Louis DiModugno, Global Chief Data Officer at Verisk and former U.S. Air Force Colonel, builds AI-ready data foundations across 40+ petabytes. He talks about embedding AI into core insurance products, tackling unstructured data and deepfakes, and shifting from governance to observability. Short, practical takes on scaling AI responsibly in a highly regulated industry.
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insights INSIGHT
Joining Verisk Multiplied His Industry Impact
Moving from single-carrier roles to Verisk allowed Louis to scale impact across the entire insurance ecosystem.
At Verisk he leverages prior CDO learnings to influence carriers, regulators, and industry AI adoption.
insights INSIGHT
Verisk Runs A 40+ Petabyte Insurance Repository
Verisk manages over 40 petabytes of longitudinal insurance data contributed by carriers.
They perform entity resolution at individual and commercial levels to benchmark and share insights back with contributors.
volunteer_activism ADVICE
Compare New Feeds To Historical Submissions
Validate incoming carrier feeds by comparing each submission to that contributor's historical shipments to detect noise or drift.
When discrepancies appear, collaborate with the carrier to correct or explain the data before use.
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Discover how enterprise AI and data strategy are operationalized at scale in one of the most highly regulated industries in the world. Louis DiModugno, Global Chief Data Officer at Verisk, shares how he builds AI-ready data foundations across 40+ petabytes of insurance and risk data, and the best practices behind embedding AI into enterprise products. He discusses unstructured data, deepfakes, and the shift from governance to observability, offering practical insights for data leaders scaling AI responsibly.
Key Moments:
From Military Leadership to Chief Data Officer: Data Integrity as a Competitive Advantage (03:02): Louis shares how his experience as a U.S. Air Force Colonel has shaped his approach to data governance, data quality, and enterprise AI leadership. He explains why integrity, service, and operational excellence are essential foundations for modern CDOs building trusted, decision-ready data environments.
Building AI-Ready Data Foundations at a 40+ Petabyte Scale (17:13): Managing more than 40 petabytes of insurance and risk data, Louis breaks down how Verisk transforms complex, multi-source data into AI-ready infrastructure. From entity resolution and master data management to benchmarking and predictive analytics, he outlines what it takes to prepare enterprise data for AI and advanced analytics at scale.
Designing an AI-First Data Strategy for Enterprise Decision Intelligence (20:00): Louis breaks down how Verisk evolved toward an AI-first data strategy across more than 150 insurance and analytics products. Rather than treating AI as an add-on, he explains how embedding AI into core workflows enables smarter underwriting, pricing, regulatory reporting, and risk management. He also discusses the strategic role ThoughtSpot plays in delivering natural language search, embedded analytics, and scalable AI-driven decision making.
AI Fraud, Deepfakes, and Risk Management in Financial Services (26:11): As AI-generated images and synthetic claims become more sophisticated, Louis discusses how the insurance industry is combating deepfake fraud and AI-driven manipulation. He shares best practices around AI risk management, vendor partnerships, and regulatory collaboration to protect policyholders and maintain trust.
Unstructured Data and AI: Why Governance Still Matters (29:28): Louis explores how expanding beyond structured data is reshaping enterprise AI. He explains why incorporating unstructured data into vector databases, graph models, and knowledge systems can significantly improve model accuracy and decision confidence. At the same time, he emphasizes that stronger governance (or observability as he reframes it) is essential as organizations scale AI across regulated industries.
Key Quotes:
“The more data that you bring to the equation, the more elements that you have in the algorithm, the higher level of accuracy you should be able to reach with your outcomes.” - Louis DiModugno
“I've tried to move away from using the word governance as much as I like to use the word observability, because I really think observability shows more aspects of what it is that we are doing with the data.” - Louis DiModugno
“The underlying aspect of what ThoughtSpot's delivering to them is our insights that not only give them their answer, but also give them insights that maybe they weren't looking specifically for. One of the big benefits of ThoughtSpot is that it's trying to anticipate what you're asking for.” - Louis DiModugno
“We've partnered with ThoughtSpot, which brings AI embedded within its product. By having our data available through the data sets that we populate through the ThoughtSpot products, we've got the opportunity to utilize Spotter and the natural language processing capabilities to interact with the data, so that you can ‘talk with your data’.” - Louis DiModugno
Louis DiModugno brings more than 20 years of career experience in data and analytics to his new role. He has held several leadership positions in insurance and (re)insurance at firms including The Hartford and AXA US, where he served as the company’s inaugural Chief Data & Analytics Officer. Most recently, DiModugno pioneered the role of Chief Data and Technology Officer for Hartford Steam Boiler.
Before entering the private sector, DiModugno served with distinction as a Colonel in the U.S. Air Force and Air Force Reserves. He has held teaching positions at Rensselaer Polytechnic Institute, and he currently serves on the Chief Data Officer Advisory Council for the George Mason University School of Business.
The Data Chief