Artificial intelligence (AI) has moved beyond hype to become a core driver of business transformation. As adoption speeds up, enterprises seek ways to capture value at scale, and Global Capability Centres (GCCs) are stepping up. By embedding automation in global capability centres, GCCs are piloting generative AI use in customer engagement. They deploy intelligent workflows that impact the operations and even influence business strategy. For example, in India, over 70% of GCCs now prioritise generative AI, with half already applying it in live use cases. The deepening GCC automation AI impact is turning them into centres of excellence and innovation hubs for businesses globally.
AI and automation driving strategic value
Automation in global capability centres initially began as a way to optimise costs and eliminate manual, repetitive tasks. Over time, it has expanded into more advanced forms of cognitive and predictive automation, powered by AI. Moreover, AI-led analyses identify trends and uncover new insights for businesses. AI and automation are fundamentally changing the way GGCs operate. The transformation spans technologies and processes such as:
- Intelligent Process Automation (IPA): It combines robotic process automation with AI/ML to automate complex workflows such as finance reconciliation, compliance monitoring, and HR service delivery.
- Natural Language Processing (NLP) and chatbots: They power self-service for IT support, HR helpdesks, and customer interactions, reducing manual interventions and improving service experience.
- Predictive analytics and Machine Learning (ML): These technologies transform supply chain forecasting, demand planning, and risk modelling. Such ML-led analytics help businesses stay agile and respond faster to market shifts.
- Computer vision: It automates document verification, quality checks in manufacturing, and anomaly detection in operational processes.
- Agentic AI systems: Unlike traditional AI models that only generate outputs, agentic AI can plan, act, and learn autonomously within enterprise systems. GCCs are piloting it to redesign workflows, IT operations, and proactive customer engagement. Agentic AI aims to reduce the need for constant human supervision.
- Generative AI: Gen AI supports knowledge management, code generation, and CX design. Such use cases of Gen AI accelerate innovation and time-to-market for GCCs.
When applied at scale, these capabilities deliver measurable outcomes ranging from 30 to 40% cost savings, faster cycle times and new revenue opportunities.
GCC automation and AI impact on workforce transformation
The impact of automation in global capability centres is felt at a deeply human level, too. With technological advancements, the GCC workforce also undergoes a transformation in capabilities. To maximise GCC AI automation, organisations must review their talent models. As the demand for data science, AI and automation design roles surges, reskilling is gaining importance.
Moreover, GCCs are becoming ecosystems where capability transfer, and skill diffusion thrive. Employees gain new AI capabilities by working across diverse projects. This ensures the workforce evolves as quickly as the technology itself.
A recent survey found that 70% of GCCs in India prioritise generative AI initiatives, with more than half already applying them in operations and customer experience. While India often serves as a vivid example for GCCs, these trends represent a global reality that AI is encouraging capability development.
from cost centres to growth engines
AI has redefined GCC success. Once measured primarily by operational savings, today their value is judged by how they impact enterprise agility, innovation, and revenue growth.
By embedding AI into forecasting, customer engagement, and product development, GCCs are directly shaping business growth. They shorten ROI cycles, improve response to global markets, and influence strategy through data-driven insights. Moreover, GCCs act as innovation pilots by testing AI-powered solutions before scaling them enterprise-wide. This role positions them as true growth engines rather than cost centres.
future outlook: the AI-first GCC
As AI adoption deepens, new models of GCCs are emerging to meet business needs. Key trends include:
- Nano GCCs: Nano GCCs are compact, highly focused GCCs built for lean and nimble operations. These hubs often focus on specific domains such as R&D, analytics and AI. They focus on delivering high-impact innovation with minimal infrastructure. They respond faster to market shifts and enable prototyping and scaling without heavy capital investment.
- Agentic AI and autonomous agents: GCCs are increasingly using AI agents that can plan, act, and learn rather than execute repetitive tasks. GCCs employ them in real-time business intelligence, automated operations, proactive risk detection, and dynamic decision-making.
- AI-led centres of excellence (CoEs): More GCCs are setting up or expanding CoEs focused on AI and automation to drive enterprise-wide standards, shared tools, governance, and scaling of best practices.
- Decentralised and hybrid decision models: There is a growing shift from centralised decision-making for GCCs. Decentralised and hybrid models are emerging where GCCs have greater autonomy for AI and automation decisions. It enables faster reaction to localised needs and experimentation.
how can Infosys BPM drive AI and automation in global capability centres?
Infosys BPM enables enterprises to design and scale AI-first GCCs. Through proven frameworks, accelerators, and global talent programs, we help organisations adopt automation responsibly. Our proven processes unlock innovation and build future-ready operating models.
