Capgemini Agentic AI Enterprise Transformation Action Plan

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CAPGEMINI

Capgemini's Agentic AI Enterprise

Transformation Action Plan

2026–2028 Strategic Roadmap for Enterprise AI, Agentic Operations &

Business Transformation

Strategic foundation

Capgemini's 2026 strategy places agentic AI at the center of its next growth cycle. At its May 27, 2026 Capital Markets Day, the

Group described enterprise agentic AI as a business-transformation journey requiring modernized technology, data and AI

foundations, governance, a new agentic technology stack, and new ways for humans and AI agents to operate together at scale.

Capgemini's strategy is supported by its OpenAI Frontier Alliance, Google Cloud AI Enterprise Hub, Outcome Deployed Engineers

and Intelligent Operations capabilities.

2026–2028

+5.5% to +7.5%

€6B+

strategic horizon

AI-driven value pools

2025–2028 revenue CAGR

ambition

cumulative organic FCF ambition,

2026–28

Transformation logic:

modernize technology debt

→

establish agentic technology foundations

→

create an agentic control plane

→

agentify products and services

→

agentify enterprise operations

→

measure business outcomes.

Integrity note:

This document is a research-based strategic synthesis of Capgemini's public 2026 strategy and announcements. It is not an official Capgemini

action-plan publication and does not imply that every recommended implementation step has been formally adopted by Capgemini.

Capgemini Agentic AI Enterprise Transformation Action Plan

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1. Strategic Objectives

Move from AI experimentation to enterprise execution:

Help clients progress from isolated pilots to production AI embedded in

core workflows.

Modernize technology debt:

Use AI-enabled engineering to accelerate modernization that is a prerequisite for enterprise-scale

agentic AI.

Build the agentic technology stack:

Prepare cloud, data, applications, integration, security and infrastructure for agent-based

workloads.

Establish an agentic control plane:

Provide governance, orchestration, monitoring and policy controls for an AI-agent workforce.

Agentify products and services:

Apply agents, AI-native engineering and physical AI to R&D;, product development and intelligent

industry.

Agentify enterprise operations:

Transform business processes and Intelligent Operations using coordinated AI agents and human

oversight.

2. 2026 AI Transformation Streams

•

Enterprise-wide AI execution:

move client programs toward production and measurable business value.

•

Foundations:

strengthen data, infrastructure, governance, cybersecurity and trust.

•

Human–AI collaboration:

redesign operating models around appropriate division of work between people and agents.

•

External delivery ecosystem:

use hyperscaler and AI-model partnerships to accelerate deployment.

•

Internal adoption:

use agentic platforms to transform Capgemini's own HR, finance, marketing, procurement and other operations.

3. Current Strategic Partnerships

•

OpenAI Frontier Alliance:

Capgemini became a founding member in February 2026 to address business, data, organizational and

systems-integration requirements for enterprise AI.

•

Google Cloud AI Enterprise Hub:

announced April 2026; Outcome Deployed Engineer teams work directly with clients and

Google Forward Deployed Engineers to build production-ready agents around real workflows.

•

OpenAI Deployment Company:

Capgemini announced an investment in May 2026 to strengthen enterprise deployment

capabilities.

Capgemini Agentic AI Enterprise Transformation Action Plan

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4. Five AI-Driven Value Pools

Value pool

Action focus

1. Technology-debt modernization

Accelerate modernization of legacy estates so enterprises can support AI at

scale.

2. Agentic technology stack

Reset enterprise technology environments for AI agents, data, integration and

automation.

3. Agentic control plane

Govern and orchestrate the agentic workforce with appropriate security, policy

and oversight.

4. Agentification of products &

services

Transform R&D;, product design, engineering and intelligent-industry workflows.

5. Agentification of enterprise

operations

Apply agentic AI to finance, customer operations, supply chain, HR and other

business processes.

5. Enterprise Implementation Architecture

•

Assess:

identify high-value processes, technology debt, data readiness and agent opportunities.

•

Prepare:

modernize platforms, data, identity, security, integration and governance foundations.

•

Design:

define agent roles, tools, permissions, escalation rules, human oversight and success measures.

•

Deploy:

use Outcome Deployed Engineer teams and domain specialists to build production-ready workflows.

•

Operate:

monitor reliability, cost, security, quality and business outcomes continuously.

•

Scale:

replicate proven agent patterns across functions, geographies and business units with governance controls.

6. Intelligent Operations & WNS

Capgemini's WNS acquisition strengthens its Intelligent Operations position and provides a large operations base through which

agentic AI can be applied to business processes. Capgemini reported strong Q1 2026 traction in Intelligent Operations and said the

acquisition reinforces its ability to pursue AI transformation projects at scale.

Capgemini Agentic AI Enterprise Transformation Action Plan

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7. Timeline & Milestones

Period

Milestone

Feb 23, 2026

Capgemini joins OpenAI Frontier Alliance as a founding member.

Apr 23, 2026

Capgemini announces Google Cloud AI Enterprise Hub and Outcome Deployed Engineer

model.

Apr 30, 2026

Q1 reporting identifies enterprise AI execution, foundations and human–AI collaboration as

2026 priorities.

