AI moves trillions of dollars in milliseconds. So why won’t companies let it send a customer email?

In this episode of the AI Proving Ground Podcast, Erik Anderson, CEO of Singularity University and former Topgolf leader, breaks down the real constraint on enterprise AI adoption: trust.

We talk about the shift to agentic AI, how it's reshaping thought work, and the tension leaders face between productivity gains and the social contract with employees. If AI gives your team 20% of their time back, Erik argues that's not just cost savings. It's an opportunity to invest in growth, quality, and long term value.

We also cover:

• Why trust becomes the bottleneck before the technology
• How AI agents reshape brand and customer experience
• What leaders should actually do next

Most companies won’t hit a technical limit with AI. They’ll hit a trust limit first.

More about this week's guest:

Erik Anderson is Founder and CEO of WestRiver Group, a global investment platform focused on the innovation economy. He previously served as Executive Chairman of Topgolf, leading its rise into a global brand, and is now Executive Chairman of Singularity Group. An experienced operator and investor, Erik holds leadership and board roles across technology, energy, and consumer sectors, focused on scaling companies that shape the future.

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

Most personalization efforts fail long before AI becomes the problem.

It fails in quieter ways. A missing identity. A disconnected signal. A decision no one owns.

In this conversation, Ralph Jovine and Chris Douglas unpack why most personalization efforts stall long before AI becomes the problem. The issue is structural. Data ownership is unclear. Governance is inconsistent. Signals don’t connect across the journey.

They get into what actually needs to be in place for personalization to work at scale, and why the companies that get this right are the ones that treat it as an operating discipline, not a feature.

Support for this week's episode provided by: Netskope

More about this week's guests:

Ralph Jovine brings over 20 years of experience in digital marketing and e-commerce. As a former executive at global agencies like Accenture, Merkle, and CEO of Nervewire, he spearheaded large-scale marketing and digital initiatives for renowned brands such as Nike, Cole Haan, Ralph Lauren, L'Oréal, Toyota, Bridgestone, and Hilton Hotels. Ralph's expertise spans various domains, including Business Strategy and Transformation, CX Product Strategy and Technology, Omni-Channel Marketing, Commerce, CRM, Loyalty, Martech/Adtech, and AI/ML Strategy and Application.

Ralph's top pick: The C-suite's Blueprint to Personalization in Retail and Beyond

Chris Douglas is Senior Director of Product for Unified Commerce at World Wide Technology. He leads the strategy and growth of WWT’s Unified Commerce practice, helping organizations modernize how they connect customer data, experiences, and operations. His work spans commerce strategy, retail transformation, loyalty and personalization, and marketing technology, with a focus on turning fragmented systems into coordinated, measurable outcomes that drive growth.

Chris's top pick: Customer Experience Priorities for 2026

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

AI can generate answers instantly. But that doesn’t mean they’re right.

Most enterprise AI doesn’t fail because of the model. It fails because the data underneath it doesn’t agree. Different teams, different definitions, different outcomes. It’s subtle, and it breaks trust fast.

In this episode, Paul Bruffett, VP of Data and Analytics at Jack in the Box, joins WWT’s Dan Moristro to talk about what it actually took to fix that. A multi-year modernization across core systems set the stage, but the real shift came from treating data as a product and building consistency into how the business defines and uses it.

They get into what Dan calls semantic debt, why generative AI makes it harder to ignore, and how modular data products, a modern data stack, and a real MLOps foundation helped turn AI from something interesting into something reliable.

If your AI works in demos but not in the business, this is probably why.

Learn more about this week's guests:

Paul Bruffett is a data and analytics leader with deep experience across cloud platforms, data engineering, and data science. He has designed and implemented enterprise data lakes, big data platforms, and scalable architectures on AWS, Azure, and GCP. Known for a hands-on approach, he focuses on building systems that support continuous deployment of data and AI workloads at scale.

Paul's top pick: Jack in the Box CTO Reveals AI Playbook

Dan Morrisroe is Managing Director of AI, Data, Analytics, and Management Consulting at World Wide Technology. He works with organizations to turn data and AI strategy into real operating capability, helping align technology, teams, and processes to drive measurable business outcomes at scale.

Dan's top pick: From Static Scorecards to Real-Time Retail Intelligence

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

Most AI strategies look good in a demo. The real challenge is getting them to run at scale.

Recorded live at NVIDIA GTC 2026, this episode with Ragu Chakravarthi from Core42 and Kraig Ecker from WWT explores what it actually takes to move from AI pilots to production systems.

They discuss sovereign AI as critical infrastructure, what control really means across data and operations, and why trust has to be built into every layer. From governance and observability to regulated environments, this is what it takes to run AI in the real world.

The conversation also looks ahead to agentic AI, rising token demand, and the growing need for traceability and access control.

If you are working to operationalize AI at scale, this episode breaks down what most teams underestimate.

Support for this episode provided by: Forescout

More about this week's guests:

Ragu Chakravarthi is Chief Technology and Product Officer at Core42, leading AI infrastructure, platforms, and operations. He oversees large-scale AI cloud deployments across NVIDIA, AMD, and Cerebras, and has driven innovations like Compass and JAIS. His work focuses on enabling secure, scalable AI adoption, with emphasis on sovereignty, performance, and enterprise readiness.

