How Gi21 Capital Sees The Next Wave Of AI Infrastructure Growth

How Gi21 Capital Sees The Next Wave Of AI Infrastructure Growth

What does it really take to build the infrastructure powering the AI economy? While much of the conversation around artificial intelligence focuses on models, applications, and breakthroughs, far less attention is given to the physical foundations making it all possible. Behind every AI workload sits an enormous amount of infrastructure, from power generation and cooling systems to land acquisition, grid connectivity, and data center design. In this episode of IT Infrastructure as a Conversation, I speak with Damir Špoljarič, a technology entrepreneur, investor, and infrastructure specialist whose journey began at just 17 years old when he founded VSHosting. Over the following two decades, he helped grow the company into one of Central Europe's leading cloud providers while building a data center that achieved something few facilities can claim, verified 100% uptime for more than a decade. Damir shares the lessons learned from designing for resilience at a level where failure simply isn't an option. He explains why many operators underestimate the importance of redundancy, how early decisions around infrastructure design can have consequences years later, and why reliability often comes down to planning for scenarios that may never happen. We also discuss how AI is changing the economics and engineering of modern data centers. As compute density continues to rise, traditional approaches are being pushed to their limits. Damir explains why liquid cooling is becoming increasingly important, how power requirements have changed dramatically, and what operators must consider when designing facilities capable of supporting next-generation AI workloads. The conversation also turns to Europe's growing demand for AI compute capacity and the challenges involved in bringing new facilities online. From securing grid connections and navigating lengthy permitting processes to finding suitable locations with access to affordable energy, Damir offers a behind-the-scenes look at obstacles that rarely make the headlines but shape the future of digital infrastructure. We also explore digital sovereignty, sustainability, renewable energy, and why waste heat from data centers may become an overlooked opportunity for local communities. Along the way, Damir shares his thoughts on robotics, long-term infrastructure investment, and why he believes demand for AI resources is still in its earliest stages. If you've ever wondered what sits beneath the AI services we use every day, this conversation offers a fascinating look at the engineering, investment, and strategic planning required to build the infrastructure supporting the next generation of technology. What role do you think Europe should play in building the infrastructure needed for the AI era, and are we moving quickly enough to meet future demand?

AI Workloads Are Changing Network Traffic, Is Your Infrastructure Ready?

Have we spent so much time talking about AI models, data, and agents that we've overlooked the networks carrying everything between them? In this episode of IT Infrastructure as a Conversation, I sit down with Jamie Pugh, CTO of Globalgig, to discuss why connectivity is becoming one of the most overlooked challenges in enterprise AI adoption and why network resilience could determine whether AI initiatives succeed or fail. As organizations distribute AI workloads across multiple clouds, regions, and edge environments, network traffic patterns are changing dramatically. Jamie explains how traditional architectures were built for people consuming applications, while today's AI systems are increasingly driven by systems communicating with other systems. Agents, inference engines, data lakes, and cloud platforms are generating entirely new traffic demands that many existing networks were never designed to handle. We explore how bottlenecks emerge when enterprises rely on single cloud on-ramps, fragmented connectivity strategies, or network designs optimized for yesterday's workloads. Jamie shares why bandwidth alone is no longer the primary concern, and how latency, carrier diversity, observability, and intelligent routing are becoming business priorities rather than purely technical considerations. The conversation also examines the growing importance of predictive and self-healing networks, the role of network-as-a-service platforms, and why infrastructure, security, and AI teams can no longer operate in isolation. Jamie offers practical advice for organizations looking to audit their current network readiness and prepare for a future where AI-powered productivity depends on reliable, real-time connectivity. If AI is becoming part of the infrastructure that powers modern business, what happens when the network underneath it can't keep pace? Join us as we discuss the hidden foundation of enterprise AI and why resilient connectivity may become one of the biggest competitive advantages of the decade. What role do you think networks will play in determining the winners and losers of the AI era? Share your thoughts with me.

From SD-WAN to AI Traffic: How Enterprise Networks Are Evolving

What happens when AI workloads begin to overwhelm the network infrastructure originally designed for human browsing and SaaS consumption? In this episode of IT Infrastructure as a Conversation, I’m joined by Jamie Pugh from Globalgig to discuss why enterprise connectivity is rapidly becoming one of the biggest blind spots in the AI era. While much of the industry conversation focuses on GPUs, models, and data centers, Jamie explains why the network itself is now under growing pressure from entirely new traffic patterns driven by AI systems communicating with other AI systems. We explore how enterprise infrastructure was largely built around human behavior, employees accessing applications, downloading files, and consuming cloud services. AI changes that model completely. Today, agents are constantly interacting with tools, inference engines are querying massive data stores, and cloud environments are exchanging huge volumes of east-west traffic across regions in real time. Jamie explains why many SD-WAN architectures and broadband-heavy deployments were never designed for these sustained, burst-heavy workloads. The conversation also examines the growing importance of cloud on-ramps and why many organizations discover bottlenecks only after deploying AI-enabled services into production. Jamie shares how asymmetric broadband connections, fragmented carrier relationships, and static connectivity models can quietly introduce latency, resilience, and observability problems that directly impact AI performance and user experience. One of the most interesting parts of the discussion centers on how dependent modern workflows are becoming on AI tools. Jamie talks candidly about using platforms like Claude, Perplexity, and ChatGPT throughout his working day and why losing connectivity now feels less like a temporary inconvenience and more like losing access to an essential member of the team. That shift in expectation is forcing infrastructure leaders to rethink resilience, automation, and real-time observability across hybrid and multi-cloud environments. We also discuss programmable networks, predictive routing, network-as-a-service fabrics, and the growing move toward centralized control planes that can dynamically adapt to changing AI traffic patterns. Jamie explains why enterprises need to stop thinking purely about north-south traffic and start preparing for a future dominated by east-west communication between clouds, data centers, agents, and inference platforms. There is also a valuable conversation around governance, security, and data sovereignty as organizations increasingly bring AI inference closer to private infrastructure rather than relying entirely on public models. Jamie argues that networking, security, and AI strategy teams can no longer operate in silos if businesses want to scale AI safely and effectively. If your organization is building toward an AI-first future, this conversation offers a timely look at the infrastructure challenges many enterprises are only beginning to recognize.

