By Kumar Rajagopalan, Vice President, Strategic Initiatives and Country Head India at Dexian
Over the recent years, Global Capability Centers (GCCs) have undergone a massive evolution, being a lot ahead in technology compared to their former role merely as cost-efficient suppliers of services. In the earlier years of their existence, GCCs mainly served as cost-efficient vendors. However, now they are becoming a hub of innovation, technology, and analytics. The next big shift in the evolution of GCCs is likely to happen due to agentic AI which represents “AI systems that are capable of achieving goals, taking decisions, performing actions, and adapting based on their experience while involving minimum degree of human influence”.
Automation Transformation to Autonomy
While traditional automation uses fixed guidelines, Generative AI has the capacity to perform various functions that help humans through information generation, information processing, and question answering. But agentic AI has a greater potential.nAI agents can be assigned a business goal and can decide on actions to take to reach it. Since GCCs deal with finance operations, one can say that AI agents can take on the duties such as tracking invoices, identifying discrepancies, communicating with various teams, updating organizational systems, and including the most complicated cases for human investigation.
GCCs as Centers of AI Implementation
As companies move forward with the adoption of the agentic AI technology, GCMs are on the way to turn into centers of testing and implementation. Thanks to their previous experience with technology, data, international processes, and diverse business activities, they can smoothly fit into the application of AI-enabled operational models.
Instead of serving only as solution providers to their parent companies, GCMs could soon become creators of AI programs for different areas including finance, human resources, procurement, customer support, cyber security, IT operations, and supply chain management. This could also redefine the place of GCMs in international companies, as their value proposition moves gradually toward the innovation and intelligent management of processes.
Human-AI Workforce Will Be More Collaborative
Agentic AI does not imply total replacement of human teams; it may create a hybrid workforce, in which workers deal with, observe, and cooperate with AI agents. At the same time, people are likely to abandon monotonous execution to concentrate on the work that entails judging, interacting with other parties, being creative, and making strategic decisions. Moreover, there can appear new specializations related to the orchestration of AI, governance of agents, assessment of models, process redesign, and AI security.
For GCM leaders, this means that training is essential for the introduction of AI. Employees have to know not only how to operate AI tools but also how to assess the generated decisions made by AI and what to do if the agent goes beyond the limits of its functions.
Using AI Comes with New Risks
The independence that makes agentic AI appealing also comes with new dangers. An AI technology which takes actions across enterprise systems needs to be highly regulated in terms of permissions, data access, accountability, and decision-making. Companies need a governance framework to define what AI technologies should and shouldn’t do, when human approval is required, how decisions are recorded, and how performance is assessed.
Cybersecurity will also become more critical, as compromised AI technologies could jeopardize interconnected systems. Building trustworthy agentic AI is thus a matter of coordinating technology, security, legal, compliance, and business departments rather than regarding it as a solely IT-oriented solution.
Data Infrastructure is the Key to Success
Agentic AI heavily relies on the quality of the data used in enterprises. Inconsistent processes, disconnected databases, and redundant technologies can lower the efficiency of AI technologies. Companies will, therefore, have to invest in updated data architecture, APIs, cloud infrastructure, identity management, and observability technologies. The organization will also have to assess where agents may operate independently, and where traditional software, workflow automation or human intervention work better. The aim is not to utilize agentic AI in all the processes, but to find the best processes for autonomous decision-making that will generate business value.
A New Development in the Transformation of Global Capability Centres
It is possible that agentic AI may become the next major stage in the development of GCCs. Most likely, GCCs that profit from it will be those having strong process knowledge, good-quality data, professional workforce, and responsible governance, in addition to available AI capabilities. Actual possibilities go beyond the introduction of a single AI agent or AI applications by GCCs. They lie in understanding the way humans and artificial intelligence work together to perform tasks.