Cognizant has launched Cognizant Secure AI Services, an integrated offering designed to help enterprises secure, govern, and scale AI and agentic systems across their operations. The service is built on three foundations: a secure Agent Development Lifecycle (ADLC), Cognizant Neuro Cybersecurity as a consolidated control plane, and a Responsible AI layer delivered through Cognizant Trust. The goal is to move enterprises from assumed trust toward "provable trust" — an approach grounded in evidence, traceability, and continuous assurance.
What it does
Cognizant Secure AI Services addresses security, governance, and runtime risks that traditional cybersecurity models were not designed to handle. Traditional security was built for deterministic software; AI systems are probabilistic and context-driven, and can be manipulated in ways legacy tools were never designed to detect. Manipulated models, poisoned prompts, and corrupted agent behavior can trigger confidently wrong actions at scale.
The offering engineers trust twice: first at build time, by securing models, data, and pipelines before deployment; and then at runtime, by monitoring AI behavior in production to detect manipulation, manage and mitigate unsafe actions, and preserve audit-supporting evidence.
The three foundations
- Secure Agent Development Lifecycle (ADLC) — embeds protection across design, build, test, deploy, and change of AI systems.
- Cognizant Neuro Cybersecurity — a consolidated control plane that unifies AI and enterprise signals for threat response, correlation, and audit-supporting evidence.
- Responsible AI (Cognizant Trust) — a continuous trust and assurance layer providing traceability, policy enforcement, and compliance alignment based on client-defined requirements as AI systems scale.
Together, these capabilities span model security, data protection, AI DevOps security, identity and access management, agent behavior controls, and generative AI risk management.
Enterprise context
Cognizant is already working with 250+ global enterprises across regulated industries to assess, secure, and operationalize digital transformation programs, including AI deployments. Early engagements address risks such as deepfake-driven fraud, model tampering, securing autonomous agents, and generative AI systems operating across enterprise workflows. The engagements also establish governance and audit frameworks required to scale AI responsibly in regulated environments.
Vishal Salvi, Global Head of Cognizant's Cybersecurity Service Line, stated: "AI is fundamentally changing how enterprise systems behave. These systems are adaptive, context-driven and increasingly autonomous – and securing them requires continuous assurance across build and run-time environments."
Arjun Chauhan, Practice Director at Everest Group, noted a growing need for unified frameworks that address risks across both the build phase and the run-and-operate lifecycle, and for integrating best-of-breed technologies into a cohesive, operationalized model.
Tradeoffs
Cognizant Secure AI Services is an enterprise-grade offering, not a lightweight tool. It requires integration with existing enterprise security stacks and likely a significant consulting engagement. The service is designed for regulated industries (finance, healthcare, energy) where compliance with frameworks like NIST AI 100-1 is mandatory. Smaller organizations or those with less mature AI deployments may find the scope and cost prohibitive.
Bottom line
Cognizant Secure AI Services provides a structured, audit-ready approach to securing AI and agentic systems in enterprise environments. For CISOs and compliance officers facing boardroom mandates to scale AI while maintaining SOC-2 audit trails, this offering bridges the gap between AI ambition and regulatory reality.