Healthcare systems are short on staff and it has become one of the defining operational challenges of health systems. Hospitals and physician groups are contending with persistent labor shortages, escalating costs and growing administrative complexity, all while patients expect faster access and more personalized care. In the face of this dilemma, many have turned to artificial intelligence as a potential solution. AI supporters in this context tend to point out that without changing how work gets done, simply adding more people only worsens costs and exhaustion, making AI a practical necessity rather than a future experiment.
For Carlos A.S. Rodriguez, its value lies less in novelty and more in disciplined integration. “The real issue is not just that we don’t have enough people,” he says. “It’s that highly trained clinicians are spending too much time on work that technology can now handle safely and effectively.” As CEO and Cofounder of Humanate, an early stage company using agentic AI and digital avatars to automate high-volume healthcare administration, Rodriguez focuses on applying advanced technology with the same operational discipline a major retail brand brings to scale and consistency.
AI as a Foundation for Modern Healthcare Staffing
At its core, AI staffing in healthcare is about redistributing time. Intake calls, documentation, preoperative screening and prior authorizations absorb hours of clinical capacity each day. “There’s a misconception that AI will replace people,” he says. “I really disagree with that. AI will partner with humans and make them more effective by removing repetitive tasks that humans are way too smart to keep doing.”
This reframing is critical as healthcare spending in the United States approaches $5 trillion annually, roughly 18 percent of GDP. Simply adding more labor without changing workflows compounds cost pressures and accelerates burnout. In this context, tools such as AI staffing solutions that can immediately address core operational problems are perhaps better viewed as essential infrastructure.
Designing AI Adoption Around Clinical Reality
Trained as an engineer, Rodriguez spent two decades leading operations in manufacturing before bringing that business discipline into healthcare. As former Vice President of Business Operations at Baylor College of Medicine in the Texas Medical Center, he applied those principles to overseeing hospitals and physician clinics within the largest medical center in the world. That blend of operational rigor and clinical exposure now informs his approach to implementation. “Anytime you introduce a disruptive technology, you need governance,” Rodriguez says. “You have to hear from physicians, nurses and staff. For every doctor in a hospital, there are about 12 people supporting that role.”
Inclusive governance helps surface where AI can deliver immediate value and where human oversight must remain central. For him, smart adoption begins with a simple clinician-first test: does the technology help clinicians do their jobs better, and does it reduce the total cost of care?
Where AI Delivers Immediate Operational Impact
One of the clearest examples of this approach is preoperative screening. In many systems, nurses spend up to 45 minutes per individual collecting medication histories, explaining procedures and answering routine questions. AI agents can now conduct these conversations around the clock, in more than 100 languages, and convert them into structured reports for clinical review.
“We’ve been able to reduce a 45-minute task to less than 10 minutes,” Rodriguez says. “Nurses appreciate that because they went to school to take care of patients, not to document.” On the care delivery side, individuals are no longer constrained by office hours, and clinicians regain time for direct care. This becomes especially important amid national shortages, such as anesthesiology, where one physician may now supervise multiple operating rooms while nurse anesthetists manage cases alongside surgeons.
Restoring Access, Equity and Time in Care Delivery
The long-term significance of AI staffing is personal as well as professional for Rodriguez. Advances in large language models, including real-time translation and even sign language capabilities, are reshaping how people communicate with care teams, allowing information to be captured in their own words and presented clearly to clinicians. “Language should never be an impediment in healthcare,” says Rodriguez, who moved to the United States at age 12 without speaking English. Looking ahead, Rodriguez believes healthcare will move toward hybrid workforces where digital agents handle up to 80% of administrative tasks, leaving humans to focus on complex decision-making and care. “AI will never be as bad as it is today,” he says. “It’s only going to get better.”
At a time when the average physician visit lasts fewer than eight minutes, AI staffing solutions offer a chance to restore what has been steadily eroded by increasing access, extending availability beyond office hours and returning time to care teams. More time for clinicians with patients, and a system better aligned with why people chose healthcare in the first place.
Follow Carlos A.S. Rodriguez on LinkedIn for more insights.
