Enterprise AI is no longer an experiment. Across financial services, telecom, life sciences and beyond, organizations are moving from exploring “what AI can do” to building the infrastructure that lets it perform reliably, at scale, and close to the data that makes it useful. The hard questions are no longer about models. They’re about infrastructure: where AI workloads run, how they connect to data and partner ecosystems, and how enterprises manage distributed deployments without losing control.
NVIDIA GTC 2026 is where those questions surface in full force. At Booth #1030, Equinix is in the middle of that conversation, demonstrating how the Equinix Distributed AI framework gives enterprises a single convergence point for compute, interconnection, and the partner ecosystems that modern AI workloads depend on. Over three days, our team is capturing that conversation: interviews with Equinix experts, subject matter experts, and the partners building the next generation of enterprise AI infrastructure.
This is where we’re collecting it all.
How Distributed AI is Reshaping Enterprise Architecture
Executive Interview – In this Cube Conversation, DD Dasgupta, VP of Product Marketing at Equinix, discusses how the distributed nature of data is transforming enterprise AI architecture. He explains why moving AI models to where data resides—rather than centralizing everything—enhances efficiency and cost-effectiveness, especially for industry-specific workloads in financial services, healthcare, and retail. Dasgupta introduces the Equinix Distributed AI™ Hub, designed to connect neoclouds, hyperscalers, and ecosystem partners for AI inferencing, while addressing sovereignty across data, network, and AI tiers.
Recorded by TheCUBE Research, March 13, 2026.
Interviews:
Day 1 – March 16, 2026
Equinix on Distributed AI, Sovereignty and What’s Coming Next
Executive Interview – Jon Lin, Chief Business Officer at Equinix, discusses how the Equinix Distributed AI ™ Hub empowers enterprises to scale AI workloads seamlessly across clouds, data centers, and edge environments. He highlights the critical role of distributed, vendor-neutral infrastructure in reducing latency, ensuring data sovereignty, and optimizing performance for AI inferencing, enabling businesses to innovate faster and more effectively.
Recorded during NVIDIA GTC 2026, San Jose, CA, March 16, 2026.
Enterprise AI Is Missing a Control Plane (Equinix Distributed AI ™ Hub Explained)
Executive Interview – Keith Townsend, The CTO Advisor, joins Equinix’s Kaladar Voruganti, Chief Technologist, and Lily Liu, Solutions Architect, to explore how distributed AI is reshaping enterprise strategies. They discuss the benefits of processing AI workloads closer to data sources, the importance of interconnection for scalability, and how Equinix’s infrastructure supports real-time decision-making across industries. The conversation highlights the role of distributed AI in driving innovation while addressing challenges like latency and data sovereignty.
Recorded at Equinix HQ, Redwood City, CA, March 13, 2026.
Equinix Unveils the Distributed AI ™ Hub
Executive Interview – Kevin Egan, Sr. Director of Technical Marketing at Equinix, discusses how distributed AI infrastructure is driving enterprise innovation. He explains the advantages of processing AI workloads closer to data sources, including reduced latency, improved compliance with data sovereignty regulations, and enhanced scalability. Egan also highlights the role of the Equinix Distributed AI ™ Hub in connecting neoclouds, hyperscalers, and ecosystem partners to optimize AI inferencing.
Live on LinkedIn during NVIDIA GTC 2026, San Jose, CA, March 16, 2026.
Day 2 – March 17, 2026
Jensen Said 90% of Enterprise Data Is Unusable. He’s Right.
LinkedIn Article by Jon Lin, Chief Business Officer at Equinix, delves into the challenges enterprises face with underutilized data, emphasizing that 90% of enterprise data remains unusable. He explains how distributed AI infrastructure, like the Equinix Distributed AI™ Hub, can transform this data into actionable insights. By processing data closer to its source, enterprises can reduce latency, ensure compliance with data sovereignty regulations, and scale AI workloads effectively across clouds, data centers, and edge environments.
Published on LinkedIn during NVIDIA GTC 2026, San Jose, CA, March 17, 2026.
Tomás Puig on Alembic and causal AI at GTC26
Customer Interview – Tomas Puig, CEO of Alembic, and Savannah Peterson, Analyst at Savvy Millennial, discuss how private intelligence and distributed AI infrastructure are revolutionizing enterprise data management. They explore the challenges of unstructured data, the importance of building world models to uncover hidden insights, and the role of private intelligence in outperforming general AI. The conversation highlights how Equinix’s infrastructure supports the scale and performance required for advanced AI workloads, enabling businesses to unlock the full potential of their data.
