Global Capability Centres

The GCC that runs on agents — and builds them for the enterprise

Employee help desks, HR, IT, finance operations, and shared services delivered by governed agents — and a centre of excellence that designs, operates, and scales agentic communications for the global enterprise.

See the pilot
The executive problem

GCCs are the shared-services engine of global enterprises — and shared services are mostly structured communications: tickets, requests, approvals, status checks, escalations.

The GCC has a double role: the best first customer for an agentic communications layer, and the natural global operator of it. The centre that automates its own help desks earns the mandate to build agents for the whole enterprise.

GCC economics are measured relentlessly in cost per ticket and SLA. Agentic resolution moves both in the same quarter it deploys.

Why now
  • GCC mandates are shifting from cost arbitrage to capability leadership — AI operations is the new charter
  • Enterprise AI platform decisions are being made now; GCCs that move first own the agenda
  • Multilingual global workforces need support coverage that follow-the-sun staffing can't economically provide
  • Ticket volumes grow with every acquisition and system migration the GCC absorbs
$64.6B
India GCC market in FY2024 — 1,700+ centres, 1.9M+ employees, heading to ~$100B by 2030
NASSCOM–Zinnov India GCC Landscape Report
40–60%
of L1 tickets are password resets, status checks, and how-to questions
ITSM benchmarks; validate per customer
2 roles
GCC as first customer of the platform — and as the enterprise's agent-building centre of excellence
strategic construct
Priority use cases

Ranked by value, feasibility, and speed

Start where value and feasibility intersect. Tags mark the lighthouse, the fastest path to production, and the plays partners lead.

Use caseValueFeasibilitySpeedNote
IT service desk (L0/L1 resolution)
Lighthouse
Password resets, access requests, how-to; ITSM APIs are mature
HR support (policy, leave, letters, payroll queries)
Fastest to production
HRMS integration; instant employee-experience win
Finance operations (invoice status, T&E, vendor queries)
Highest volume
High volume from vendors and employees alike
Procurement support & intake
Guided intake beats form abandonment
Employee onboarding & offboarding orchestration
Executive value
Cross-system agentic workflow showcase
Knowledge access & policy Q&A with citations
Grounded enterprise search; day-one value
Agent assist for retained human desks
Uplift for complex-queue specialists
Enterprise process notifications & chase-ups
Approvals, timesheets, compliance training nudges
Multi-language employee engagement
Global workforce, one support layer
Agent-building CoE for business units
Partner-led
GCC operates the platform and ships agents to the enterprise
Lighthouse journey

Employee IT + HR support, before and after

Today
  1. 1Employee searches the intranet, gives up, raises a ticket in the wrong category
  2. 2L1 agent triages 4 hours later, asks for details already in the ticket
  3. 3Password reset — a 2-minute fix — took 6 hours of elapsed time and $18 of cost
  4. 4HR policy questions queue behind payroll-run spikes
  5. 5Quality team samples tickets; systemic knowledge gaps persist for quarters
With the agentic layer
  1. 1Employee asks in chat, voice, or the portal — in their language, 24/7
  2. 2Identity and entitlements resolved via SSO; answers cite governed policy sources
  3. 3Password resets, access requests, leave applications executed immediately against ITSM/HRMS
  4. 4Unresolvable cases become perfectly-formed tickets routed to the right queue with context
  5. 5Every interaction scored; knowledge gaps and process friction surface to owners weekly
Watch the transformation

The same interaction, two worlds — racing live

The loop runs itself: the conventional journey stalls, backtracks, and drags while the agentic one flows straight through — grounding, acting, and resolving with a human approval exactly where policy demands one. Pause anytime and click any node to explore that step.

