Healthcare has never suffered from a lack of information. Insurance companies have years of claims data. Doctors have patient histories, laboratory results, medical research, imaging, and clinical notes. Hospitals collect enormous amounts of information every day.
The problem has been turning all that information into useful action quickly enough to improve a patient's health and prevent unnecessary expenses.
Artificial intelligence could begin to change that.
Two recent developments show how AI is moving beyond experimentation and becoming part of everyday healthcare. Cigna says its AI technology could save customers approximately $200 million in medical expenses over the next three years. At the same time, an American Medical Association survey found that more than 80 percent of physicians are now using AI professionally.
Together, these developments show how AI could help make healthcare more efficient, proactive, and eventually more affordable.
From paying claims to preventing them
Health insurance has traditionally been reactive.
A patient becomes sick, receives treatment, and submits a claim. The insurance company then processes the claim and pays its portion of the medical bill according to the person's coverage.
AI creates an opportunity for insurers to become more proactive.
Cigna is using AI to identify members who may have chronic or complex medical conditions and connect them with nurses and other clinicians earlier. The goal is to provide support before those conditions develop into more serious and expensive medical events.
According to Cigna, the technology could increase access to its clinical programs by 20 percent for people with conditions such as cancer, heart disease, and kidney disease. The company also expects its technology to assist with the earlier identification of breast, colorectal, and lung cancers.
That matters because emergency room visits, hospital admissions, and advanced medical treatments are among the most expensive parts of the healthcare system.
Consider a patient with diabetes, heart disease, or kidney disease. Small changes in laboratory results, prescription history, missed appointments, or claims activity may signal that the patient's condition is getting worse.
A human care team may not immediately recognize all those patterns, especially when information is spread across different systems. AI can analyze large amounts of data and alert clinicians that a patient may need help.
A nurse can then contact the patient, help coordinate an appointment, address medication issues, or provide additional support.
The technology does not need to replace a doctor to create value. It only needs to help the healthcare system intervene before a manageable condition becomes a medical emergency.
Cigna estimates that customers participating in these clinical programs save approximately $2,000 per year in medical expenses. Across thousands of members, those savings can become significant.
AI is already inside the doctor's office
AI is also becoming part of the physician's daily workflow.
The AMA reported that 81 percent of surveyed physicians were using AI professionally in 2026. That is more than double the adoption level reported when the organization first surveyed physicians about healthcare AI in 2023. Physicians now report an average of 2.3 professional AI uses, compared with 1.1 in 2023.
Doctors are using AI to summarize medical research, document patient visits, prepare discharge instructions, and support other clinical and administrative tasks.
This is important because much of the cost of healthcare is not directly related to treating patients.
Doctors, nurses, hospitals, and insurance companies spend enormous amounts of time documenting visits, reviewing records, processing claims, coordinating care, and completing administrative work.
Every hour spent on repetitive paperwork adds cost to the healthcare system.
When AI prepares a draft of a clinical note, summarizes a lengthy patient record, or organizes information for a physician to review, the doctor can spend more time evaluating the patient and less time typing into a computer.
That increased efficiency could allow healthcare professionals to help more patients without requiring the same increase in staffing and administrative expenses.
AI should be viewed as an assistant rather than a replacement for medical professionals. It can organize information, identify patterns, and automate routine tasks, but physicians and clinicians should remain responsible for making important medical decisions.
How AI could lower healthcare costs
There are several ways AI could reduce the cost of care over time.
- Detect health risks earlier. Treating a condition before it becomes severe is generally less expensive than treating it after hospitalization becomes necessary.
- Improve care coordination. Patients with complex conditions often see multiple doctors, take several medications, and interact with different healthcare facilities. Better coordination can reduce duplicated testing, medication conflicts, and avoidable hospital visits.
- Reduce administrative work. Faster documentation, claims processing, scheduling, and record review can lower the cost of operating medical practices and insurance companies.
- Help clinicians work more efficiently. AI can summarize information and surface relevant details, allowing doctors to focus their attention on the patient rather than searching through extensive medical records.
- Identify what actually works. AI can help insurers and providers see which interventions are producing better outcomes, which could shift more spending toward preventive care and treatments that offer measurable value.
None of these changes means health insurance premiums will suddenly fall next year. Technology requires investment, healthcare systems change slowly, and savings are not always immediately passed to consumers.
However, AI has the potential to bend the healthcare cost curve by allowing the system to accomplish more with the same resources while preventing some of its most expensive medical events.
Medical inflation could offset the savings
The largest threat to these affordability gains may be medical inflation.
The cost of hospital care, prescription drugs, medical equipment, labor, and specialized treatments continues to rise. Even when AI removes waste and improves efficiency, those savings can be offset when the underlying price of healthcare increases.
For example, an insurer may use AI to prevent thousands of dollars in avoidable hospital costs. However, if the price of hospital services, medications, and physician care continues to increase, consumers may not feel the full benefit.
This does not mean AI has failed. It means AI and inflation are pushing healthcare costs in opposite directions.
The tension in one line: AI can make the system more efficient. Inflation can make every service within that system more expensive. The long-term affordability of healthcare will depend on whether efficiency gains from AI can grow faster than medical prices.
Inflation is not the only factor affecting healthcare costs. Increased utilization, expensive new treatments, an aging population, and regulatory requirements also influence what patients and insurers pay. But medical inflation may be the most powerful force capable of absorbing the savings AI generates before they reach consumers.
A more proactive healthcare system
The most important change may be the transition from reactive healthcare to proactive healthcare.
Instead of waiting for someone to become seriously ill, AI can help identify risk earlier. Instead of requiring doctors to search through years of records, AI can organize the most relevant information. Instead of spending hours documenting every appointment, physicians can use AI to prepare notes for review. And instead of insurance companies only paying claims after care occurs, they can use their data to connect members with support before expensive treatment becomes necessary.
Cigna's projected $200 million in customer savings is one early example. The rapid adoption of AI among physicians is another.
AI will not solve every healthcare problem, and it should not be allowed to make important decisions without appropriate human oversight. Privacy, data accuracy, transparency, and accountability must remain central to its use.
Still, the direction is becoming clear. AI is giving healthcare organizations the ability to act earlier, reduce administrative waste, and use existing information more effectively. If those savings outpace medical inflation and are passed along to patients and employers, AI could become one of the most important tools for making healthcare more affordable in the future.