The Value of AI in Rural Healthcare and for Rural Providers

Key Takeaways on the Value of AI in Rural Healthcare

AI augments — not replaces — rural care teams by helping reduce administrative workload and staffing pressure.
Ambient charting cuts documentation time, so providers spend more time with patients and less time working after hours.
AI-powered clinical support expands access to expertise, so organizations strengthen diagnosis, treatment decisions, and early intervention.
Operational AI improves efficiency across workflows, so rural organizations reduce manual tasks, limit billing errors, and support sustainable care delivery.

AI (artificial intelligence) is helping healthcare providers of all types reduce stress, increase accuracy, and deliver better patient care and care delivery. And with the persistent staffing shortages and funding challenges AI in rural healthcare can make a big impact on providers and patients.

What Is AI?

AI is the common acronym for artificial intelligence. But another term describes it better — augmented intelligence.¹ Where artificial intelligence implies replacing intelligence, augmented intelligence enhances intelligence instead of replacing it. Most AI in use today augment intelligence and tackle high-volume, low-value, and/or tedious tasks that take time and energy away from higher value tasks.

Applying AI to healthcare challenges helps providers address complex issues, such as data analysis, diagnostics, workflow optimization, and population health management. Augmented intelligence is an ideal way for healthcare providers and staff, especially in rural areas with staffing shortages and more limited resources, to do more without working more hours. Adding AI-powered tools can help facilities and providers decrease overtime hours worked, reduce burnout, and increase recruitment and retention.

How AI Augments Rural Healthcare

AI can help increase access to healthcare for underserved rural populations. And, it can help healthcare providers and staff reduce administrative tasks and access information they may not regularly have access to. Handling repetitive, manual tasks with augmented intelligence, facilitates faster workflows and can even give providers a virtual second-opinion.

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I’ve reduced the strain on my hands and saved hours each day.

tamara Maher, DO

Family practice physician, on ambient charting with Azalea Clinical Assistant

Popular Applications for AI in Rural Healthcare

While AI is capable of many uses, some of the most popular in healthcare are for reducing manual work or augmenting existing knowledge.

Ambient Charting

One of the most popular uses of AI for providers today is ambient charting (also called ambient listening or ambient clinical intelligence [ACI]). It uses AI to transcribe the interaction between patient and provider into clinical notes in real-time. It also automatically turns the transcription into usable clinical notes that the provider can approve and adjust as needed. Instead of spending time typing or recording notes during or after a visit, the provider can interact with the patient and capture the interaction automatically.

The notes of most ambient charting solutions attach to the patient’s record in the electronic health record (EHR) and are protected by the same security processes that protect the record itself. The large language models (LLMs) that drive AI are used to transcribe and understand clinical conversations. And they can further improve the accuracy and clarity of documentation for rural providers.

A research paper published in ScienceDirect found that providers who use AI for documentation has less burnout and frustration and spent 2.5 fewer hours a week working on documentation after hours.²

Another study done by the American Heart Association found that using AI for documentation reduced rural provider’s burden by 40% in Medicare Chronic Care Management (CCM) settings.³

And the Azalea Health Clinical Assistant tool, powered by Suki, is shown to reduce amended encounters by 48%, save providers 20 hours a month, and increase same-day encounter close rates by 25 points.⁴

AI charting can help with recruitment and retention too. Younger providers expect modern technologies and often prefer not to do things manually.

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I would say to another provider that if you want to be able to provide more precise notes, better patient care, better follow up, and just overall better service to the clinic and the patient, there’s no better way to do it.

Dr. Brian Gabber, DC

Gabbert Medical, on ambient charting with Azalea Clinical Assistant; read the Gabbert Medical case study

AI Treatment and Diagnosis Augmentation

A growing use of AI is using it to help providers diagnose and treat patients through on-the-spot second opinion decision support and early detection abilities. And partnerships between academic medical centers, government agencies, and AI companies have led to clinical decision support tools that improve diagnosis accuracy and enable earlier detection of conditions.

For example, AI can analyze X-rays or CT-scans to augment or validate what a provider sees. It can even detect patterns a provider may not see initially to help with early prevention and even improve rural patient outcomes.

This is known as predictive analytics. AI uses predictive models to analyze anonymized historical data sets to spot trends, predict responses or outcomes, and suggest diagnostic possibilities and customized treatment and dosage plans. Examples include using AI to identify patterns that show a patient is at risk of developing diabetes or heart disease based on health history, lifestyle, and more compared to known patient populations, including people living in rural settings.

Using AI to customize treatment plans or identify disease early can save a provider the time needed to manually find and compare patients based on inclusion and exclusion criteria.

AI can even be used to give providers access to specialized knowledge. For example, a physician assistant/associate can use AI as a coach to perform a more advanced procedure when a specialist isn’t readily available.

Similarly remote monitoring can give providers a way to monitor patients at a distance without seeing them in-person. For example blood pressure monitors or glucose meters can be used to collect and send data for provider review. Monitoring can be continuous or done with the provider during a telehealth visit.

Operational Augmentation

Healthcare AI tools can help increase operational efficiency too. AI chatbots and virtual assistants can do routine tasks, like scheduling appointments, sending appointment reminders, educating patients, and answering basic medical questions to free up staff and provider time.

AI billing augmentation not only saves teams time, it can also increase revenue. An AI billing tool, like Azalea AI Billing Assistant, can flag coding errors before bills are submitted. It can use predictive analytics to assess how likely a claim is to be denied and alert the biller before the claim is submitted. AI can flag inconsistent information to show billers what to check. And it can automatically track claim status after submission, so billers don’t have to.

Billers save the hours of time they might spend tediously verifying codes focusing on other tasks. And those hours saved, equal money in your pocket. Money you can use to pay your team to do more important work instead of chasing claim denials and coding errors.

The end result is that your organization has fewer denials and gets faster approvals, which means you get paid faster and spend less paying staff to do busy work.

The Adoption Landscape for AI in Rural Healthcare

Despite its promise, AI adoption in healthcare in general is below average compared to other industries.⁵ Even so, an AMA survey found that in 2024, two out of three physicians (66%) were using AI — 78% more than in 2023.⁶

Specific usage and sentiment data for rural hospitals, healthcare systems, and providers is lacking. But a questionnaire emailed to 48 providers at a rural medical center in Texas in May 2024 found that 58% of respondents were willing to use AI in their practices. It also found though that trust in AI around data privacy, accuracy and patient safety was a concern.⁷

And concerns are valid. It’s important to ensure any AI used is compliant and secure and understand that it exists only to augment provider and staff knowledge, not replace it.