Compute power has become one of the most crucial components of the healthcare delivery cycle.
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The landscape of healthcare delivery is being transformed by artificial intelligence (AI) applications and tools, sparking a surge in demand for advanced computational hardware. Companies are swiftly acquiring high-performance graphics processing units (GPUs) and high-bandwidth memory (HBM) to power large-scale language models and applications for their users. Similarly, forward-thinking healthcare leaders are realizing the necessity of substantial computing and memory resources to accommodate the growing use of AI-driven medical models and applications. While some continue to rely on established cloud providers, others are opting to develop sovereign, on-premise computing infrastructure.
Historically, healthcare institutions have depended on large cloud providers, which offer numerous bundled services and support. However, as cloud and computing expenses climb, the concept of building independent hospital data centers is gaining traction. According to DataBank, some healthcare leaders are investing in their own computing infrastructure to benefit from reduced costs associated with observability and monitoring. Healthcare operations often involve predictable, steady-state computing workloads, such as medical AI diagnostics and imaging analytics. Sovereign computing infrastructures provide enhanced auditability and observability, which are critical for ensuring patient safety and efficacy.
Owning computing resources also offers the advantage of mitigating reliance on fluctuating prices and potential price gouging. The AI computing market is largely driven by millions, if not billions, of daily users engaging with common AI models. As demand from retail users rises, compute providers are experiencing shortages, leading to price hikes and a rush to produce more hardware. By investing in their own infrastructure, healthcare organizations can reduce dependencies and shield themselves from such cost variations that come with public cloud reliance.
Moreover, there is an increasing focus among healthcare leaders on how compute sovereignty can enhance privacy and data sovereignty. When healthcare entities achieve vertical integration, offering end-to-end services from application to hardware, they gain full control over their data’s ownership and usage. This setup significantly reduces cybersecurity risks by limiting external access to data through cloud or hardware infrastructures. The HIPAA Journal reported nearly 75,000 data breaches in 2024 alone, with an ongoing annual increase since 2023. As healthcare organizations increasingly rely on AI, the incidence of cybersecurity threats is expected to rise.
However, managing sovereign computing resources is not without challenges. Many healthcare providers opt to outsource their computing needs to experts to leverage specialist management expertise. Establishing hospital-based data centers is not only complex but also resource-intensive, requiring ongoing maintenance, substantial initial investments, and significant physical space. The construction of a hospital data center can take anywhere from two to five years. For many, working with seasoned technology or cloud providers that offer turnkey solutions and rapid application deployment remains a practical choice, sparing them the burden of maintenance costs or issues.
As memory and chip prices continue to rise, healthcare organizations embracing AI applications will encounter important cost and infrastructure choices. Recognizing the essential role of computing power in modern medicine, akin to electricity or clean water, will ensure that hardware capabilities remain a critical focus in the years ahead.