Recorded during NVIDIA GTC 2026, San Jose, CA, March 16, 2026.
Shon Manov on Rackdog’s bare metal-aaS capabilities at GTC26
Partner Interview – Shon Manov, Co-founder of Rackdog, shares how their bare metal infrastructure as a service is transforming AI workloads by delivering ultra-low latency and high throughput. By eliminating hypervisors, Rackdog enables businesses to shave off critical milliseconds, essential for latency-sensitive applications like AI inference and financial trading. The discussion highlights Rackdog’s global expansion, supported by Equinix’s connectivity-rich data centers, which provide the reliability, scalability, and ecosystem needed to meet the demands of distributed AI and enterprise customers worldwide.
Recorded during NVIDIA GTC 2026, San Jose, CA, March 16, 2026.
Glenn Dekhayser on the future of AI at GTC26
Executive Interview – Glenn Dekhayser, Global Principal Technologist at Equinix, discusses the critical role of distributed AI in enabling enterprises to achieve scalable, compliant, and efficient AI outcomes. He highlights how Equinix’s interconnected global data centers, hybrid multicloud solutions, and last-mile connectivity provide the foundational infrastructure for AI data platforms and AI factories. By addressing challenges like data sovereignty, governance, and latency, Equinix empowers businesses to navigate the complexities of AI while ensuring repeated success across diverse use cases.
Recorded during NVIDIA GTC 2026, San Jose, CA, March 16, 2026.
Day 3 – March 18, 2026
2026 ZKast #41 – Equinix at GTC 2026: Powering the Shift from AI Training to Edge Inferencing
Executive Interview – Jon Lin, Chief Business Officer at Equinix, discusses the pivotal role of Equinix in enabling distributed AI and edge inference at NVIDIA GTC 2026. With 270+ interconnected data centers across 37 countries, Equinix provides the infrastructure to support AI workloads, from training to inference, closer to end users and data sources. Lin highlights innovations like 400G physical ports and 100G fabric connections, which ensure low-latency, high-throughput, and secure interconnection for AI applications. He also emphasizes the importance of data sovereignty, governance, and sustainability in scaling AI globally.
Recorded during NVIDIA GTC 2026, San Jose, CA, March 16, 2026.
Kaladhar Voruganti and Kevin Egan discussing GTC26 highlights
Kaladhar Voruganti, VP & Senior Technologist at Equinix with Kevin Egan, Sr Director Technical Marketing, highlights the transformative impact of Equinix Fabric in delivering predictable performance, enhanced security, and cost efficiency for AI workloads. By comparing public internet performance with Equinix Fabric, the analysis revealed significant time savings—up to tens of seconds when using complex toolchains. Equinix Fabric enables enterprises to set enterprise-wide policies, avoid vendor lock-in, and maintain flexibility to leverage the best AI models across multiple providers without costly data egress. This approach ensures agility and optimal business outcomes for customers.
Recorded during NVIDIA GTC 2026, San Jose, CA, March 17, 2026.
Day 4 – March 19, 2026
How Equinix Thinks About AI Infrastructure at Scale
Executive Interview – At NVIDIA GTC, Glenn Dekhayser from Equinix explains why many AI projects fail to move beyond the pilot phase. The challenges go beyond models to include siloed systems, unstructured data, and inadequate infrastructure. Glenn introduces the concept of the “AI factory,” where data centers are reimagined as systems designed to continuously turn data into outcomes. By focusing on reliable, secure, and localized infrastructure, Equinix enables enterprises to scale AI from experiments to production, ensuring long-term success. For more information, check out this LinkedIn post from Ravit Jain, Founder and Host of The Ravit Show.
Recorded during NVIDIA GTC 2026, San Jose, CA, March 18, 2026.
NVIDIA GTC 2026 Highlights
During the course of NVIDIA GTC 2026 we have had countless meaningful conversations with industry leaders. Enjoy a few of our favorite clips!
Recorded during NVIDIA GTC 2026, San Jose, CA, March 16, 2026 – March 19, 2026.
Episode 127 Data Center Sustainibilty
Executive Interview – Christopher Wellise, VP of Global Sustainability at Equinix, offers a fresh perspective on scaling AI sustainably during a CSO panel at NVIDIA GTC. He highlights innovative strategies like transforming data centers into active participants in the energy grid and forging new partnerships with energy suppliers. Christopher’s insights provide a practical roadmap for addressing the sustainability challenges of AI infrastructure at scale.
Recorded during NVIDIA GTC 2026, San Jose, CA, March 17, 2026.
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