Enterprises are spending heavily on AI, yet measurable returns remain hard to prove. Cognizant AI Nexus aims to close that gap by linking AI costs, quality, workflows and governance in one operating layer.
Enterprises have invested heavily in artificial intelligence, but proving what that spending delivers remains a challenge. Cognizant’s research found that two-thirds of Global 2000 leaders had yet to show measurable productivity gains from AI. One in four had paused or abandoned deployments.
Now, Cognizant is introducing Cognizant AI Nexus, a modular operating layer designed to help businesses track AI spending, govern quality and measure results across teams.
The launch points to a growing enterprise concern: choosing a powerful AI model is only part of the job. Businesses also need to know what it costs, how well it performs and whether it delivers measurable value.
AI costs are becoming harder to control
The financial pressure is already visible. A Cognizant survey of 250 FinOps leaders found that 72% of organisations exceeded their AI budgets over the past 12 months. In 16% of cases, spending went more than 25% over budget.
The same survey found that 97% of organisations had experienced an AI agent session that went beyond expected cost or activity. For 36%, the impact was material.
These figures show why AI oversight is becoming a practical business issue, not just a technical one. Without clear cost tracking and accountability, scaling AI can create new budget risks.
Five capabilities aim to connect work and oversight
Cognizant AI Nexus brings together five capabilities that enterprises can adopt separately or as a group.
Engage provides a governed workspace built around enterprise knowledge, while Orchestrate is designed to turn business processes into agent-based workflows.
The other three focus on oversight. Reveal tracks AI usage, spending and outcomes. Coach evaluates AI work and helps turn effective practices into shared standards. Route selects models based on quality, cost and control, including options that can keep sensitive workloads within the enterprise.
Together, these capabilities are designed to help businesses monitor changes in cost, quality and speed over time.
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