Kraig Ecker is EVP of Global Service Provider Sales at WWT, leading teams that help the world’s largest telecom and hyperscale companies adopt next-generation technologies. With deep industry relationships, he has driven growth across AI, 5G, cloud, and edge, expanded WWT into new markets, and helped establish the company as a leading partner across the global service provider ecosystem.

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

AI is writing code faster than most teams can review it. That’s the tension.

Recorded live at NVIDIA GTC with Nate McKie, we get into what happens when developer speed takes off but security and quality don’t.

The middle of the development process is collapsing. Code is cheap. Mistakes aren’t.

So what actually has to change?

We get into AI-native engineering, agentic development and the shift from code generation to code governance. From code review bottlenecks and the “hourglass effect” to model selection, RBAC and secure data access, this is how enterprise teams scale AI without breaking things.

Support for this episode provided by: Thales

More about this week's guest:

Nate McKie is a Senior Executive AI Advisor with more than 25 years of experience in software and automation engineering. He helps organizations translate AI into real business outcomes, advising on strategy across data, infrastructure and applications to drive effective and responsible adoption.

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

AI is working. Your data probably isn’t.

As enterprise AI moves into production, a new constraint shows up fast. Not models. Not compute. Data.

In this episode, recorded live at NVIDIA GTC, NetApp’s Tore Sundelin and WWT’s Derek Elbert get into what’s actually slowing teams down. The shift from clean, structured data to messy, high-value, unstructured data that’s harder to find, govern and use in real time.

This is where things start to break. Data spread across systems. Inconsistent policies. No clear way to trust what’s being used.

And once AI depends on live enterprise data, those gaps don’t stay hidden for long.

Because at this stage, AI doesn’t fail at the model. It fails at the data.

Support for this episode provided by: Riverbed

More about this week's guests:

Derek Elbert is an AI Practice leader at World Wide Technology focused on hybrid cloud AI and high-performance architecture. He specializes in networking and storage within modern AI stacks, helping organizations design and scale infrastructure to support data-intensive, production-grade AI workloads.

Tore Sundelin is a product leader at NetApp focused on enterprise AI and data platforms. With 20+ years at Microsoft, Google and NetApp, he has built AI-powered products at global scale, including early machine learning capabilities in Microsoft Office. He specializes in turning complex data, governance and platform challenges into production-ready AI solutions.

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

AI isn’t slowing down. Your data center is.

As enterprise AI moves into real workloads, physical limits show up fast. Power. Cooling. Space. Timing. The conversation shifts quickly from what model to use to whether you can run it at all.

In this episode, Schneider Electric CTO Jim Simonelli and WWT’s Chris Campbell talk through what happens when AI infrastructure, data center design and workload placement collide in production.

Because “speed to first token” isn’t just about model performance. It’s about whether your environment can keep up.

More about this week's guests:

Chris Campbell is responsible for the strategy, development, and delivery of WWT's AIaaS/GPUaaS and Facilities & Infrastructure solutions, and their associated GTM to our clients. Campbell has also served as Sr. Director - Executive Engagement and Customer Advocacy at WWT, and was responsible for the strategy, development, and delivery of WWT's global customer executive engagement programs, and has also served as a Sr. Director of Engineering and Architecture - Mid America at WWT, where he was responsible for managing WWT's team of consulting systems engineers and architects in Mid America.

Jim Simonelli is a Schneider Electric leader focused on the infrastructure realities shaping enterprise AI. He brings a practical view of what it takes to make AI deployable at scale: reliable power, liquid cooling, flexible data center design, and the operational certainty leaders need before turning on compute. He speaks from both sides of the equation, as someone helping Schneider use AI while also helping enterprises build the environments required to support it. His perspective is relevant as organizations weigh cloud, hybrid and on-prem choices and try to move faster without locking into the wrong infrastructure decisions.

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

AI is working. Until it isn’t.

Not because the model failed, but because something behind it did.

In this episode, recorded live at NVIDIA GTC, WWT’s Mike Trojecki and Everpure’s Kaycee Lai talk through what starts to show up once AI moves into real use. Data that’s harder to access than expected. Systems that slow things down. Security and governance questions that weren’t part of the original plan.

It’s a different kind of conversation than most. Less about what AI can do, more about what it takes to actually run it inside a business.

There’s a shift happening underneath it all. AI is starting to behave like a core application, which means it inherits the same expectations around reliability, performance and control.

And that’s usually where things get complicated.

More about this week's guests:

Mike Trojecki brings 25+ years of experience across security, cloud, and AI, starting with his service in the U.S. Air Force supporting White House and Air Force One missions. He’s led emerging tech practices at top integrators and now leads the AI Practice at World Wide Technology, driving high-performance AI infrastructure and data strategies.

Kaycee Lai is a data and AI leader with 20+ years of experience driving innovation and enterprise transformation. At Pure Storage, he leads Enterprise AI and Analytics strategy. As founder and former CEO of Promethium, he pioneered Data Fabric, helping organizations unlock more accessible, usable data.

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.