AI IN ACTION
We were our own first AI Builder client
Before we engineer AI for clients, we engineer it for ourselves. Cognizant is Client Zero: developer productivity up ~70% over 18 months, 80% productivity gains in contract work, 30% of help desk requests deflected by agentic AI and HR query resolution down from 30 minutes to ~5 seconds. This is what our AI Builder approach looks like in practice—and it's what we bring to you.
Cognizant tackles AI complexity—with powerful results
Cognizant’s OneCognizant platform shows how multi-agent AI can simplify work, reduce complexity and scale AI across the enterprise. Read more.
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<h3>Why AI-driven transformation is important to us</h3> <h5><span class="text-regular">From reshaping consumer behavior to transforming the ways we work, AI is accelerating momentum and driving new types of growth. At Cognizant, we continuously architect what it means to be a modern business in the age of evolving tech. So we put that research to work on ourselves.</span></h5> <h5><span class="text-regular">Like our clients, we faced the hard part—moving AI innovation into a governed, scaled operation, always exploring how to bridge the gap from investment in AI to deriving enterprise value from AI. Like you, we’re navigating AI-driven disruption and the opportunities it creates across investment strategy, operations and the workforce.</span></h5> <p> </p>
<h3>Our roadmap to the agentic enterprise</h3> <p>We believe the AI journey for most enterprises is progressing along three interconnected vectors. Most businesses will mature in each of these vectors simultaneously rather than in linear, successive order:</p>
Vector 1: Enabling hyperproductivity
Software development productivity
- Apply AI to software cycles to increase productivity
- Productivity gains are reinvested toward corporate growth
- These savings fund innovation projects powered by agentic AI
Vector 2: Industrializing AI
Migration to the agentic layer
- Move business logic from traditional software-as-a-service (SaaS) layer into a SaaS-native or custom agentic layer
- Agents integrate with human capital and structured/unstructured data, creating larger areas of opportunity
- Development is outcome- and behavior-driven, iterative and requires ongoing supervision
Vector 3: Agentifying the enterprise
Unlocking new labor pools
- Agentic layer is a multiplier to the software layer
- Combining agentic capital and human capital can create new outsourcing cycles
- Example: Customer care transformed into a 65–35 agentic-to-human model
OUR JOURNEY
<h3>How we built it—and continue to build</h3> <p>We worked through all three vectors deliberately. For each, we asked how to stay ahead of client needs and fuel innovation while managing demand, frameworks and architecture. And we weighed the human side too—how to engage and support our associates, and how AI would reshape our structure and the way we work.</p>
- People
- Operations
People
Empower our people
We reimagined our workforce, collaborating across the business to transform how we work, how we build:
- 50K participation in Vibe Coding event
- Innovation and advanced AI labs
- 50K+ certified via L&D and upskilling
- Centralized AI hub and and resource
Operations
Drive higher levels of productivity
We continue to leverage AI analytic capability for real-time information, decision-making and risk mitigation:
- 256 use cases completed enterprise-wide, 10+ new agents deploying monthly
- 67% drop in major incidents over 15 months
- Business process and context engineering
- Agent development lifecycle
- Secure multi-agent architecture
- ISO 42001 certification
<h3>Deploying key function-specific agents</h3>
We implemented a gen AI value realization framework to measure progress
LESSONS LEARNED
Five hard-won insights
<p>We’re continuously learning and adapting to change on our AI transformation journey. Here are a few key lessons learned that you can use to shape your AI initiatives:</p>