Scenario: A new analyst in the Manila centre is locked out of two systems on day 3, with a leave request pending
Today
same interaction, two worlds
Agentic layer
Elapsed time to resolution
6 hours – 2 days
minutes, in one thread
Assumption
Cost per L1 ticket
$15–25 fully loaded
self-service economics
Benchmark
Reset/status share of L1
40–60% of volume
fully automated
Benchmark
Tickets per incident
2–3 across teams
0–1, auto-filed with context
Platform capability
Experience measurement
quarterly survey
100% of interactions
Platform capability
Sources & assumptions
  • · Elapsed time to resolution: Conventional = typical L1 SLA pattern (assumption); agentic = platform design
  • · Cost per L1 ticket: HDI / service-desk benchmarks (validate per customer); Gartner $1.84 self-service median
  • · Reset/status share of L1: ITSM benchmarks (validate per customer); automation is a platform capability
  • · Tickets per incident: Process design: root-cause reasoning across systems
  • · Experience measurement: Platform capability
  • · Gartner, customer service cost benchmarks (2024): $13.50 median assisted vs $1.84 self-service per contact
  • · McKinsey, digital-first collections research: 20–25% NPL reduction among leaders; up to 40% opex reduction with gen AI
  • · Baymard Institute: ~70% average cart abandonment (meta-analysis)
  • · IAMAI–Kantar via IBEF (2025): 900M+ Indian internet users; 98% consume Indic-language content
  • · LeadSquared and vendor funnel studies: 78% of students choose the first institution to respond (directional, vendor data)
  • · HDI / ITSM operator benchmarks: $15–25 per L1 ticket; 40–60% of L1 volume is resets/status (validate per customer)
  • · Conventional-flow wait times and volumes are typical operator patterns — assumptions to replace with the customer's own baseline
  • · Agentic-flow behaviors (context retention, 100% logging, in-line policy checks) are platform capabilities, not projections
One integrated solution — clear ownership
Gemini Enterprise Agent Platform

Agent Platform runs the employee-support agents: identity-bound reasoning, cross-system root cause, governed actions into ITSM/HRMS/AD.

Customer Engagement Suite (GECX)

Not typically in scope — employee support sits outside the contact-centre domain. If the GCC also runs customer CC operations, GECX leads that track.

Tilicho Labs — communications & implementation

Tilicho Labs provides the conversational execution layer, integrates ITSM/HRMS/IdP and the entitlement catalog, and co-builds the GCC's agent-operations CoE.

Human oversight

Managers approve in-flow; sensitive HR matters route to HRBPs; the CoE governs every agent the centre ships.

Customer & employee impact

Customers: Employees get answers and actions in minutes, in their language, in one thread — onboarding week feels like the company works.

Employees: L1 teams shift from reset factories to agent-operations roles; HRBPs and leads work judgment cases, not inboxes.

Value drivers · differentiators
L1 cost collapse on automatable volumeElapsed-time (not just SLA) improvementUpstream defect eliminationFollow-the-sun coverage without staffingGCC charter expansion into AI operationsOne governed layer across IT, HR, finance, and facilitiesLeast-privilege actions with full audit vs shared-inbox opacityThe GCC as builder-operator: same platform serves the global enterpriseMultilingual workforce support in one deployment
Operating-model comparison

Conventional vs point solutions vs agentic

Thirteen dimensions where the operating models differ — from experience and speed to governance and measurement. Point solutions improve one channel; the agentic layer changes how the whole enterprise communicates.

Conventional: Queue, IVR maze, repeat yourself at every step

Point solutions: One channel improves; experience breaks at its edges

Agentic: Recognized, understood, and resolved in the customer's language on any channel

Who you'll talk to

Every stakeholder, one coherent story

GCC Site Leader / Head

Cares about: Cost per ticket, charter expansion

Wants: Lower unit costs and a new AI-operations mandate

Will object: Automation shrinks my headcount story

Proof that works: Charter-growth narrative: fewer L1 FTEs, new agent-ops roles

“The GCCs winning new mandates are the ones running the enterprise's AI operations. Is that your charter yet?”
Global CIO

Cares about: Standardization across regions and towers

Wants: One governed agent layer instead of tool sprawl

Will object: Every region bought its own chatbot

Proof that works: Consolidation architecture + governance model

“How many conversational tools does your enterprise run today, and who governs them?”
Shared Services / Ops leader

