Capgemini: Engineering the Agentic Future

Capgemini: Engineering the Agentic Future

The AI Adoption Explosion

The adoption of Generative AI has moved from early experiments to mainstream implementation at a breathtaking pace. This foundational shift is now paving the way for the next frontier: AI Agents.

Gen AI Is Now Mainstream

30%

of organizations have deployed Generative AI at scale in 2025, a fivefold increase from just 6% in 2023.

AI Adoption at Scale (2025)

Unlocking Tangible Value

Initial concerns about ROI are fading as enterprises witness substantial returns. AI is not just a technological marvel; it's a proven engine for efficiency and growth, delivering significant cost savings across core business functions.

Average Return on AI Investment

AI-Driven Cost Savings by Function

The Rise of the AI Teammate

The future of work involves deep collaboration between humans and AI. By 2028, a significant portion of organizations expect AI agents to be integral members of their teams. However, this human-AI chemistry hinges on trust, a factor that is declining for fully autonomous systems, highlighting the need for careful governance.

AI Agents as Team Members

38%

of organizations will have AI agents as team members within human teams by 2028.

Trust in Fully Autonomous AI Agents

Capgemini's AI Implementation Framework

To turn ambition into measurable impact, Capgemini provides a sequential approach to conceptualize, structure, and implement successful AI-driven transformations, ensuring value creation is anchored in strategy.

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1. Strategy

Shape the vision and strategic roadmap grounded in business priorities.

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2. Value Identification

Identify and prioritize high-impact use cases and ecosystem partners.

🛠️

3. Delivery & Scaling

Deliver proofs of concept and scale solutions across the enterprise.

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4. Transformation

Transform people, culture, and processes to maximize human-AI collaboration.

The Bedrock of Trust: An Ethical Framework

Capgemini believes human values must never be undermined by AI. Their Code of Ethics for AI is built on seven core principles to ensure solutions are human-centric, trustworthy, and beneficial to society.

Human Benefit

Designed with a clearly defined purpose to benefit humanity.

Sustainable

Mindful of environmental and societal impact for all stakeholders.

Fair & Inclusive

Produced by diverse teams to ensure unbiased and inclusive outcomes.

Transparent

Outcomes can be understood, traced, and audited as appropriate.

Controllable

Enables humans to make informed choices and retain the final say.

Robust & Safe

Includes fallback plans and ensures reliability and security.

Privacy Aware

Considers data privacy and security from the initial design phase.

Accountable

Maintains clear accountability for the system's operations and decisions.

Capgemini AI Research Synthesis | 2025

The Agentic Awakening: A Capgemini Chronicle of the AI Revolution
Chapter 1: The New AI Frontier: The Fading of Hype, the Rise of the Agent The narrative of artificial intelligence has, for years, been one of immense promise, often veiled in abstract concepts and pilot projects. But a new chapter is unfolding, one that moves beyond the speculative to the

Detailed Research Report

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A Research Compendium on the AI Ecosystem: The Symbiotic Relationship Between Academic Foundation and Commercial Trajectory

I. Executive Summary: The AI Ecosystem at a Glance   The following report provides a detailed analysis of the artificial intelligence (AI) landscape, tracing its roots from foundational academic research to its contemporary manifestation as a global, multi-trillion-dollar industry. The analysis is structured to demonstrate the profound, enduring influence of pioneering

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