Overview
Explore
Services
65 results found
How to Scale Agentic AI Without Losing Control
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.
What We Learned at NVIDIA GTC 2026
At NVIDIA GTC 2026, the conversation shifted from model novelty to enterprise reality. In this episode of the AI Proving Ground Podcast, WWT Chief AI Advisor Tim Brooks explains why agentic AI, inference-heavy workloads and physical AI are forcing CIOs and CTOs to rethink infrastructure, governance, trust and leadership.
Before You Scale AI, Fix Your Data Foundation
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.
When AI Starts to Act on Its Own, Who's in Control?
As artificial intelligence moves from prediction to action, a new security frontier is taking shape. In this episode, Zscaler's Head of AI Innovation Phil Tee and WWT's VP of Global Cyber Chris Konrad explore the rise of autonomous agents, the evolution of Zero Trust and what it means to secure AI itself. From poisoned prompts to quantum threats, they warn the biggest risk isn't just deploying AI — it's trusting it. A sharp, real-world look at how enterprises can protect their future as machines begin to make decisions of their own.
The CEO's Job in the AI Era: Accelerating Idea to Outcome (I2O)
As AI spreads beyond developers into every workflow, the differentiator shifts from tools to leadership. In this episode of the AI Proving Ground Podcast, WWT Co-Founder and CEO Jim Kavanaugh argues that winning in AI will lean heavily on culture: how fast an organization can learn, adapt and change. The new leadership challenge is moving fast without creating downstream chaos.
Cloud, FinOps and AI: What You Need to Know About Unit Economics, GPUs and the ROI Flywheel
AI has pushed cloud into overdrive. In this episode of the AI Proving Ground Podcast, two of our top cloud experts — Jack French and Todd Barron — reset the approach and detail why cloud is the launchpad but portability is the strategy; how to start greenfield with containers and abstraction; what a real FinOps model for AI looks like (unit economics, tagging, token/GPU visibility); where neo clouds fit versus hyperscalers; and how to handle cross-cloud risk and skill gaps; and the governance moves that accelerate—not restrict—innovation.
Compressing Idea to Outcome (I2O): WWT Co-Founder and CEO Jim Kavanaugh on Why AI Coding Assistants Could Reshape the Enterprise
AI-powered coding assistants are rapidly compressing the time it takes to build software and delivering a competitive advantage that can lead to transformational outcomes. But according to WWT Co-Founder and CEO Jim Kavanaugh, the bigger shift is organizational: companies must rethink leadership, data strategy and workforce skills to compete in an AI-native world. In this episode of the AI Proving Ground Podcast, Jim shares his vision for how coding assistants are emerging as one of the most practical and disruptive use cases in enterprise AI.
Scaling AI Across the Workforce to Empower Every Employee
In 2024, organizations laid the groundwork for AI transformation, and now in 2025, it's time to cement your AI strategy. Join WWT experts David Rosenblatt and Mike Davis as they share insights from our 2025 Digital Workspace Priorities research report. You'll hear their unique perspectives on treating AI like a new employee and guidance on transitioning from proof-of-concept to organization-wide AI implementation so you can empower every employee.
Agentic AI Is Coming for Software Development — Are Enterprises Ready?
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.
How Jack in the Box is Building the Data Foundation for 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.
Invisible AI: What AI Leaders Can Learn from IHG Hotels & Resorts' AI Strategy
At IHG Hotels & Resorts, AI is being applied with a clear principle: make the employee more effective so the customer experience feels more human. That approach, according to IHG CTO Jolie Fleming, who joined us in our latest episode of the AI Proving Ground Podcast, offers a useful model for any leader trying to scale AI adoption without losing trust, control or business focus.
Why Storage, Security and Data Readiness Now Decide AI Success
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.