Equinix Sees AI Driving Data Center Demand, Interconnection Growth

AI is accelerating Equinix's data center demand , with enterprises moving toward larger, higher-power deployments and greater need for high-density, low-latency infrastructure.

Equinix's interconnection business grew 9% , supported by increasingly complex AI networks connecting data, cloud platforms, models and end users. New offerings include Fabric One and Inference Exchange.

Management expects 9%–12% annual adjusted funds from operations per-share growth through 2029 , with development projects generating mid-20% cash yields and demand diversified across customers and workloads.

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Equinix (NASDAQ:EQIX) sees enterprise adoption of artificial intelligence accelerating demand for higher-density data center capacity, interconnection services and latency-sensitive infrastructure, executives said during a Barclays conference discussion.

Arquelle Shaw, Equinix's President of the Americas, said she oversees growth strategy across the region from Canada through Chile and Argentina, including corporate development, business development and growth from investments. Shaw previously spent about six years as the company's senior vice president of sales for the Americas.

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Shaw said Equinix has evolved its go-to-market model to serve customer segments differently, ranging from small businesses served through channel partners to large global enterprises supported by dedicated teams. The company has "almost 11,000 customers," she said, distinguishing its customer base from that of other data center operators.

AI is raising capacity and density requirements

Enterprise customers have been increasing the size of their capacity requirements and deploying workloads that consume more power, Shaw said. She described a shift from 250 kVA deals once being considered large to megawatt-scale deployments becoming more common.

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While AI-focused companies and hyperscalers moved quickly to adopt the technology, Shaw said enterprises were initially more cautious. In prior discussions, many enterprise customers were still considering an AI strategy or dealing with "Shadow AI" usage within their organizations. This year, she said, those same customers have been more heavily engaged in developing and implementing AI strategies.