HCA Healthcare’s AI Projects Don’t Stop at Pilots
How centralized management turns pilots into production systems
In their fourth-quarter earnings call on Jan. 27, 2026, HCA Healthcare CEO Sam Hazen told investors that the company is “all in” on AI, describing combining it with “the human intelligence that exists within our facilities,” to improve their quality, efficiency, and management effectiveness.
Those remarks came alongside HCA’s financial disclosure that it generated $75.6 billion in revenue in 2025, underscoring the scale of resources available to fund technology initiatives.
Hazen outlined three areas where HCA is applying AI: administrative functions, operations, and clinical care. He cited revenue cycle management, supply chain, staffing, and scheduling as active areas of deployment, while positioning clinical AI more cautiously and describing it as a longer-term objective rather than an immediate transformation.
Across the healthcare sector, AI is often discussed in terms of algorithms, models, or vendor platforms. HCA has not claimed that its AI advantage comes from proprietary models. Instead, the company’s public disclosures point to organizational capacity: centralized decision-making, standardized systems, sustained capital investment, and a repeatable process for moving AI from pilot to production across a national hospital network that includes roughly 186–190 hospitals and about 2,400 sites of care.
Where HCA Is Actually Using AI
Hazen’s language during the earnings call consistently tied AI to management tasks. He referenced throughput, productivity, staffing, operating room scheduling, and consistency of performance across facilities, framing AI as a tool for managers over being an experimental initiative.
That aligns with where HCA has concentrated its early deployments. On the operational side, the company has rolled out Timpani, an internally developed AI-driven staffing and scheduling platform. HCA has described Timpani as moving beyond pilot use and being deployed across multiple facilities to help align staffing levels with patient demand and clinician preferences.
The company’s ability to move tools like Timpani beyond pilots is tied to its internal structure. HCA operates a centralized Digital Transformation and Innovation organization, previously known as Care Transformation & Innovation, which oversees pilots and enterprise scaling. The system has also established Innovation Hubs embedded in live hospitals, including UCF Lake Nona Hospital in Florida and TriStar Hendersonville Medical Center in Tennessee, where clinicians and technologists test tools in active care settings.
Capital allocation supports that structure. HCA has reported annual capital expenditures in the $4 billion to $5 billion range, with information technology and digital infrastructure included as priorities. In its 2024 annual report, the company detailed nearly $4.9 billion in capital spending, enabling continued investment in technology even as several large nonprofit systems reported operating losses during the same period.
Why HCA Escapes “Pilot Purgatory”
A recurring problem in healthcare technology adoption is the gap between pilot projects and system-wide deployment. HCA has attempted to address that problem by sequencing its investments around standardization first. During the earnings call, Hazen said variable data sets across hospitals had previously limited the company’s ability to use large-scale analytics, calling the ongoing electronic health record transition “foundational” to future AI work.
As part of that effort, MEDITECH Expanse is now live in 43 HCA hospitals, representing an early wave of a broader EHR modernization intended to standardize clinical data across facilities. In parallel, HCA has partnered with Google Cloud to centralize and analyze data in the cloud as a foundation for analytics and AI development.
The clearest example of HCA’s ability to move from development to deployment predates the current generative AI cycle. The company’s Sepsis Prediction and Optimization of Therapy (SPOT) algorithm was developed internally using data from millions of patient encounters and deployed across 173 HCA hospitals. Peer-reviewed research found that the system enabled earlier detection of sepsis and was associated with improved outcomes. HCA has reported that SPOT helped save approximately 8,000 lives in its early years of use.
SPOT established an internal precedent for how the company evaluates and scales AI tools, demonstrating that HCA could identify a clinical problem, build a predictive system, integrate it into workflows, and deploy it nationally.
Governance has also played a role. HCA has published a Responsible AI policy and a separate policy governing the responsible use of generative AI, both of which require human review of AI outputs and restrict the use of unsanctioned public AI tools with company data. HCA has also referenced an internal AI Risk Register in presentations to the FDA, outlining how potential AI risks are identified and mitigated.
The result is an AI strategy that looks like operations. Nurse handoff tools developed with Google Cloud, ambient documentation systems being rolled out with Commure, and staffing platforms like Timpani are introduced through pilots, refined with clinician input, and then expanded in waves.