Syndigo on Why AI Commerce Is Failing Without Better Product Data

What if the biggest problem in AI-powered commerce isn’t the AI at all, but the data feeding it? In this episode of IT Infrastructure as a Conversation, I spoke with Tarun Chandrasekhar, Chief Product Officer at Syndigo, about the hidden infrastructure powering modern commerce and why product data has suddenly become one of the most strategic assets inside every retail and consumer brand. As AI shopping assistants, conversational commerce, and agentic retail experiences rapidly move into the mainstream, many companies are discovering a hard truth. Their product information systems were never built for an AI-first world. Tarun explained why decades of fragmented product records, disconnected systems, inconsistent metadata, and siloed workflows are now becoming major blockers to reliable AI-driven discovery and personalization. This episode offers a fascinating look at why “single source of truth” projects continue to fail across enterprises decades after organizations first started chasing them. Tarun argued that this is less a technology problem and more a people-and-process problem, where organizational handoffs and disconnected ownership models continue to create friction across data pipelines. We also explored the rise of agentic commerce, AI readiness scoring for enterprise data, and how companies are now being forced to treat product data as infrastructure rather than simply marketing content. Tarun shared how smaller brands sometimes leapfrog larger enterprises by moving faster, adopting AI-native workflows more easily, and avoiding decades of technical debt. We also discussed Syndigo’s acquisition of OneWorldSync and how ratings, reviews, and product syndication data are increasingly interconnected within AI-powered commerce ecosystems. The long-term vision is a world where product data continuously improves through feedback loops between customers, retailers, AI systems, and manufacturers. If you work in retail technology, AI infrastructure, enterprise data management, supply chain systems, or digital commerce, this episode offers a valuable behind-the-scenes look at the systems quietly shaping the future of how products are discovered, trusted, and purchased online. Useful Links * Syndigo Acquires 1WorldSync to Lead AI-First PXM [https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsyndigo.com%2Fnews%2Fsyndigo-acquires-1worldsync%2F&data=05%7C02%7C%7C3a182cdc4b9d4cc0df1608deaf754cd4%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C639141115547703940%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=b4S8PkPSzO2C7a37vPJwWCbxwCVaMzQHyxvX7c7eflo%3D&reserved=0] * Syndigo [https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsyndigo.com%2F&data=05%7C02%7C%7C3a182cdc4b9d4cc0df1608deaf754cd4%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C639141115547757695%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=Y5I3RxiCbNq60Ob%2Befi7MqPULu83AqHjKnN6BXQMuMI%3D&reserved=0] * Connect with Syndigo’s Chief Product Officer, Tarun Chandrasekha [https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.linkedin.com%2Fin%2Ftarun-chan%2F&data=05%7C02%7C%7Cd78ed05ca2194f00fbbd08de997fa96a%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C639116970746763467%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=4EDf73O3cGWuTwn6X0aMDsH5OzRYjfEOUhkV6SoD0Fg%3D&reserved=0]r

Why Infrastructure Needs A Survivability Layer: HyperBUNKER And The Shift To True Offline Recovery

In this episode, I’m joined by Imran Nino Eškić and Boštjan Kirm from HyperBUNKER, two leaders whose perspective has been shaped by more than 50,000 real-world data loss and ransomware cases. This is not a conversation about theoretical security models or another incremental backup feature. It’s a discussion about what actually survives when production systems, identity layers, and cloud replicas have all been compromised. For years, infrastructure has been designed around availability, scale, and performance. Recovery was treated as a process that would work when needed. But as attackers have grown more patient and methodical, they now target recovery paths first, quietly mapping environments and neutralising backup systems long before an incident becomes visible to the business. That shift forces a new architectural question for infrastructure leaders. Where is the layer that remains reachable when everything connected has been taken down? We explore why so many environments that claim to be air-gapped or immutable still rely on credentials, control planes, and automation, and how those dependencies create hidden single points of failure. Imran and Boštjan explain how HyperBUNKER introduces a physically isolated survivability layer into modern infrastructure, using a hardware-enforced, one-way ingestion process and a double air-gap design that removes the network from the vault entirely. No IP address, no inbound ports, and no authentication surface to attack. This leads to a wider conversation about infrastructure governance, cyber insurance, and regulatory pressure. Insurers are increasingly focused on whether a final, untouchable copy of critical data exists, because the largest financial losses now come from failed recovery rather than the initial breach. That reality is pushing offline recovery out of the basement and into board-level architecture discussions. We also tackle the practical challenge every organisation faces. If only a small percentage of data can be placed in a fully isolated vault, how do you decide what keeps the business alive? That decision, as we discuss, cannot sit with IT alone. It requires operational and executive alignment around what the company must have to restart after a catastrophic event. This episode reframes resilience as an infrastructure design principle rather than a security feature. It asks where a survivability layer should sit alongside cloud platforms, backup software, and existing controls, and why the future of Infrastructure as a Service may depend as much on guaranteed recovery as it does on uptime. If your architecture assumes that recovery will always be there when you need it, this conversation may change how you think about your entire stack.