The Rising Demand for AI Data Centers

The generative AI economy is expected to be worth $4 trillion by 2030.1 Widespread adoption of gen AI, enterprise integration across industries, geopolitical priorities, and a global race for AI dominance are all pushing demand sky-high. But for AI to grow at the pace that consumers and companies are demanding, the world needs more data centers. This rise in demand for data centers naturally means a rise in demand for the enabling technologies that make them possible, from cloud storage and cybersecurity to advanced chips and processors.

More and more data centers are popping up around the world, housing millions of servers that process today’s AI and machine learning models around the clock. Globally, AI data centers are likely to require nearly $5 trillion in investment by 2030.2 In the meantime, the amount of energy sucked up by data centers is expected to roughly triple in the next five years.1 The accelerating demand in energy and scale will continue to put pressure on enabling technologies to produce more and innovate fast.

This need could not be more apparent than in the chip industry. Projected demand for data centers in the U.S. alone would require 90% of the world’s chips, which is an unrealistic proportion considering the U.S. currently uses less than half of the world’s supply.3 And with energy demand being one of the biggest limitations to data center growth in the US, chip makers face great incentives for innovating more energy-efficient solutions.4

Amazon is one of several large companies investing in AI data centers across the U.S. and has been developing a liquid-cooling system to keep Nvidia and other high-power AI chips from overheating.5 It has begun integrating these systems into its massive data centers, like the one under construction in Indiana for Anthropic’s AI computing.

Alongside chips, companies like Amazon that are investing in data centers will need the best and most advanced cybersecurity systems to keep their AI data centers secure from cyber threats. AI data centers are particularly vulnerable to such attacks.4 The need for AI-powered and -focused cybersecurity companies extends to the power companies supplying energy to the data centers as well. This demand opens the door for the most innovative cybersecurity companies to grow alongside essential AI infrastructure.

Even though it might feel like AI is everywhere, the technology is still in its infancy, with massive growth projections in our future. That’s one major reason why the focus of TrueShares Technology, AI, and Deep Learning ETF (LRNZ) is not focused on the tech giants of today, but is investing in the AI leaders of tomorrow. The highly concentrated fund does hold behemoths like Nvidia and Amazon, but it mostly holds the AI enablers and sophisticated AI users we believe to be some of the big names in the future of tech. They include innovative AI cybersecurity companies like Cloudflare, Crowdstrike, and Zscaler alongside other AI enablers like Snowflake and Datadog. The connecting thread among all LRNZ holdings is that we believe them to be AI category killers. 

As AI grows, the companies and technologies needed to build the data centers powering it will be essential for scaling AI to its full potential. The question is whether you’ll be along for the ride or realize you missed the boat once it’s already too late to climb aboard.

For a full list of holdings, visit: https://www.true-shares.com/lrnz/ 

  1. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/data-centers-the-race-to-power-ai
  2. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-cost-of-compute-a-7-trillion-dollar-race-to-scale-data-centers
  3. https://www.utilitydive.com/news/not-enough-ai-chips-to-support-data-center-projections-london-economics/752371/ 
  4. https://www.deloitte.com/us/en/insights/industry/power-and-utilities/data-center-infrastructure-artificial-intelligence.html 
  5. https://www.cnbc.com/2025/07/09/amazon-web-services-builds-heat-exchanger-to-cool-nvidia-gpus-for-ai.html