Conversational AI Should Fill the White Space in Mental Health Care, Not Replace Humans

Conversational AI (CAI) is being rapidly deployed in mental healthcare settings, with much of the attention focused on using chatbots to deliver therapy directly to patients. However, we argue that this vision is too narrow and overlooks broader opportunities for CAI to extend existing systems of care. Mental health care systems have struggled for decades with structural gaps outside of immediate therapy delivery. Specifically, we identify opportunities for CAI to support (1) prevention and screening, (2) patients on waitlists, (3) between-session processes during ongoing therapy, and (4) post-treatment aftercare. Patients spend most of their time in these stages where human support is currently the least available. Rather than focusing on replacing clinicians in therapy, we argue that CAI should be strategically integrated into the broader care infrastructure to make the care system more seamless, less burdensome, and increase its capacity, thereby enhancing its effectiveness. We review preliminary studies that suggest that this is plausible. Across stages of healthcare delivery, we highlight specific opportunities and candidate mechanisms for effective and ethical implementation of such blended human-AI care.

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Publication Details

Published
2025-10-02
DOI
https://doi.org/10.31234/osf.io/e3qg7_v1
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
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article

Conversational AI Should Fill the White Space in Mental Health Care, Not Replace Humans

Elizabeth Cameron Stade, Johannes C. Eichstaedt, Jaan Aru, Mykyta Kabrel
1 citations
Artificial Intelligence in Healthcare and Education
0.65
article

Conversational AI Should Fill the White Space in Mental Health Care, Not Replace Humans

Elizabeth Cameron Stade, Johannes C. Eichstaedt, Jaan Aru, Mykyta Kabrel
article en
1 citations

Abstract

Conversational AI (CAI) is being rapidly deployed in mental healthcare settings, with much of the attention focused on using chatbots to deliver therapy directly to patients. However, we argue that this vision is too narrow and overlooks broader opportunities for CAI to extend existing systems of care. Mental health care systems have struggled for decades with structural gaps outside of immediate therapy delivery. Specifically, we identify opportunities for CAI to support (1) prevention and screening, (2) patients on waitlists, (3) between-session processes during ongoing therapy, and (4) post-treatment aftercare. Patients spend most of their time in these stages where human support is currently the least available. Rather than focusing on replacing clinicians in therapy, we argue that CAI should be strategically integrated into the broader care infrastructure to make the care system more seamless, less burdensome, and increase its capacity, thereby enhancing its effectiveness. We review preliminary studies that suggest that this is plausible. Across stages of healthcare delivery, we highlight specific opportunities and candidate mechanisms for effective and ethical implementation of such blended human-AI care.

Openalex Percentile: Top 21%
Artificial Intelligence in Healthcare and Education
0.65
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