Copyright and IP considerations under Indian law remain unsettled for AI training, necessitating conservative, well-documented licensing and data source practices that respect contractual restrictions and source terms.

GCCs cannot rely solely on a global parent’s AI ethics policy; they require an India-specific governance layer with a joint operating model across engineering, legal, compliance, and governance functions.

India adopts a techno-legal approach rather than a single AI Act, requiring GCCs to navigate overlapping frameworks including IT law, DPDP Act, consumer protection, criminal law, copyright, sectoral regulations, vendor contracts, and intermediary due diligence.

AI governance for Bengaluru GCCs is shifting from voluntary ethics to a structured, multi-law framework anchored by India’s AI Governance Guidelines, SGI Rules, the DPDP framework, and the Digital India Act, affecting legal, compliance, data protection, IP, cybersecurity, product governance, and board reporting.

A 60-day readiness checklist is proposed: inventory all AI systems in production, testing, and use; select a user-facing Indian feature and verify SGI labeling; ensure intra-group data processing agreements cover training data flows; gaps indicate insufficient operational maturity.

AI risk classification should be use-case driven, with human oversight empowered to intervene, and deployment documentation maintained for auditability and accountability.

DPDP overlays on AI training data require a defensible lawful basis, purpose limitation, data minimization, and cross-border transfer controls, with emphasis on not repurposing data without proper legal basis and restricting non-production environments.

AI incident response should include detection, triage, notification, containment, and post-incident review, supported by templates and tabletop exercises for regulatory or reputational impact.

SGI labeling under IT Intermediary Guidelines and Digital Media Ethics Code Amendment Rules (2026) requires clear labeling of synthetic content and consideration of labeling in product features, with audit logs detailing generation details, model version, prompts, and surfaces where outputs appear.

The article positions a leading firm as a guiding partner for GCCs on AI governance, DPDP compliance, vendor contracts, incident response, and AI litigation support, framing the 60-day readiness exercise as essential for regulatory, auditor, and investor confidence.

GCCs face unique challenges as data and model usage control may be split between the parent and the Indian entity, requiring careful management of data provenance, cross-border transfers, and Indian regulatory disclosures.

Six key operational areas for SGI governance in GCCs: training data ingestion, model development and fine-tuning, evaluation and red-teaming, deployment and inference, vendor models and APIs, and cross-border data flows, each with clear ownership and processes.