Cognizant has launched a new offering aimed at helping enterprises secure and manage the growing complexity of AI-driven and agentic systems. Evolving alongside the demand for AI-driven business growth, the company’s Secure AI Services platform works as a foundational layer that equips organizations with the necessary governance, security measures, and operational control as AI deeply integrates into the fabric of their business processes and decision-making.
For instance, these rapidly advancing AI features will allow AI agents not only to interact with customers and to perform routine tasks but also to access and manipulate business-critical content in a completely automated way. This new kind of AI can offer tremendous leverage in productivity but will also generate types of cyber risks that conventional security models have no answers for.
Cognizant said its new service focuses on establishing “provable trust” in AI systems through continuous monitoring and evidence-based assurance. Rather than relying on traditional static defenses, the platform is built to secure AI systems during both development and real-world deployment. The company noted that modern AI systems are probabilistic and context-aware, making them vulnerable to threats such as manipulated prompts, poisoned models, and compromised agent behavior.
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“AI is fundamentally changing how enterprise systems behave,” said Vishal Salvi, Global Head of Cognizant’s Cybersecurity Service Line. “These systems are adaptive, context-driven and increasingly autonomous – and securing them requires continuous assurance across build and run-time environments. With Cognizant Secure AI Services, we are helping enterprises engineer trust into AI systems from day one and to sustain that trust as those systems evolve.”
The offering combines three major components: a secure Agent Development Lifecycle (ADLC) framework, Cognizant Neuro® Cybersecurity for unified threat monitoring and audit support, and Cognizant Trust™, which provides policy enforcement, traceability, and responsible AI governance.
All these features together aim to cover the entire operational lifecycle for AI model security, data protection, identity management, AI DevOps security, and generative AI risk mitigation.
Based on Cognizant, they are currently helping over 250 companies in regulated industries to carry out AI security and digital transformation projects. Some of the first implementation examples include protection against deepfake fraud, model tampering, and risks related to autonomous AI agents operating within enterprise systems.
Research analysts working in the industry point out that businesses are looking more and more for integrated AI security systems that not only cover development but also operational environments. With the rapid spread of AI, there is a rising need for governance models that are capable of securing complex AI ecosystems while at the same time allowing for compliance and transparency.