A recent article from the American Psychological Association noted that Artificial Intelligence (AI) is increasingly being used in health care settings, with its potential use expected to expand across the industry. While AI adoption in health care is on the rise, many providers and patients remain hesitant about its implementation. Although this apprehension is understandable, AI has the potential to enhance accessibility, efficiency, and personalization in mental health care, provided it is utilized thoughtfully and ethically.
Currently, attitudes toward the use of AI in behavioral health care are mixed. Many people don’t feel strongly either way. On the other hand, there are a few who have strong opinions both in favor of and against the use of AI in mental health. However, as more physicians incorporate AI into their practices, particularly for documentation, openness to the use of this technology is increasing. As AI becomes more widespread, experts anticipate a shift in perception as people recognize its effectiveness as a tool to support, rather than replace, clinicians and clinical care.
AI tools hold great potential for improving behavioral health care. It can aid in faster, more accurate diagnoses, enhance patient engagement, and support clinician training and documentation. Because AI is designed to identify patterns and anomalies, it is well suited for these tasks. Additionally, AI can analyze clinician-patient interactions, extracting quality metrics such as how well clinicians apply their training and how empathetic they are in their patient interactions. In terms of training, AI can facilitate skill development in evidence-based practices by allowing clinicians to practice new techniques in a risk-free environment before applying them in real-world patient care.
At organizations like Centerstone, a nonprofit health system specializing in mental health and substance use disorder treatments, AI is already being used for improvements in electronic health records, note-taking, and documentation. Feedback from providers has been largely positive, with many reporting that these tools have cut their documentation time by more than half. Like many behavioral health organizations, Centerstone is committed to using AI only as a means to enhance care, not as a replacement for clinical judgment. The goal is to make clinicians’ jobs more efficient and to improve the quality of patient care.
As AI continues to expand in behavioral health care, ethical and practical challenges must be considered. Concerns often arise about AI’s reliability and accuracy, making it essential that organizations ensure they are using high-quality, well-tested products. Health care is heavily regulated in terms of quality and administration of care, yet standardized AI regulations remain in early development. Efforts are underway at the federal level to establish guidelines for responsible AI use in health care settings. While formal regulations are still evolving, existing frameworks emphasize the need for transparency with patients.
For instance, if AI is used for note-taking and does not influence a patient’s care, disclosure may not be necessary. However, if AI assists in diagnosing a condition and directly impacts treatment decisions, clinicians must inform patients of its use. While AI does not replace clinical judgment, transparency about its role as a tool is crucial.
Another challenge is that many clinicians may not fully understand how AI works. To address this, these professionals must develop a sufficient understanding of the technology to explain how it arrives at its conclusions and to communicate this information in simple terms to their patients.
Additionally, when selecting AI vendors, organizations should evaluate not only the reliability of the software but also the research behind it. Key considerations include how the AI model was trained, its accuracy, and how it is monitored over time. AI’s ability to make accurate diagnoses depends on the quality and diversity of its data input. For example, an effective AI model for diagnosing depression should be trained on data that represents a wide range of ages, genders, races, and socioeconomic backgrounds to ensure accuracy across diverse populations.
To verify the reliability of AI technology, companies should ask whether the product is based on independently researched models or if the vendor conducted all research internally. If the latter, they should request details on the research process. Speaking with other companies that use the product can also provide valuable insights into its effectiveness and any challenges they have encountered.
Ultimately, AI presents a promising opportunity to enhance behavioral health care, but its implementation must be carefully managed to ensure ethical use, accuracy, and transparency.
Ashley Newton is the Chief Executive Officer of Centerstone’s Institute for Clinical Excellence and Innovation. Learn more at Centerstone.org.
