S&P Global has signed a definitive agreement to acquire datacenterHawk, a provider of intelligence covering global data centers, fiber networks and digital infrastructure, in a move aimed at strengthening its capabilities across the rapidly expanding AI infrastructure ecosystem. The transaction is expected to combine S&P Global's existing energy, power and technology research with datacenterHawk's asset-level market intelligence, creating a broader platform for investors, developers and enterprises tracking global infrastructure expansion.
The acquisition comes at a time when demand for AI computing capacity is accelerating investments in data centers, electricity grids, fiber connectivity and related infrastructure worldwide. Companies building AI models continue to increase spending on high-performance computing facilities, driving the need for deeper insights into data center supply, power availability, pricing, land acquisition and network connectivity.
Following the acquisition, S&P Global Energy plans to integrate datacenterHawk's intelligence with 451 Research, its technology research business, alongside its existing coverage of global power markets, grid infrastructure, renewable energy, sustainability and supply chain intelligence. The combined offering is expected to provide customers with a more comprehensive view of operational and planned data centers, compute capacity, power demand and infrastructure development.
According to S&P Global, the acquisition aligns with its broader strategy of delivering connected intelligence across industries increasingly influenced by artificial intelligence. As AI workloads reshape global infrastructure requirements, the company believes customers require integrated datasets that link technology deployments with energy markets, capital investments and infrastructure planning.
Dave Ernsberger, President of S&P Global Energy, said artificial intelligence is transforming not only technology markets but also the physical infrastructure and energy systems supporting the global economy. He noted that bringing datacenterHawk into S&P Global Energy would strengthen the company's energy expansion strategy while helping customers make more informed decisions in one of the fastest-growing infrastructure segments.
datacenterHawk's platform provides proprietary intelligence on data center supply and demand, pricing, construction pipelines, site selection and fiber connectivity through its Fiber Locator platform. By integrating these datasets with S&P Global's analytics, customers are expected to gain greater visibility into where new AI infrastructure is emerging and how demand for electricity, connectivity and computing capacity is evolving.
David Liggitt, Founder and Chief Executive Officer of datacenterHawk, said the data center sector now sits at the intersection of artificial intelligence, energy, capital investment and sustainability. He added that enterprises increasingly require intelligence connecting infrastructure growth with power markets, grid constraints, supply chains and environmental considerations, enabling a clearer understanding of where future capacity and investment opportunities may emerge.
The acquisition also reflects the growing importance of data as enterprises, investors and governments seek greater transparency into AI infrastructure deployment. Market participants are increasingly evaluating not only where new data centers are being built but also whether adequate electricity, land, fiber connectivity and sustainable resources are available to support long-term expansion.
Upon completion of the transaction, S&P Global expects to further enhance benchmarking, indices and analytical products related to compute demand, data center capacity, infrastructure availability and pricing. The deal is also expected to support the development of AI-ready datasets and analytics across its broader portfolio.
The transaction is expected to close during the second half of 2026, subject to customary closing conditions. S&P Global said the acquisition is not expected to have a material impact on its financial results.