Global Capability Centres (GCCs) in India are increasingly expanding beyond traditional technology support functions. Many are now involved in product development, engineering, analytics, cybersecurity, research, and innovation. Artificial intelligence is adding another dimension to this evolution. GCCs are building teams and capabilities that can support AI development, deployment, experimentation, and business use cases. For GCC leaders, building GCC AI capabilities requires more than hiring AI specialists. It involves developing the right talent, infrastructure, data environment, governance practices, and collaboration models.
Why are GCCs Expanding AI Capabilities?
AI is becoming relevant across industries and business functions. Companies are exploring AI for software development, customer service, analytics, operations, risk management, product development, and decision support.
GCCs can contribute to these initiatives because they often bring together technology talent, domain expertise, and global business processes.
This creates an opportunity for GCCs to move further into strategic technology and innovation roles.
What Talent Do GCCs Need?
Building AI capabilities requires a combination of technical and business skills.
Data scientists, machine learning engineers, AI engineers, cloud specialists, cybersecurity professionals, product managers, and domain experts can all contribute to AI initiatives.
However, talent development should not rely only on external hiring. GCCs can also reskill existing technology teams and create structured learning programmes.
A strong talent strategy can make GCC AI capabilities more sustainable over the long term.
Why Does Data Matter?
AI systems depend heavily on data. GCCs need access to reliable, relevant, and well-governed information to develop useful AI applications.
Data quality, accessibility, security, privacy, and governance should therefore be considered alongside AI development.
Without a strong data foundation, AI projects may struggle to move from experimentation to production.
What Infrastructure Is Required?
AI workloads can require specialised computing, cloud platforms, storage, data pipelines, and application environments.
GCC leaders need to determine which infrastructure is appropriate for their AI priorities.
Not every AI use case requires the same technology architecture. Some applications may require real-time processing, while others may focus on analytics or internal productivity.
Infrastructure planning should therefore be connected to specific business use cases.
How Important Is Responsible AI?
As GCCs become involved in AI development and deployment, governance becomes increasingly important.
Leaders need to consider privacy, security, transparency, model performance, data usage, and regulatory requirements.
Clear governance can help teams understand how AI should be developed and used while reducing potential business and technology risks.
How Can GCCs Collaborate With Global Teams?
AI initiatives often involve teams across different countries and functions.
GCCs can collaborate with global product, technology, data, security, and business teams to develop AI solutions that address real organisational needs.
This collaboration can also help GCCs understand global priorities while contributing local technical expertise.
What Should GCC Leaders Prioritise?
GCC leaders should begin by identifying areas where AI can create measurable value. They can then assess talent, data, infrastructure, governance, and operating requirements.
Rather than launching multiple disconnected AI experiments, GCCs can build reusable capabilities that support several business use cases.
This can make GCC AI capabilities more scalable and strategically relevant.
Final Thought
India’s technology talent and growing GCC ecosystem create opportunities for organisations to develop advanced AI capabilities. However, success will depend on more than technical expertise.
GCC leaders need to combine talent development, strong data foundations, suitable infrastructure, responsible AI practices, and collaboration with global business teams. A structured approach to GCC AI capabilities can help centres contribute more directly to innovation and long-term technology strategy.