Kiewit's Chief Data and Analytics Officer, Matt Pappas, has spent 15 years building machine learning into one of the world's largest construction companies — long before "AI-ready" was a buzzword. In this episode of teh AI Proving Ground Podcast, he shares what he's learned about data culture, decision science, and the discipline most enterprises are skipping when it comes to driving AI strategy at scale.

AI is forcing a new leadership challenge inside the enterprise, in which boards are expected to oversee a fast-moving technology they do not manage day to day, while executives are tasked with deploying it responsibly at speed. In this episode, Byron Loflin, Global Head of Board Advisory at Nasdaq, and WWT AVP of Global Cyber Advocacy Kate Kuehn explore what that means for modern governance — from board-level AI literacy and trust between directors and management to error reporting, escalation paths and the growing need for stronger oversight as AI systems become more capable and more autonomous.

AI security is entering a new phase where models like Anthropic's Mythos are becoming more capable and agentic systems can take action across enterprise environments. The risk is no longer just bad answers or hallucinations. It is speed, scope and blast radius. In this episode of the AI Proving Ground Podcast, WWT security leaders Jillian Nix-Anderson and Istvan Berko explore how organizations can secure themselves in the agentic AI era, where vulnerability discovery, response timelines and operational complexity are all accelerating. And they talk about how WWT's ARMOR framework helps teams structure the conversation across infrastructure, models, data, software development, operations and compliance.

From AI ambition to real business impact — how WWT and NVIDIA are helping Asia-Pacific (APAC) organizations build, scale, and operationalize AI.

What does it really take to make AI useful in the enterprise? In this episode of the AI Proving Ground Podcast, Jack in the Box VP of Data and Analytics Paul Bruffett and WWT Managing Director of AI and Data Analytics Daniel Morrisroe detail how to turn fragmented data, legacy systems and disconnected workflows into an operational foundation the business can actually use. From modular data products and self-service analytics to forecasting, personalization and the road to more autonomous systems, this conversation offers practical lessons for leaders trying to move from modernization to measurable AI outcomes.

As AI coding assistants move from novelty to necessity, enterprises are discovering that the real challenge is managing what happens before and after the code is created. In this episode of the AI Proving Ground Podcast, WWT's executive AI advisor Nate McKie explains why faster code generation is only half the answer — and why leaders who don't reinvest the time they're saving are already falling behind.

The new AI bottleneck is whether your enterprise data can be trusted, governed, and used at speed. Recorded live at NVIDIA GTC, this episode of the AI Proving Ground Podcast features Tore Sundelin of NetApp and Derek Elbert of World Wide Technology discussing why unstructured data, policy-based governance, data classification and unified AI data pipelines are becoming critical as enterprises push toward agentic AI and production-scale inference.

AI success now depends on whether your enterprise foundation is actually ready. Recorded live at NVIDIA GTC, this episode of the AI Proving Ground Podcast features WWT AI leader Mike Trojecki and Everpure VP of AI and Analytics Kaycee Lai discussing why business outcomes, secure data access, low-latency infrastructure, governance and storage architecture are becoming the real differentiators as organizations try to operationalize AI at scale.

AI is moving out of prototype mode and into production. In this episode of the AI Proving Ground Podcast, recorded live at NVIDIA GTC, leaders from Cisco, NVIDIA and WWT unpack the real job in front of enterprise executives: how to scale agentic AI, secure AI factories, manage token economics and prepare infrastructure for an inference-heavy future.