Meta Buys 1 GW Solar to Fuel AI Ambitions

Meta has secured nearly 1 gigawatt of solar power through three new agreements this week, accelerating its push to support growing artificial intelligence workloads. The deals, split between Texas and Louisiana, bring the company's total solar procurement to over 3 gigawatts in 2025 alone, highlighting the intense energy demands of AI infrastructure.

On Monday, Meta announced a 600-megawatt purchase from a large solar farm near Lubbock, Texas, scheduled to begin operations in 2027. Although this facility won't connect directly to Meta's data centers, it will supply the local grid, helping to offset electricity used by the company's facilities in the region.

Following the Texas deal, Meta revealed two additional agreements in Louisiana, involving the purchase of environmental attributes for a combined 385 megawatts. These projects are also set for completion in 2027 and rely on environmental attribute certificates (EACs) to counterbalance carbon-intensive power sources.

EACs, often called renewable energy certificates, were originally designed to incentivize renewable energy development when costs were high. They allow companies to buy credits that represent the environmental benefits of clean power, even if the electricity isn't directly consumed by their operations.

However, experts have raised concerns that EACs may obscure the true carbon footprint of tech companies, especially as AI drives up electricity consumption. With solar and wind power now cheaper than new fossil fuel plants in many areas, the certificates' role in stimulating additional renewable capacity is under scrutiny.

Critics argue that if firms like Meta aim to genuinely offset AI's energy surge, they should focus on spurring new renewable projects rather than relying on certificate schemes. This debate comes as data center expansions across the industry strain power grids and intensify climate discussions.

Meta's solar investments reflect a broader trend among tech giants turning to renewables for cost and sustainability reasons. As AI models grow more complex, the race to secure affordable, clean energy is likely to accelerate, shaping corporate strategies and regulatory responses in the years ahead.