Microsoft AI is changing what sits between a Cognizant delivery leader and the decision they need to make. With more than 350,000 associates, over 10,000 projects and 2,000-plus customers, scale has long been both Cognizant’s strength and its pressure point. Few functions feel that scale more acutely than Delivery Excellence (DEx), whose leaders are responsible for quality, governance and consistent execution across thousands of customer engagements.
Using Microsoft AI Foundry, Azure AI services and Microsoft 365 Copilot, Cognizant is reimagining how those leaders work.
A few years ago, much of a DEx leader’s day disappeared into finding the right version of a process document, pulling service-level data out of an incident system or re-reading a statement of work before a client call.
“That work is not intellectually demanding, but it interrupts deeper thinking and client focus,” says Pandiyan Adiyapatham, Assistant Vice President, Business CIO, Delivery Excellence at Cognizant.
Promise: Re-architecting the function at scale
Pandiyan and his team saw an opportunity to redesign how DEx work gets done, moving leaders from finding information to acting on it. “What changed was the work between the systems and the delivery leader,” he says.
Cognizant’s core systems remain in place, but AI now handles reading documents, reconciling data, surfacing risks and preparing drafts for the team to review. The agent ecosystem powers retrieval, reasoning and workflow orchestration while embedding these experiences directly into familiar tools such as Teams, Outlook, Word and Excel.
Proof: A constellation of agents at work
Behind the scenes, a network of agents connects delivery, audit and knowledge workflows.
The ‘delivery layer’ monitors live projects that track contract obligations, predict risks and analyze client sentiment. The ‘audit layer’ supports assurance, reviewing commitments and drafting corrective actions before assessments begin. The ‘knowledge and innovation’ layer turns institutional memory into a reusable asset, surfacing relevant project context and insights in real time.
“It would be humanly impossible to track all these signals — delivery, risk and customer sentiment — simultaneously. That’s where AI becomes powerful,” explains Pandiyan.
Guardrails are built into every workflow: zero-trust access, fine-grained permissions, and full auditability within a controlled Azure environment, with continuous feedback loops improving output quality.
Productivity: How course correction helped
The clearest signal is time and adoption.
The platform saw rapid adoption, growing from 6,700 users in its early rollout to more than 8,000 users as of June 2026. “People found it useful and brought others in,” Pandiyan says. “Agents became infrastructure quietly, which signals genuine utility rather than compliance.”
The biggest surprise wasn’t accuracy, but ownership. “The anticipated worry had been whether the agent would get it right, but the real friction turned out to be ownership. The question became who is accountable when the agent drafts and the assessor approves.” The debate reinforced human accountability for final decisions.
The knowledge maturity assessment agent, for instance, has a 42 percent recommendation acceptance rate. “That is not a failure metric,” Pandiyan says. “It’s the governance model working as intended.”
For Cognizant, the outcome is a fundamental shift in how leaders spend their time, focusing more on customers, risk management and business decisions.
Frontier Employee
“Reviewing every statement of work took time and sometimes a commitment could slip through. Now the agent securely extracts and tracks SOW obligations and presents them in a format that makes them easier to review and assess. I still make the final decision, but I can do it faster and with greater confidence.”
L. Vedavalli, Director-Delivery Excellence, Cognizant