As enterprises accelerate digital transformation, the Global Capability Center (GCC) evolves from a cost-efficiency engine to a strategic innovation hub. Today, the most forward-looking organizations are asking:
How do we build an AI-first GCC that drives transformation, not just operations?
Whether you're setting up a GCC for the first time or evolving an existing one, this article outlines the blueprint for an AI-first GCC covering infrastructure, security, AI enablement, operating model, organizational structure, and the path forward.
Why AI-First?
An AI-first GCC is designed to:
- Drive innovation through AI, data science, and cloud-native platforms
- Foster collaboration with universities, startups, and strategic partners
- Enable domain-led transformation across industries like BFSI, retail, and healthcare
India remains a top destination for GCCs due to its deep talent pool, cost advantages, and thriving tech ecosystem. However, success depends on strategic clarity, governance control, and the right operating model.
Core Infrastructure for AI-First GCC
- Networking: SD-WAN, enterprise-grade routers, and telemetry platforms like Datadog or ZDX
- Security: Zero Trust architecture with Zscaler, Palo Alto, or Cloudflare; CASB, DLP, SIEM/SOAR integration
- AI Platforms: GPU clusters or cloud-native AI platforms (Azure ML, AWS SageMaker); LLM orchestration; Responsible AI frameworks
- Governance: Modular architecture, bias detection, explainability, and compliance guardrails
Operating Model: Retaining Strategic Control
When working with third-party setup partners, especially in India, enterprises must ensure:
- Governance Ownership: Control over hiring, vendor selection, and architecture
- Vendor-Agnostic Infrastructure: Avoid exclusive deals; use open standards and multi-cloud strategies
- Custom Org Design: Tailor org structure to AI-first vision - CoEs, pods, agile squads
- Transparent Reporting: KPIs, dashboards, and review cadences
- Hybrid Leadership: Blend local leadership with enterprise oversight
Suggested Organization Structure
| Role |
Reports To (Global) |
Focus |
| GCC Site Head (India) |
Head of GCC Strategy |
Delivery, governance, stakeholder alignment |
| Delivery, governance, stakeholder alignment |
Chief Data & AI Officer |
AI CoE, model development, innovation |
| Head of Engineering & Cloud |
CTO |
Cloud platforms, DevOps, and telemetry |
| Head of Cybersecurity |
CISO |
Zero Trust, audits, compliance |
| Head of Talent & Culture |
CHRO |
Hiring, retention, and learning |
| Program Managers |
GCC Site Head |
Agile delivery, pods, sprints |
| Functional Leads |
Business Unit Heads |
Domain alignment, business impact |
Top Challenges Ranked by Likelihood & Priority
| Priority |
Challenge |
Solution |
| High |
Provider lock-in & exclusivity |
Negotiate vendor-agnostic contracts; retain architectural control |
| High |
Opaque governance models |
Define clear governance structures; ensure transparency |
| Medium |
Talent acquisition & retention |
Competitive salaries, career growth, and a strong employer brand |
| Medium |
Security & compliance |
Zero Trust, DLP, SIEM/SOAR, local legal expertise |
| Medium |
Regulatory constraints |
Regional cloud zones, federated learning, and data anonymization |
| Low |
Infrastructure complexity |
Modular, cloud-native architectures; experienced infra partners |
| Low |
Cultural alignment |
Shared OKRs, cross-functional squads, rotational leadership |
| Low |
AI governance |
Responsible AI frameworks, third-party monitoring tools |
| Low |
Underutilization of AI |
Prioritize high-impact use cases; embed AI into core processes |
Existing GCC Models
| Model |
Best For |
Control |
Setup Speed |
Innovation Potential |
| AI-First GCC |
Strategic transformation |
High |
Medium |
High |
| Traditional GCC |
Cost optimization |
High |
Medium |
Low |
| Hybrid GCC + Vendor |
Balanced delivery |
Medium |
Fast |
Medium |
| Build-Operate-Transfer (BOT) |
Fast entry with future control |
Medium → High |
Fast |
Medium |
| Federated Innovation Hubs |
Agile innovation |
High |
Medium |
High |
| Vendor-Led Centers |
Rapid scale |
Low |
Fast |
Low |
| Remote-First Teams |
Flexibility |
Medium |
Medium |
Medium |
Who Should Build an AI-First GCC?
Ideal Candidates
- Enterprises setting up a net-new GCC
- Companies with AI-led transformation goals
- Organizations seeking IP creation, data science scale, or cloud-native innovation
- Firms with strong global governance and tech maturity
Not Yet Ready
- Companies with traditional GCCs focused on back-office operations
- Enterprises with vendor-led centers and limited internal AI capabilities
- Organizations lacking AI governance frameworks or cloud readiness
Path Forward for Existing GCCs
If you already have a traditional GCC, here’s how to evolve toward AI-first:
- Assess Current Capabilities: Identify gaps in AI, cloud, and governance
- Define AI Vision: Align with enterprise transformation goals
- Build AI CoE: Start with a small team focused on high-impact use cases
- Modernize Infrastructure: Upgrade to cloud-native, telemetry-enabled systems
- Embed Governance: Introduce Responsible AI, compliance, and transparency
- Restructure Org: Shift from service delivery to innovation-led pods
- Upskill Talent: Invest in AI fluency across roles
Final Thoughts
An AI-first GCC is not just a facility. It is a strategic asset. Whether you're starting fresh or evolving an existing center, the opportunity is clear:
Move beyond cost and scale toward innovation and transformation.
Start with a bold vision. Invest in the right infrastructure. Design a transparent operating model. Most importantly, you should retain control over your architecture, governance, and vendor strategy to ensure long-term flexibility and success.
