The rapid global expansion of artificial intelligence (AI) has created an unprecedented demand for data centers—the physical backbone of our digital transformation. Yet this technological revolution faces a fundamental challenge: where will the massive energy required to power these "intelligence factories" come from, and how can we ensure this power is reliable, affordable, and sustainable?
These critical questions took center stage at GLP's annual Groundbreakers event, where founder, chairman and CEO Hamid Moghadam engaged in a forward-looking discussion with U.S. Secretary of the Interior Doug Burgum about the intersection of energy policy, AI development, and supply chain evolution.
Part I: The Evolution of Energy Strategy
1. From "Energy Dominance" to "Energy Abundance"
Secretary Burgum outlined the White House's energy strategy, emphasizing peace and prosperity through energy diplomacy and domestic energy abundance. "Energy dominance is really about energy abundance," Burgum stated. "We need abundant energy to power the next generation of AI innovation and support great companies like GLP and their logistics customers."
The secretary positioned energy as not merely a commodity, but as the foundation for national security, economic growth, and technological leadership—particularly in the AI race.
2. The National Energy Abundance Committee
To accelerate this vision, the administration established the National Energy Abundance Committee, which Burgum chairs. "This committee serves as the foundation for domestic prosperity, international peace, and national security," he explained, describing its mission to streamline approvals and attract investment in energy projects.
Part II: GLP's Energy Transformation
1. Listening to Customer Needs
Moghadam revealed how customer demands are pulling GLP into the energy business. "While real estate costs represent just 3-5% of supply chain expenses, we've developed 5-10 year partnerships that reveal deeper needs," he said. "Energy has emerged as a critical factor—whether moving goods within facilities or transportation between them."
2. Solar Power as Competitive Advantage
With vast rooftop spaces across its properties, GLP sees solar as the most cost-effective energy solution for clients. "Solar represents the cheapest energy we can provide," Moghadam noted, highlighting the company's strategic shift from real estate to infrastructure and now digital infrastructure—particularly data centers.
3. The Data Center Dilemma
"Data centers consume enormous energy that renewables alone can't satisfy," Moghadam acknowledged, advocating for an "all-of-the-above" energy strategy. "We need to mobilize every resource—this isn't just about property owners, but manufacturing electrification, truck fleets, and all equipment requiring power."
Part III: The AI-Energy Infrastructure Race
1. An Existential Competition
Burgum framed the U.S.-China AI competition as an existential threat requiring urgent infrastructure development. "We're spending years getting permits for transmission lines while China moves ahead," he warned. "AI factories must be built near energy sources to avoid these delays."
2. Rethinking Location Priorities
Moghadam proposed a new paradigm: "The old mantra was 'location, location, location.' Now it's 'location, location, energy.'" He outlined a three-phase evolution: first building AI facilities near existing power, then increasing on-site generation, and ultimately deploying inference capabilities near population centers to reduce latency.
"We're particularly excited about converting our 6,000 properties near major population centers into inference-ready data centers," Moghadam revealed. "When LLM processing gives way to localized inference, we'll be positioned perfectly."
Conclusion: The Converging Future
The Groundbreakers discussion illuminated how energy policy, AI advancement, and supply chain logistics are becoming inextricably linked. As governments and corporations recognize energy abundance as the foundation for technological leadership, strategic investments in infrastructure and location planning will determine which economies thrive in the AI era.