Capitalizing on the AI Infrastructure Value Chain Beyond Nvidia: A Deep Dive into Underpenetrated Enablers

The AI revolution is accelerating, but the spotlight on Nvidia's GPUs has obscured a broader, more nuanced story. While compute remains central, the true scalability of AI hinges on underpenetrated enablers in the infrastructure value chain. These components-data infrastructure, networking, platforms, and liquid cooling-are poised to outperform traditional segments in growth and investment potential. Let's dissect why.

1. Data Infrastructure: The Unsung Backbone of AI Scaling

Data infrastructure is the bedrock of AI, enabling the collection, storage, and processing of massive datasets. Mordor Intelligence estimates the global AI infrastructure market size in 2025 at USD 87.60 billion, with a projected CAGR of 17.71% through 2030. This growth is driven by the need for high-quality, secure data management across training and inference stages.

Leading the charge are tech giants like Microsoft, Amazon, and Oracle. Microsoft's $80 billion fiscal 2025 AI data center investment and Oracle's $300 billion compute power commitment underscore the sector's momentum, as reported by TechCrunch. Meanwhile, Meta's $65 billion 2025 data center buildout, featuring 1.3 million GPUs, highlights the critical role of data infrastructure in sustaining AI's exponential demands, per AI Magazine.

2. Networking: The Arteries of AI Workloads

As AI models balloon to trillions of parameters, networking becomes a bottleneck-and an opportunity. Advanced network fabrics like Infiniband NDR and Ethernet 800G are essential for reducing latency and enabling synchronized GPU training at scale, according to TrendForce. By 2025, 78% of companies had adopted AI technologies, with 90% viewing networking as a competitive differentiator, per DemandSage.

Key players like Arista Networks, Cisco, and Juniper Networks are innovating with AI-driven analytics and cloud-native solutions. Arista's CloudVision platform and Cisco's AI Canvas are streamlining operations, while Juniper Mist's enterprise AI networking tools are gaining traction, as reported by CRN. The market for AI-specific networking is expanding rapidly, with cloud providers like Microsoft Azure and Oracle Cloud leading deployments, according to Mordor Intelligence.

3. Liquid Cooling: A Necessity, Not a Luxury

The energy demands of AI data centers are pushing traditional air cooling to its limits. Future Market Insights projects liquid cooling adoption to surge, with the market growing from USD 3.2 billion in 2025 to USD 15.7 billion by 2035-a 390.6% increase. Direct-to-chip cooling, which accounts for 47% of the market, is the gold standard for managing rack densities exceeding 50kW, according to a Yahoo Finance write-up.

Companies like Vertiv, CoolIT Systems, and nVent Electric are dominating this space. Vertiv's 20% CAGR growth projection and nVent's 40% annual expansion in data center cooling revenue highlight the sector's potential, as covered by CNBC. Hyperscalers like Google and AWS are already deploying modular liquid cooling systems, while regulatory pressures in the EU and Asia-Pacific are accelerating adoption, per GeoActive Group.

4. Platforms: Bridging Compute and Data

The platform layer-software and tools that integrate compute and data-is a hidden gem. Cloud-native AI accelerator instances, such as AWS's H100 clusters, are democratizing access to AI resources, with over 50 GPU-enabled instance types now available, according to Mordor Intelligence. This democratization is fueling a CAGR of 20.4% in the global AI market, projected to reach $2.74 trillion by 2032, per Coherent Solutions.

Startups and established firms alike are innovating in this space. For example, Alkira's agentless multi-cloud networking and Aviz Networks' AI-first software are redefining how enterprises manage distributed AI workloads, as highlighted by CRN's startup roundup.

Conclusion: The Case for Diversification

While Nvidia's dominance in compute is undeniable, the AI infrastructure value chain offers fertile ground for investors seeking high-growth opportunities. Data infrastructure, networking, and liquid cooling are not just complementary-they are foundational. With market sizes expanding at double-digit CAGRs and regulatory tailwinds in key regions, these enablers represent a compelling case for diversification.

As AI adoption accelerates, the winners will be those who recognize that the future of AI is not just about chips-it's about the entire ecosystem that makes those chips work.