How can AI-first GCCs run responsible AI practices?

What is a GCC? 

Tier 1 and 2 Cities in India seeing rapid expansion of GCCs

A Global Capability Centre (GCC) is a wholly owned strategic unit of a multinational organisation that supports its global operations through technology, talent and innovation. GCCs have evolved into Centres of Excellence (CoE), bringing together subject-matter expertise, high-quality technology talent, and an environment that fosters efficiency and growth.

GCCs offer significant business advantages, such as access to global talent pools to overcome skill shortages, enhance capabilities, enhance quality and productivity through standardised processes, and the development of new innovative solutions and services that can be deployed globally.

Transformation from traditional GCCs to AI First GCCs 

Traditional GCCs focus primarily on process efficiency and cost optimisation. They streamline global operations and deliver consistent, high-quality services. However, today, by leveraging advanced technologies such as artificial intelligence, machine learning, and analytics, GCCs are transforming organisations to optimise processes, enhance decision-making, and drive innovation at scale. 

As today’s world shifts toward AI-enabled operating models, GCCs are also transforming as the engines of enterprise AI transformation. By embedding AI into core architecture, GCCs are evolving from execution centres into strategic innovation hubs that design, build, and deploy AI capabilities for the entire enterprise. 

According to a leading analyst firm, over 60% of new GCC mandates in 2024 had a built-in digital and AI-first character. AI-first GCCs redefine operational intelligence by integrating it into the core. AI-first GCCs through AI, analyze and optimize processes continuously, drive predictive and prescriptive insights through data, and shift decision-making from periodic trend analysis to real-time analysis. 

By embracing advanced technologies, AI-First GCCs help enterprises optimise operations, uncover new revenue streams, strengthen global competitiveness, and build future-ready capabilities.

Pillars of AI first GCCs 

AI-first GCCs rest on several strategic pillars, including:

• Advanced Technology Integration: AI-first GCCs embed AI, ML, and automation tools deeply across processes to drive insight, accuracy, and speed. These systems constantly learn and refine processes, resulting in faster delivery, reduced manual effort, fewer errors, and much higher efficiency across global functions.

• Data-driven analytics and decision making: For AI-first GCCs, data becomes the core foundation for all decision-making. These centres build integrated data platforms that unify structured and unstructured data from multiple regions and business units. This allows real-time visibility, advanced analytics, and consistent access to quality insights across the organisation. The data-centric approach optimizes global operations proactively.

• Predictive and Prescriptive Intelligence: AI-first GCCs go beyond descriptive reports by generating predictive forecasts and prescriptive recommendations. With these capabilities, organisations can anticipate market shifts, evaluate risks, plan resources better, and take proactive decisions. It enables advanced use cases like demand prediction, risk modelling, customer behaviour insights, and strategic scenario planning.

• Talent Transformation: AI-first GCCs focus on augmenting human talent, not replacing it. By automating repetitive and data-heavy tasks, employees can concentrate on strategic and creative work. These GCCs also invest heavily in upskilling teams in data, AI, and digital skills, creating a workforce that is comfortable working with AI tools and adopting a data-driven mindset.

• Modern Technology Infrastructure and Scalable AI Platforms: AI-first GCCs rely on strong technology foundations, cloud-native systems, unified AI/ML platforms, data lakes, automation frameworks, and generative AI capabilities. This infrastructure allows them to scale AI solutions globally, integrate with legacy systems, and support real-time global operations without disruption.

• Innovation and high-value business contribution: Rather than functioning as cost centres, AI-first GCCs evolve into strategic innovation hubs. They help build new products, digital solutions, and revenue-driving capabilities using AI insights, simulations, and experimentation. This shifts their role from operational support to enterprise-wide value creation.

How can AI-first GCCs ensure Responsible AI Practices?

AI-first GCCs should ensure that AI initiatives are developed and deployed responsibly, in compliance with relevant standards and rules. Responsible AI practices include; 

• Ensuring that the AI systems are transparent, explainable and bias-free

• Maintaining data privacy and security

• Establishing a governance framework for AI, including ethical principles, risk management processes and accountability mechanisms.

• Developing ethical guidelines and ethical oversight.

• Having human oversight to ensure AI systems operate within ethical boundaries and align with the values of the organisation.

• Conducting regular AI Impact Assessments considering the social, economic and environmental implications of the AI.

• Conducting regular training and awareness programs for the GCC employees on AI ethics and compliance.

How ISO 42001 would help in Responsible AI Practices?

Practical steps for ensuring responsible AI in AI-first GCCs, leveraging ISO 42001, include:

• Establish Responsible AI Governance: Set up an AI governance framework aligned with ISO 42001, defining roles, responsibilities, and accountability to oversee AI development and deployment ethically and legally.

• Conduct AI Risk and Impact Assessments: Regularly evaluate AI systems for bias, fairness, and ethical implications, identifying risks and implementing mitigation measures before deployment and throughout the AI lifecycle.

• Implement Transparency and Explainability Controls: Design AI models and processes to be interpretable by stakeholders, documenting data sources, model decisions, and providing clear explanations for AI-driven outcomes.

• Ensure Data Privacy and Security: Apply strict data governance policies to protect personal data, enforce access controls, and comply with data protection regulations, thereby safeguarding AI inputs and outputs.

• Maintain Human Oversight: Incorporate human-in-the-loop mechanisms where critical decisions are supervised or reviewed by humans to prevent unethical or harmful AI outcomes.

• Continuous Monitoring and Auditing: Conduct audit processes to monitor AI system performance, biases, and compliance with ethical standards, enabling timely corrections and updates.

• Train and Raise Awareness: Provide ongoing training for AI teams and broader employees on responsible AI principles, ethical usage, compliance requirements, and ISO 42001 adherence.

• Document and Report Compliance: Maintain comprehensive records of AI governance activities, risk assessments, audits, and improvements to demonstrate compliance with ISO 42001 and regulatory standards.

  
  

As organisations embrace AI-led transformation, AI-First GCCs have emerged as pivotal drivers of enterprise innovation and global competitiveness. But the real measure of success lies not just in deploying AI at scale but in doing it responsibly.

By adopting strong governance structures, embedding ethical principles, complying with global standards like ISO 42001, and fostering a culture of transparency and accountability, GCCs can lead the world in building responsible, trustworthy, and human-centred AI.