The United States is in the midst of a fatal women’s mental health crisis. On the surface, this crisis can be attributed to the chasm between demand for patient care and the availability of mental health professionals. The reality is much more stark: while the nation’s pool of qualified and available mental health professionals is limited, the specialized education required to treat some of the most acute conditions among this population is all but absent in traditional clinical training.

Currently, there are fewer than 500 trained psychiatrists in reproductive mental health. That’s for a population of nearly 800,000 women in the U.S. who experience maternal mental health complications every year — to say nothing of the unique (and dire) needs of all women across all stages of life, from perinatal to perimenopause. 

The fact is, traditional methods of training have failed to keep pace with both academic advancement and demand for patient care, and the broader healthcare system now finds itself in a seemingly intractable imbalance. How do we provide a workforce in short supply with the specialized education — and, importantly, hands-on experience — required to treat debilitating mental health conditions in short order? 

Training is time-intensive, requiring hours of live patient encounters, observation, and feedback, and there is no guarantee that residents will be exposed to reproductive mental health cases during generalized training. Their experience is often limited by the diversity of the patient populations they encounter during their rotations. Without comprehensive and consistent exposure, many clinicians will continue to leave their residency programs without the knowledge necessary to treat mental health conditions like postpartum depression effectively. 

I rotated through five different hospitals in my own residency, each of which offered a limited exposure to various patient populations. There were entire populations I didn’t have the chance to observe at all, even having spent a month or two at each site. Generations of psychiatrists are missing out on critical opportunities to understand cultural sensitivity in psychiatric care before they enter practice.

This is a bottleneck created by a shortage in supply, but drawn taut by an inability to scale specialized education and experience. While nothing short of a miracle will alleviate the shortage of mental health professionals in the U.S., generative AI can play a critical role in solving the problem of scale.

How AI can fill gaps in education and experience

So much of the public discourse around AI in healthcare over the past few years has focused on the technology’s potential to help diagnose diseases, personalize treatment plans, or free up clinicians to focus on care by automating tasks like notetaking. But generative AI’s most immediate and practical application may be in medical education — specifically, in simulating complex care scenarios for specialized populations.

Successful psychiatric treatment often hinges on a clinician’s ability to build trust with a patient, elicit key information, and navigate cultural nuances. Our healthcare system’s inability to nurture and refine these skills is partially why nearly three quarters of women never receive treatment for perinatal mental health conditions. Generative AI can simulate highly adaptable patient avatars that respond dynamically to a clinician’s questions and approach. 

Unlike static textbook cases, AI-generated simulations offer a universe of opportunities for clinicians to gain broad exposure, practice, and enhance their emotional intelligence. For example, a trainee might encounter a postpartum patient avatar — a young Spanish-speaking mother on Medicaid, managing type 2 diabetes and struggling to keep her car out of the shop. She feels isolated, overwhelmed by mounting bills, and intense feelings of worthlessness. Clinically, she’s presenting symptoms of depression. And this is who we are often missing with our existing training.

An AI-enabled training module can assess how well the trainee obtains relevant details like sleep patterns, mood fluctuations, and history of mental health conditions, while also providing real-time feedback on empathy and bedside manner, open-ended questioning, and even non-verbal cues like eye contact.

One of the most significant challenges in current psychiatric training is the inconsistency in patient demographics across different hospitals and clinics. Some trainees may never encounter certain populations, leaving them unprepared to address cultural and socioeconomic factors that influence mental health outcomes. As a result, it can be common for a young black mother to receive the same treatment as a middle aged white man. 

AI-generated simulations can standardize diversity in exposure by creating virtual patients from varied backgrounds, each with unique risk factors and life experiences. This ensures that clinicians develop cultural sensitivity and learn to anticipate complications that might arise in specific populations.

Low risk, high reward

Generative AI is still finding its place in healthcare. The hype around various applications of the technology has fizzled somewhat as solutions across the industry struggle to demonstrate their ability to help providers turn a profit. More broadly, criticisms and concerns around accuracy, ethical implications, and potential biases in AI models persist. 

These hedges are not just valid, but warranted whenever new technology is introduced in clinical settings. However, when applied to medical education, the risks are relatively low — especially compared to the potential benefits. Unlike diagnostic AI tools, which directly impact patient care, AI-driven simulations serve as a learning tool, a safe and controlled environment where clinicians can make mistakes, learn, and improve without putting real patients at risk.

In an application like this, generative AI poses no threat to humans. Not their lives, and not their jobs. Instead, it’s a force multiplier, enabling training programs to scale much faster and much more effectively. The manual hours required to train the number of reproductive psychiatrists needed to meet current demand is not feasible under traditional models. A single AI-generated simulation can provide consistent, high-quality training to hundreds or even thousands of clinicians, vastly expanding access to much-needed specialized psychiatric care.

The maternal mental health crisis demands urgent, dynamic solutions that can train the next — and current — generation of mental health professionals to meet this challenge head-on. Generative AI may be that solution. By embracing this technology thoughtfully, the medical community can ensure women receive the mental health care they deserve, at every stage of life. Even more promising, it can take medical education far beyond where it stands now by arming professionals with the knowledge and experience they need to treat any specialized patient population.

Photo: krisanapong detraphiphat, Getty Images

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