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August 6, 2025 2 min Meet your data superhero Platform Foundations Thought Leadership
Amit Zavery
Amit Zavery President, CPO, COO, ServiceNow
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AI should be transformative. Too often it’s trapped in the mundane work of flagging fraud patterns, supply chain disruptions, and IT tickets in need of escalation—all without context. The problem isn’t the intelligence; it’s the data. AI stumbles when forced to work with data chaos—fragmented, poorly governed data spread across a disconnected enterprise.
 
That’s what makes ServiceNow’s recent acquisition of data.world so powerful. The company’s technology acts as AI’s “vision corrector,” or data superhero, across the entire ServiceNow AI Platform, automatically mapping relationships between data sets that humans could intuitively connect but systems historically couldn’t.
 
Imagine fraud detection that understands nuances , such as linking an unusually large bank withdrawal with a recent customer call about buying a home, or predictive maintenance that knows a “low inventory” alert is irrelevant if the machine is scheduled for retirement. This is AI working as it should—with appropriate context, lessening the load on human agents.
 
 
Super strength
 
AI that can connect the dots between scenarios and context can be revolutionary, and it’s not just aspirational. It’s happening today, in real-world scenarios.
 
 
Financial services
 
Fraud systems no longer need to choose between sensitivity and accuracy. With data.world’s automated cataloging, AI can cross-reference transactions with customer service histories, external risk feeds, and behavioral patterns—reducing false alarms while effectively detecting intricate fraud.
 
 
Healthcare
 
Clinical AI moves beyond reactive alerts to proactive guidance. By linking electronic health records to staffing schedules, equipment logs, and pharmacy inventories, the platform understands that a medication order isn’t just about dosage. It’s also about whether the patient has transportation to pick up the prescription at a convenient location.
 
 
Manufacturing
 
Predictive maintenance evolves from guesswork to precision. When sensor data automatically connects to supplier timelines and production calendars, AI stops “crying wolf” about parts that won’t be needed and instead focuses on preventing failures that truly matter.
AI that can connect the dots between scenarios and context can be revolutionary, and it’s not just aspirational. It’s happening today, in real-world scenarios.

X-ray vision

Traditional data governance often felt like a giant code library without any comments or documentation. data.world flips the script by:

  • Adding clear labels
  • Making connections obvious
  • Tracking changes over time
  • Flagging unreliable data

This is more than “cleaner data.” It’s data that speaks AI’s language: It’s contextual and actionable.

The organizations winning with AI—identified in the ServiceNow Enterprise AI Maturity Index as Pacesetters—aren’t those with the biggest budgets. They’re the ones that have stopped asking “How fast is our AI?” and started asking “How much does our AI understand?”

How do you escape data chaos and take advantage of everything the agentic AI world has to offer? By following three steps:

  1. Identify one critical AI blind spot.
  2. Map the missing conversations.
  3. Let ServiceNow connect the dots.

Our data solutions give AI X-ray vision to see through your data chaos and into what truly matters.

Ready to remove your AI's nemesis? Find out how ServiceNow can help you put AI to work for people.
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