Bridging the Gap: AI-Assisted Telehealth

Authored by: Noah Scheidt

Art by: Aleena Naeem

Mental healthcare in rural America remains one of the nation’s most pressing and overlooked crises. For decades, shortages of providers, long distances to clinics, and persistent stigma have left countless patients without the help they need. The COVID-19 pandemic not only accelerated the adoption of telehealth, but also drastically increased rates of mental health issues such as depression. These circumstances provided both the problem – increased rates of mental health issues – and the solution – telehealth visits with psychologists or psychiatrists. However, this was not enough, as still over 60% of rural Americans live in designated mental health professional shortage areas, compared to just 30% in urban regions [1]. With the recent integration of artificial intelligence into telehealth platforms, there is new potential to reduce disparities in rural mental healthcare.

Artificial intelligence is being embedded into services in multiple ways, from chatbots that provide cognitive behavioral therapy exercises to algorithms that flag early signs of depression or anxiety based on patient speech and text. Studies suggest that digital interventions can effectively reduce symptoms of depression and anxiety, particularly when used as supplements to therapy [2]. For rural patients, where access to psychiatrists and psychologists is often scarce, AI-driven tools can serve as an initial point of contact to determine the needs of the patient before the patient is put in contact with a psychiatrist. In addition, AI-assisted platforms can streamline clinical workflow by automating intake surveys, monitoring symptoms, and flagging high-risk cases for clinicians. This not only reduces burden on overextended mental health professionals but also ensures that critical cases are given priority.

However, there are still many barriers that the telehealthcare field must overcome. First, reliable broadband internet remains unavailable in many rural areas, limiting who can benefit from these technologies [3]. Furthermore, those in rural communities may be less likely to share mental health issues with an AI tool, especially because of the stigma that already exists in many rural communities regarding mental health problems. Research shows that this stigma is linked to both reluctance to seek care and distrust of digital mental health tools, as many rural patients associate technology-mediated care with impersonality and exposure risk [5]. Patients also may fear being regarded as weak or judged by their community, which further discourages them from using AI-based tools that require the disclosure of personal information such as name and insurance to access the service. Another barrier is algorithmic bias. AI systems trained primarily on urban or majority populations may not recognize the cultural norms that exist in rural communities, leading to possible incorrect recommendations. Lastly, it is hard to look at this issue and not think of how this could be used to further prioritize profits over quality of care. AI could potentially be used as a tool in mental healthcare to provide second-class care to those who would otherwise not receive any as a method to expand an organization’s profits.

To maximize the benefits of AI-assisted telehealth, a multi-pronged approach is necessary. First, federal and state investment in broadband infrastructure is essential to eliminate internet inequity. Second, policymakers must develop clear standards for AI transparency, and privacy in mental health. Third, local providers and community leaders should be involved in shaping implementation, ensuring that technology is culturally responsive and aligned with community needs. Pilot programs highlight the importance of such approaches. For example, partnerships between rural clinics and academic medical centers have shown that when telehealth platforms are tailored to community needs and supported by training for local providers, patient satisfaction and adherence improve [4]. Integrating AI into such models could further increase their reach and effectiveness.

AI-assisted telehealth has the potential to transform rural mental health care by uprooting the persistent gap in access. However, without thoughtful implementation, these tools are likely to reinforce existing disparities. If approached carefully, AI in telehealth could represent not only a technological advance but also a step toward health justice for rural America.

References:

1. Morales, D. A., et al. (2020). A call to action to address rural mental health disparities. Journal of Clinical and Translational Science, 4(5), 463–467. https://doi.org/10.1017/cts.2020.27

2. Yang, F., et al. (2025). Artificial Intelligence-Based Mobile Phone Apps for Child Mental Health: Quality Assessment and Literature Review. JMIR mHealth and uHealth, 13(1), e58597. https://mhealth.jmir.org/2025/1/e58597

3. Whitacre, B. E., & Rhinesmith, C. (2021). Broadband unavailability and health disparities in rural America. Telecommunications Policy, 45(3), 102072. https://doi.org/10.1016/j.telpol.2020.102072

4. Reali, L. (2025). What is the place for Digital Health and Artificial Intelligence in pediatric primary care? EClinicalMedicine, 74, 103901. https://doi.org/10.1016/j.eclinm.2025.103901

5. Naslund, J. A., Kim, S. J., Aschbrenner, K. A., et al. (2020). Digital technology for treating and preventing mental disorders in low-resource settings: A scoping review. World Psychiatry, 19(3), 364–375. https://doi.org/10.1002/wps.20794