AI in rural primary care: 6 questions physicians must answer with their nurses and APPs

Artificial intelligence (AI) is increasingly becoming part of health care, from documentation and administrative tasks to clinical decision support.

For rural primary care practices, where resources and staffing are often limited, preparing care teams to use these tools effectively and responsibly is critical. Nurses and advanced practice providers (APPs) are central to that effort.

As chief nursing officer of the American Nurses Enterprise, I have seen firsthand how technology can either strengthen clinical teams or create additional burden when it is introduced without sufficient training or input from the people who use it. That is particularly important in rural settings, where practices may have fewer staff, fewer resources and less access to specialized training.

Here are 6 questions primary care physicians should be asking about AI, and together with their nursing and APP colleagues, begin to answer.

Why does AI training matter for rural primary care practices?

Rural practices cannot afford to think about AI simply as another technology purchase. AI adoption is fundamentally a workforce issue.

When used appropriately, AI can help clinicians spend less time on repetitive administrative tasks and more time on patient care. It may also help teams manage information, identify relevant clinical patterns and support communication.

Those benefits depend on whether clinicians understand what an AI tool can and cannot do.

That is why AI literacy needs to extend beyond physicians. Nurses and APPs need to understand how AI tools work at a basic level, when they may be useful, what their limitations are and when human judgment must take precedence.

What role can nurses and APPs play in AI-enabled primary care?

Nurses and APPs are often deeply connected to the day-to-day workflows that keep primary care practices running smoothly. They conduct assessments, coordinate care, educate patients and help explain treatment plans, manage follow-up and contribute to clinical decision-making.

That puts them in a unique position to identify where AI could help and where it could make a workflow worse.

At the American Nurses Association's 2026 AI in Nursing Practice Think Tank, leaders identified the need for nurse-led guardrails, greater AI literacy and nursing-specific guidance for responsible implementation. The think tank’s consensus report highlighted concerns of overreliance on AI-generated outputs, unclear accountability, algorithmic bias and increased cognitive burden.

Nurses should not simply be handed an AI tool after a purchasing decision has been made. They need to have a voice from the outset in identifying problems, evaluating solutions, testing workflows and determining what training is truly needed to make AI effective, so they can focus on their patients.

Can AI help address rural workforce challenges?

AI is not a substitute for nurses, APPs or physicians, nor should it be viewed that way. But when used thoughtfully, technology can reduce unnecessary administrative work and help clinicians manage information more efficiently, giving care teams more time to focus on patients.

For rural practices, that distinction is especially important. The goal is not to replace human expertise, but to use AI to support and extend the capabilities of the care team.

The American Nurses Enterprise, encompassing the American Nurses Association, the American Nurses Credentialing Center, and American Nurses Foundation, for example, is launching an initiative called Nurse AI Training in Rural and Underserved Communities focused on strengthening AI skills among nurses, with a priority on rural, remote and underserved settings. The three-year, $5 million initiative funded by Google.org and the Johnson & Johnson Foundation will enable co-designed education to help build nurses’ knowledge, skills and confidence in using AI safely in clinical settings.

Where could AI have the greatest impact in a physician practice?

The most immediate opportunities may not be the futuristic applications that receive the most attention.

Administrative tasks are a practical place to start. Documentation, information management, coding and billing, prior authorizations, scheduling-related workflows and other repetitive tasks can consume significant amounts of clinicians' time.

There may also be opportunities for AI to support clinical workflows, but those applications require greater caution. An AI-generated recommendation is not a clinical decision. Clinicians must understand the source and limitations of the information and retain responsibility for evaluating whether it is appropriate for an individual patient.

For nurses and APPs, training should therefore address both administrative and clinical applications and make clear where human oversight is essential.

What should AI training for nurses and APPs include?

AI training should go beyond teaching someone how to use a particular software platform.

Clinicians need foundational AI literacy: how AI systems generate outputs, why those outputs can be inaccurate or biased and how to recognize when an answer requires additional verification.

Training should also cover privacy, security, patient communication, ethical considerations and professional accountability.

Most importantly, education should be practical. Nurses should have opportunities to apply what they learn to realistic scenarios that reflect their actual work.

That is particularly important in rural communities, where training needs to account for the realities of smaller teams and different technology infrastructures.

How can primary care practices adopt AI without creating more burden?

Start with the problem, not the technology.

Before implementing an AI tool, practices should ask their clinicians what is consuming the most time, where unnecessary work exists and which challenges could realistically be addressed with technology.

Then involve the people doing the work.

Physicians, nurses and APPs should help evaluate potential tools, test them in real workflows and identify unintended consequences before widespread implementation.

Finally, practices should treat AI education as an ongoing process rather than a one-time training session. Technology will continue to evolve, and clinicians will need opportunities to build their skills as new tools emerge.

The goal is a stronger care team, not a less human one

For rural primary care, the promise of AI is not that technology will solve the workforce shortage. It is that thoughtfully implemented technology may help clinicians make better use of their time and expertise.

That requires nurses and APPs to be part of the conversation from the beginning.

Nurse AI Training in Rural and Underserved Communities is an important step toward building that capability. But the larger lesson extends beyond this initiative: If AI is going to become part of everyday health care, the people closest to patients must have the knowledge, confidence and authority to help shape how it is used.

For primary care physicians, that means viewing AI training not simply as a nursing initiative or technology initiative, but as an investment in the entire care team.

When nurses, APPs and physicians understand how to use AI safely and when their clinical judgment remains at the center of implementation, technology has a better chance of doing what it should: supporting clinicians and strengthening care for the patients and communities they serve.

Bradley “Brad” Goettl, DNP, DHA, RN, FNP-C, FAAN, is chief nursing officer of the American Nurses Enterprise, which encompasses the American Nurses Association, American Nurses Credentialing Center and American Nurses Foundation. He has more than 20 years of experience across clinical practice, health care administration, academia and nonprofit organizations and began his career in rural health care.