep workers longer without losing quality. This spread-out model will be normal by 2030.
What abilities will GCCs want by 2030?
Cloud building, AI and data science, information study, leading products, and supervising others are top needs. Old jobs like basic help, old software work, and hand testing are declining and need retraining.
How fast should we move toward AI GCCs?
Speed is very important. Companies that wait too long risk falling behind others building AI teams now. Starting with one or two projects that give fast returns is smart, making the start too hard is not.
What is the hardest part of building new GCCs?
Getting people to change their thinking ranks among the top hard parts. Changing from seeing GCCs as just low cost to seeing them as new idea makers, building new processes for machines, and moving workers to new jobs needs steady, structured work.
