Cognizant CIO Points To Context-Driven Leadership As The Decisive Factor In Enterprise AI

Enterprise AI is pushing CIOs into a broader leadership role that extends well beyond technology oversight. As organizations scale from pilots to production, success increasingly depends on operating models that reflect how people share context, make decisions, and work together. CIOs must now act as organizational architects, responsible for engineering human understanding at scale so AI can deliver durable enterprise value.

Neal Ramasamy is the Global Chief Information Officer at Cognizant, with prior CIO leadership roles at New York Life Insurance Company and Fidelity Investments, and recent recognition on the Forbes CIO Next list. He said that when it comes to enterprise AI, outcomes are shaped by how effectively leaders connect human behavior, institutional knowledge, and execution.

"AI adoption isn’t about tools or infrastructure. It’s about people, context, and engineering human understanding at scale so organizations can create real enterprise value," said Ramasamy. For him, context is the defining factor behind any successful AI initiative.

• Unwritten intel: He described context engineering as the evolution of traditional process transformation, focused on capturing the informal, human elements of work that rarely appear in documentation. "Process transformation only captures what’s written down. Context engineering focuses on how work actually happens, including the informal decisions and interactions that never make it into documentation, and that missing context is where AI initiatives often break down," he explained. When that context is not intentionally designed and shared, AI systems struggle to operate effectively across real organizational conditions.

• A model with a mission: That emphasis on context carries through to how Ramasamy thinks about model design. Rather than relying on generalized intelligence alone, he argued that enterprise value comes from models built with a clear mission and a deep understanding of their operating environment. "As much as the generic models you can extract off the shelf will give you a lot of intelligence, to get to the next level, purpose-built models are going to be the answer. They also allow you to drive a lot of control and effectiveness."

• Context to capability: He pointed to a practical example inside the service desk to show how context engineering works in practice. "We gave our help desk a very specialized, context-rich set of tools that understand the specific domain. This allowed us to cut down on the noise and deliver high success rates in problem resolution versus things getting turned into tickets that require manual labor," Ramasamy said. It's a process that transforms the AI model from a raw tool into a reliable "enterprise skill" for the organization.

That same thinking shapes his contrarian view on responsible AI. He argued for embedding governance directly into a company’s "core operating DNA," insisting that responsible AI frameworks and global governance standards are not constraints but accelerators, allowing leaders to move faster with confidence.

• A contrarian velocity: "Today, the belief is that you have to be fast and be responsible. We believe something different: we want to move fast through responsibility," noted Ramasamy. "You build trust and adoption in the organization by being explicit about what responsibility means within your company, and then you build that into the execution velocity."

• Dignity and DNA: For Ramasamy, responsible AI is ultimately a human question. When responsibility is embedded into how an organization operates, it shapes behavior, builds confidence, and gives teams permission to engage rather than hesitate. "I believe it’s more about how AI will enhance human dignity, creativity, and help grow character. You move fast through responsibility if you make that part of your core operating DNA."

• The force multiplier: He said that this level of transparency needs to be driven from the top, with executive leadership working to galvanize the entire organization around clear, shared outcomes. For an organization to have credibility, it must first embody these principles internally before offering them to the market. "That level of responsibility and transparency builds a lot of trust because people start seeing the discipline behind the speed," he explained. "That trust becomes the force multiplier. If you just do it for show, people are going to see right through it."

Ramasamy defined the modern CIO's role as owning the organizational intelligence required to make an AI-driven organization effective. "The role of a CIO is no longer just about optimizing technical platforms," he said. "The key to enabling a large organization to succeed is engineering human understanding at scale." While technical components are important, he cautioned that a clear line of separation will emerge, distinguishing leaders who prioritize context from those who focus on infrastructure.

• The art of the possible: The goal is to amplify human potential. "We are here to make our associates better, improve their skill sets, and remove any fear they might have by showing them the art of the possible. Ultimately, the role of technology is to improve human potential, and the faster leaders get it, the easier that becomes."

• Advantage that lasts: That conviction, he said, will ultimately determine which leaders turn AI into durable advantage. "The successful leaders who get that piece, will clearly stand out in the next decade. That level of comprehension, that ability to manage change, the ability to manage intelligence and context, and then build that conviction within the organization will create lasting competitive advantage."

He framed the choice as one of inclusion versus imposition. Leaders who involve the organization from the start create shared ownership, trust, and momentum, while those who build in isolation struggle to earn adoption after the fact. "It’s the difference between bringing the organization together to be part of the solution from day one, versus building something in isolation and simply telling people, 'Now you will use it,'" he concluded. "You want the organization to buy in and be part of the journey."