In the private sector, artificial intelligence (AI) tools are improving health care and connecting patients with services more quickly. They can ease paperwork burdens on physicians, smooth the insurance process, and help with scheduling and referrals. This is in addition to the many ways AI is improving the detection and treatment of any number of conditions. If this is possible in private systems, wouldn’t we want our veterans to have access to the same quality of care? With this in mind, the VA should consider adopting AI tools to cut wait times, free clinicians, and save money.
For decades now, the VA has struggled with long wait times and other inefficiencies stemming from government bureaucracy. While a better solution would lie in broader reforms around the underlying problems stemming from a government run health care system, AI tools can improve the current situation and connect veterans to the care they deserve. Existing systems are largely technically outdated and could present additional barriers to AI adoption. Broader reforms should also consider how to maintain more flexibility to not risk falling behind when such innovation occurs whether it is from AI or other technologies.
AI tools can improve the current situation and connect veterans to the care they deserve.
Assuming technical constraints could be overcome, AI tools could be key in helping solve many of the problems plaguing the VA and providing veterans better care. Many of the VA’s backlog problems stem from the difficulty of keeping up with growing demand under resource constraints. As in many industries, AI may not replace humans, but it can alleviate burdens and make better use of limited resources. For example, existing AI tools can help optimize allocation of resources within an existing medical office or hospital and predict patient needs. Given prioritization systems the VA is required to use, this could help ensure that the patients most in need of care get it quickly and more patients can be seen. AI can also lessen the burden of administrative tasks, freeing up time for patients and improving their experience. In private sector health care, available AI tools have helped reduce documentation and electronic health record entry time by up to 40 percent, giving physicians more time to see additional patients or engage more thoroughly with existing patients.
The role of AI in health care is not just to improve the existing metrics or better executing the status quo. AI can improve diagnostics and find new treatments. For example, AI can screen test results and identify patterns that might have otherwise gone unnoticed. Beyond that, AI tools are becoming important in many kinds of medicine and disease management. Various AI tools, from smart monitors for diabetes to AI coaches for mental health and addiction conditions, can help patients manage chronic conditions. With these tools already available in the private sector, it makes sense to ensure they are available to our veterans as well.
Properly incorporating AI into a health system has another advantage: it can reduce costs. A 2023 National Bureau of Economic Research paper estimated that wide-scale AI adoption could reduce health spending costs by as much as 5 to 10 percent. That may seem low at first, but in the context of U.S. health care spending, it could easily amount to more than $200 billion. VA spending on veterans’ healthcare has been steadily rising and was around $149 billion in 2025. If the VA saw even a 1 percent improvement in health costs, whether due to widescale AI adoption either by veterans or in its own systems, it would be nearly $1.5 billion in government savings.
With these tools already available in the private sector, it makes sense to ensure they are available to our veterans as well.
Of course, AI in health care, both in the VA and beyond, raises specific concerns. Human judgment must remain part of the process, because AI can make mistakes in diagnostics or prioritization. For this reason, humans should remain part of decision-making in most settings. If concerns arise, the way an algorithm is weighted or the factors it considers can be reviewed and remedied in the underlying model more easily than by retraining generations of doctors when the status quo changes. There will continue to be questions about which factors should determine prioritization in the VA, and which treatments should be available; however, these debates exist independently of AI.
AI is one of the most exciting tools for transforming both health and health care. Our veterans should not be left out of that transformation.
Jennifer Huddleston is a Senior Fellow in Technology Policy at the Cato Institute.