May 12, 2026

Capgemini announces investment in the OpenAI Deployment Company.

May 27, 2026

Capital Markets Day establishes 2028 strategic direction centered on agentic AI enterprise

transformation.

2026–2028

Scale agentic transformation across technology modernization, products/services and

enterprise operations while pursuing the Group's 2028 ambitions.

8. KPI & Performance Framework

AI bookings:

Track the contribution of generative and agentic AI to Group bookings; Capgemini reported >11% of Q1 2026 bookings

from generative and agentic AI.

Production deployments:

Count client AI/agent deployments reaching production and sustained operation.

Time-to-value:

Measure time from use-case selection to production deployment and measurable outcome.

Modernization throughput:

Track applications, data estates and technology components modernized to support AI.

Agent reliability & safety:

Monitor accuracy, escalation, security, policy compliance and operational incidents.

Business value:

Measure revenue, cost, cycle time, quality, customer experience or productivity outcomes by engagement.

Workforce readiness:

Track AI-native skills, Outcome Deployed Engineers and practitioner upskilling.

Capgemini Agentic AI Enterprise Transformation Action Plan

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9. Governance, Responsible Teams & Operating Model

•

Group leadership:

strategic direction, investment priorities and enterprise transformation governance.

•

Strategy & transformation teams:

business-case development, operating-model design and value realization.

•

Data & AI teams:

model, agent, data and AI-platform architecture.

•

Cloud & technology engineering:

modernization, integration, infrastructure and production engineering.

•

Cybersecurity & trust:

identity, access, data protection, AI governance and risk controls.

•

Intelligent Operations:

process transformation, operations redesign and agent-enabled delivery.

•

Outcome Deployed Engineers:

embedded client-facing teams that build and deploy agents around real business workflows.

•

Technology ecosystem:

OpenAI, Google Cloud and other partners provide platforms and specialized capabilities.

10. Risks & Mitigation

Risk

Exposure

Mitigation

Legacy technology

debt

Old applications and integration

constraints can slow AI deployment.

Prioritize modernization around high-value AI use

cases.

Data quality & access

Poor data foundations can limit agent

reliability.

Improve data governance, lineage, quality and

controlled access.

Agent governance

Autonomous systems introduce

permission, security and

accountability risks.

Use an agentic control plane, identity controls,

monitoring and human escalation.

Operating-model

resistance

AI changes roles and workflows.

Redesign processes with human–AI collaboration

and workforce training.

Value uncertainty

Pilots may not translate into

measurable business outcomes.

Require explicit value hypotheses, baselines and

outcome tracking.

Platform

fragmentation

Different models and cloud platforms

can increase complexity.

Use common architecture patterns, interoperability

and governance.

11. Action-to-Impact Chain

AI strategy

→

technology/data readiness

→

governed agentic architecture

→

production deployment

→

redesigned human–AI

workflows

→

measurable business outcomes

→

scaled enterprise transformation.

Capgemini Agentic AI Enterprise Transformation Action Plan

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12. 2028 Strategic Outcome Framework

Outcome

Strategic contribution

Enterprise AI scale

Shift client programs from experimentation toward production-scale, enterprise-wide AI

execution.

Modernized technology

estate

Accelerate reduction of technology debt that constrains AI adoption.

Governed agentic

workforce

Establish controlled orchestration and governance for enterprise AI agents.

AI-native products &

services

Expand agentic capabilities across R&D;, engineering and intelligent-industry offerings.

Agentified operations

Apply AI agents to repeatable enterprise processes with human oversight where

appropriate.

Client value creation

Tie AI deployment to measurable business outcomes rather than model deployment

alone.

13. Verified 2028 Financial Ambitions

Capgemini's May 2026 Capital Markets Day set a 2025–2028 constant-currency revenue CAGR ambition of

+5.5% to +7.5%

, with

approximately two percentage points from M&A; an Operating Profit before acquisition-related expenses target of

12.1%–12.3%

revenue by 2028; and cumulative organic free cash flow of

more than €6 billion

over 2026–2028.

These are Capgemini Group financial ambitions, not KPIs for an individual client agentic-AI implementation. They are included to

distinguish corporate strategy from project-level operating metrics.

14. Research Basis & Fact-Checking Notes

• Capgemini's May 27, 2026 Capital Markets Day is the primary source for the five AI-driven value pools and 2028 strategic direction.

• Capgemini's April 23, 2026 Google Cloud AI Enterprise Hub announcement supports the Outcome Deployed Engineer model.

• Capgemini's February 23, 2026 OpenAI Frontier Alliance announcement supports the enterprise AI deployment strategy.

• Capgemini's May 12, 2026 OpenAI Deployment Company announcement supports its expanded enterprise AI deployment

positioning.

• The document does not repeat unsupported claims that Capgemini has already deployed a fixed number such as 250 AI agents

across clients; client deployments vary by engagement.

Prepared as a research-based strategic synthesis | Information checked against public Capgemini materials available through September 16, 2026 | Not an official

Capgemini publication.

Capgemini's Agentic AI Enterprise Transformation Action Plan

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