Cognizant Adopts Anthropic’s Claude to Accelerate Enterprise AI Adoption at Scale and Deploys Claude to Drive Internal AI Transformation

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  Cognizant will use Claude models and agentic tooling in Cognizant platforms to help clients modernize and scale AI adoption.

• Cognizant will provide Claude to up to 350,000 associates across key corporate functions, engineering, and delivery teams, and use Claude Code to accelerate coding tasks, testing, documentation and DevOps workflows.

Cognizant is now using Anthropic’s Claude, one of the world’s most powerful family of large language models (LLMs), to help its enterprise customers and internal teams move from AI experimentation to scaled business outcomes. This combines the Claude family of models and agentic tooling with Cognizant’s engineering platforms and industry blueprints to help deliver measurable impact at enterprise scale.

Cognizant plans to align its software engineering and platform offerings with Anthropic capabilities – including Claude for Enterprise, Claude Code, the Model Context Protocol (MCP), and the Agent SDK – so clients can integrate AI with existing data and applications, orchestrate multi-step work with human oversight, and more effectively manage performance, risk and spend.

Enterprises adopting AI at scale need solutions that integrate with existing systems and deliver tangible outcomes. Cognizant’s use of Claude aims to help clients move faster from pilot to production and scale AI capabilities across the enterprise. Cognizant will also provide Claude internally to associates across key corporate functions, engineering and delivery teams to enhance productivity and advance AI maturity.

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“Enterprises are moving beyond simple productivity gains toward a more connected, agentic future,” said Ravi Kumar S, CEO of Cognizant. “By pairing Anthropic’s Claude models and agentic tooling with Cognizant’s suite of platforms and industry expertise, we will help clients build the foundations of an agentified enterprise where intelligent systems collaborate with people to accelerate modernization, engineering and industry transformation. We are equally excited to apply Anthropic’s technology to help us drive these transformation goals internally at Cognizant.”

“The combination of frontier AI with deep domain expertise and implementation capabilities is what makes this partnership so exciting and will absolutely accelerate AI in the enterprise,” said Paul Smith, Chief Commercial Officer at Anthropic. “Companies require trusted AI that combines cutting-edge performance with safety and reliability, which is why hundreds of thousands of businesses trust Claude. We’re demonstrating this at scale by rolling out Claude to up to 350,000 Cognizant employees and helping our joint clients do the same.”

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Initial focus areas for the partnership include:

• Software engineering productivity: Deploying Claude and Claude Code with Cognizant Flowsource Platform to accelerate coding tasks, testing, documentation and DevOps workflows with MCP-based access to developer tools.
• Legacy modernization: Combining Cognizant’s modernization frameworks with Anthropic’s code understanding and transformation capabilities to speed analysis and refactoring across large codebases.
• Agentification: Using Cognizant Neuro^® AI Multi-Agent Orchestration and Anthropic’s Agent SDK to design reusable, domain-specific agents and multi-agent systems that operate with explicit policies, approvals and human-in-the-loop controls.
• Industry solutions: Developing vertical solutions, beginning with Financial Services, leveraging Cognizant Agent Foundry with Claude to embed agentic workflows into regulated, enterprise environments.
• Responsible AI: Advancing practices for safe deployment, monitoring, and operations at scale, aligned to enterprise governance needs and open standards such as MCP.

Cognizant plans to engage clients through workshops, reference patterns, and platform integrations using Claude to help teams identify high-value use cases and move them into production to enable measurable outcomes.