Cares about: SLA, ticket backlogs, attrition

Wants: L1 resolution in seconds, humans on L2/L3

Will object: Our processes are too bespoke

Proof that works: Process-mining audit of their real ticket data

“What share of last quarter's tickets were password resets and status checks?”
CHRO

Cares about: Employee experience scores

Wants: Instant, consistent HR answers in every language

Will object: HR needs a human touch

Proof that works: Escalation design: sensitive matters route to HRBPs immediately

“Your people wait two days for answers that exist in your policy documents.”
Security & Risk

Cares about: Access control, data leakage

Wants: Role-scoped agents with full audit trails

Will object: An agent with system access is an attack surface

Proof that works: IAM design review: least-privilege tool permissions, logged actions

“Every agent action is identity-bound, permission-scoped, and logged — unlike your shared-inbox workflows today.”
Architecture

The same layers, grounded in your systems

Channels and industry connectors are partner-built; the agent platform and models are Google Cloud; your systems of record and policies remain yours.

Gemini Enterprise Agent Platform

Enterprise Intelligence & Agents

Google Cloud provides the intelligence: agents that reason over policies, history, and enterprise data, coordinate specialized agents, and execute governed actions — running in the customer's Google Cloud environment.

Gemini reasoning & intentEnterprise grounding with citationsDomain & workflow agentsMulti-agent orchestrationEnterprise-system actionsPolicy enforcement & model routing
1Contact

Interaction arrives on any channel — or the enterprise initiates outreach

2Identify

Identity and permissions resolved; consent and policy windows checked

3Understand

Intent understood in the customer's language, with full context retrieved

4Reason

Agent reasons over policies, history, and enterprise data

5Act

Governed actions executed in systems of record — payments, bookings, tickets, updates

6Escalate

Humans brought in on sentiment, complexity, or policy triggers — with full context

7Record

Outcome written back; 100% of the interaction logged and auditable

8Improve

Every interaction evaluated; policies, prompts, and workflows refined

Economics

Model it with your numbers

Defaults reflect typical global capability centres interaction profiles — replace them with yours. Every formula is shown; the pilot proves the containment rate before any scale decision.

Your inputs
120K
6 min
$0.55
$0.08
55%
$250K
Modelled impact
$231K
monthly cost savings
1.1 mo
payback period
$8.1M
three-year net value
66K
interactions resolved by agents / month
Sensitivity — containment ±15 points
$196K
$267K
monthly savings range across containment scenarios
Assumptions & formulas (no hidden numbers)
  • Baseline cost = interactions × minutes × human $/min
  • Contained interactions cost AI $/min only; escalated interactions incur AI cost + 60% of human handle time (triage saves the rest)
  • No revenue uplift modelled for this scenario
  • Containment is the pilot's job to prove — the sensitivity band shows the stakes. These are modelling defaults, not claims.
Security & regulatory

Designed for your regulatory reality

Least-privilege agent permissions bound to the requesting employee's entitlements
Cross-border employee-data handling per region (GDPR, DPDP, local labor law)
Sensitive HR matters (grievances, health, performance) always route to humans
Full audit trail of every automated action against ITSM/HRMS/ERP
The pilot

Narrow scope. Real traffic. Explicit thresholds.

Scope · 6–10 weeks

IT L1 + HR policy support for one business unit or region, chat + voice, English + one language

Integration boundary
ITSM (ServiceNow or equivalent)HRMS (read + leave actions)SSO / directoryKnowledge sources
Success is measured as
  • L1 resolution rate
  • Mean time to resolution
  • Ticket deflection
  • Employee satisfaction
  • Cost per resolved contact
Expansion roadmap

One pilot, then the platform

1
All towers (finance, procurement)
2
Onboarding orchestration
3
Global rollout
4
Agent-building CoE serving business units
5
Customer-facing agents operated by the GCC
Common questions

Asked in every meeting