Cognizant is doubling down on the future of enterprise AI with an ambitious plan to deploy 1,000 context engineers over the next year, in a move it calls a “pivotal investment” in the emerging discipline of context engineering. The initiative is paired with a strategic partnership with Workfabric AI, the company behind the ContextFabric platform, to help enterprises move from AI experimentation to large-scale deployment.
At the heart of this effort is context engineering, which Cognizant describes as the key to making AI agents capable of reasoning, acting, and adapting in alignment with enterprise objectives. ContextFabric provides a continuous runtime grounding layer that transforms workflows, data, rules, and processes into actionable context for AI systems—essentially giving AI the ability to operate with an understanding of a company’s goals and constraints.
“In the microprocessor era, the lever was code. In the cloud era, it was workload migration. In the LLM era, the lever is context,” said Ravi Kumar S, CEO of Cognizant, emphasizing the central role context will play in unlocking enterprise value from AI.
Through this partnership, Cognizant plans to arm its engineers with ContextFabric tools and training, enabling them to turn a company’s operating models, governance systems, policies, and institutional knowledge into a dynamic, AI-ready knowledge base. The goal: to move clients beyond proof-of-concept projects and into scalable, enterprise-grade AI adoption.
Applauding the initiative, Rohan Murty, CEO of Workfabric AI, called it a bold step for the industry, adding that “ContextFabric will be the force multiplier that turns this vision into reality, enabling engineers to deliver trusted, enterprise-grade outcomes.” Murty also pointed to proven results from existing enterprise deployments, noting 3X higher accuracy, 70% fewer hallucinations, faster deployment cycles, and stronger ROI as key benefits already being seen in the field.
With this investment, Cognizant signals that context engineering is not just a technical capability but a critical enabler for industrializing agentic AI—turning AI from an experimental tool into a core driver of business transformation.
