In one case, a Global Capability Centre (GCC) team in Bengaluru stopped a profitable AI rollout last month after internal audits revealed inconsistent performance across customer segments. The suspension provided an opportunity to both lose and gain time. The latter decision reflects a new reality: GCCs will not be required to adhere to AI ethics and compliance in 2025, but as a matter of strategy, they will be able to achieve scale, reputation, and economic value.
The Indian GCC market is both vast and expanding; over 1,900 GCCs work in India, generate about USD 64.6 billion in revenue, and involve almost 2 million professionals. By 2030, analysts estimate that the GCC number in India will grow significantly to 3500 led by AI and research and development requirements imposed by multinational corporations. These centres are the main engines of execution of enterprise AI; therefore, the governance stakes are not localised. Meanwhile, regulators are coming to agreements on AI standards. The EU AI Act is already in effect and implementing obligations (with key provisions taking effect until 2026-2027), raising the compliance threshold of any GCC building product or service offered in Europe. In addition to this, the national legislations on data, like India’s Digital Personal Data Protection Act (DPDP Act, 2023), demand cautious data management and mapping across borders. The combination of these rules implies GCCs will have to design multi-jurisdictional controls and not as an add-on.
Responsible AI cuts the financial, operational and reputational risk, and it opens up the possibility of growth. Companies that have made compliance a part of model lifecycles do not face the cost of remediation, regulatory fines and delayed entry into the market. In addition, GCCs with certified governance capabilities receive more valuable mandates from HQ (core product development, generative AI experimentation, and intellectual property creation), generate more revenue per centre, and improve talent retention. Other international research also indicates that the companies that invest in AI governance achieve higher deployment speed and increased stakeholder confidence, an economic multiplier when implemented through hundreds of GCCs.
The following are brief requirements that all Global Capability Centres should observe this year:
DPIAs and explainability are managed by AI product managers, transfers and consent are mapped, engineering pods integrate monitoring and retrain pipelines, and legal teams handle regulatory submissions. HR and L&D facilitate training programmes that enable governance to function.
GCCs working with APAC and MENA markets should also consider region-specific ethics frameworks and toolkits published by cities and states. This includes local UAE ethical standards as well as national AI policies that emphasise human-centred design. In the case of GCCs that favour Europe, EU AI Act schedules and classification regulations must be considered when developing products and selecting vendors.
By 2026–2027, the major GCCs will possess independent AI audit departments, interactive compliance dashboards, and RegTech integrations to execute continuous conformity assessments. These GCCs will become strategic hubs by attracting more valuable work, reducing external audit friction, and making compliance a talent magnet.
AI compliance and AI ethics are business requirements in 2025 in the GCC. Governance centres that treat governance as infrastructure, documented, automated, and accountable, will not only avoid the stigma of regulation but will also claim the new and more lucrative responsibilities that businesses are outsourcing. There is only one way to become a GCC leader: first, develop trustworthy AI, and then reap the benefits of profits, stability, and reputation.
Hyderabad, Bangalore and Pune have become significant pharma innovation centres with global delivery centres of major biotechnological and pharmaceutical firms such as Novartis, Pfizer, AstraZeneca and GSK. They offer an economic benefit of calculation, a variety of scientific and technical human resources, and speedy time-to-market. On average, businesses reduce between 25-40 percent of the operational costs and increase the rate of innovation. The next-generation operations of Pharma GCC focus on advanced molecular modelling, AI/ML-based drug discovery, cloud supercomputing, and data integration platforms, as well as quantum-ready simulations. Pharma GCCs use AI to screen molecules, predict the efficacy of drugs, optimise clinical trials and aid in making data-driven decisions, resulting in smarter, faster and safer drug pipelines. Pharma GCCs will be global innovation ecosystems that are a combination of computational chemistry, generative AI, and quantum computing. They will turn into the hubs linking data science, discovery and regulatory intelligence in the global arena. Aditi, with a strong background in forensic science and biotechnology, brings an innovative scientific perspective to her work. Her expertise spans research, analytics, and strategic advisory in consulting and GCC environments. She has published numerous research papers and articles. A versatile writer in both technical and creative domains, Aditi excels at translating complex subjects into compelling insights. Which she aligns seamlessly with consulting, advisory domain, and GCC operations. Her ability to bridge science, business, and storytelling positions her as a strategic thinker who can drive data-informed decision-making.
The Moment: Data and Growth
Economic Benefit

What GCCs Need To Do in 2025
Compliance Area
Required Implementation
Business Rationale
Governance & Accountability
AI governance charter; role-based accountability matrix; AI register
Secures ownership in the model lifecycle.
Cross-border Data Controls
DPIAs, data-Mapping, encryption, RBAC, and legal means of transfer.
Compliant with DPDP and foreign transfer requirements.
Bias & Fairness
Bias tests periodically, explainability records, fairness dashboards.
Minimises the risk of discrimination; exceeds the high-risk AI regulations.
Model Monitoring
Drift detection, human-in-the-loop gates, retraining SLAs
Ensures model accuracy and safety of operation.
Vendor Risk
Third-party AI assessment, SLAs, security attestations
Manages exposure of control supplier and supply risk.
GenAI Safety
Timely governance, mitigation of hallucinations, provenance, logging.
It eliminates IP leak and false information
Incident & Audit Readiness
Audit Playbooks Traceable logs, audit kits, regulatory notification.
Shortens time-to-respond for regulators and clients
Personas and Practical Roles
Third-party and Regional Entities (UAE, EU, India).
The Vision Of Success
Conclusion
frequently asked questions (FAQs)

Aditi