Survey reveals the perception gap and strategic opportunities for AI in behavioral health care
Healthcare organizations face a growing demand for mental health services, but there are too few providers to meet the need. Could AI help bridge this gap? We recently conducted a consumer survey that reveals nuanced perspectives across different demographics.
Parents show notably higher comfort levels with AI mental health tools, with 65% feeling comfortable using AI assessment tools before speaking with a human provider. Nearly half (47%) of men also demonstrate receptiveness to AI treatment recommendations compared to 36% of women.
Despite this promising receptivity among certain groups, meaningful concerns exist about privacy and the preservation of personal connection in mental healthcare delivery. Our vision centers on AI as a behind-the-scenes assistant that handles operational tasks, rather than technology attempting to deliver therapy directly to patients. This approach is embodied in Iris Insights, our platform that enables data visualization and operational analytics to support behavioral health services.
AI offers valuable opportunities to enhance mental health services while maintaining the fundamental human elements of care. By understanding both openness and concerns, health care organizations, including health systems and community-based health centers, can develop thoughtful integration strategies that leverage technology to improve access and efficiency.
Patient privacy and the trust factor
Trust forms the foundation of mental health care. When someone shares their personal health information and emotional experiences with a provider, that disclosure depends on confidence that their information remains private and that the professional genuinely understands their experiences. A patient discussing their anxiety symptoms, for instance, must feel secure that sharing vulnerable details about panic attacks or traumatic experiences won’t lead to judgment or privacy breaches before they disclose these critical details. Without that trust, the patient could struggle to open up.
Our survey shows that 70% of individuals expressed significant worry about the privacy and security of their mental health data when using AI-powered tools. This concern stands out against a backdrop of increasing healthcare data breaches and heightened digital privacy awareness.
Confidence in AI’s capabilities remains limited. Only 18% of survey participants believe AI tools are “very reliable” for providing mental health support. This skepticism could reflect both the novelty of these technologies and uncertainty about their performance compared to traditional care.
Three key concerns about AI mental health tools emerged consistently in our findings:
First, 60% of people worry about losing empathy and connection in their care journey. For about 44% of patients in a separate study, having an in-person therapeutic relationship with a human provider is important to them. This widespread concern highlights why AI should enhance rather than replace human clinicians.
Second, our survey found that 55% question the accuracy of assessments or recommendations that AI might provide. Without clear evidence of reliability or clinical validation, many hesitate to trust algorithmic judgment on something as personal as mental health.
Third, 36% express concern about potential bias in AI algorithms that could affect care quality. This awareness reflects growing public discourse around AI ethics and representation.
General perceptions around AI in mental health tilts toward caution, with 40% opposing its use compared to 32% supporting it. The remaining participants maintain a neutral stance, suggesting they could be persuaded either way based on how these tools develop.
For healthcare organizations considering AI integration, these findings highlight the importance of transparent implementation that addresses privacy concerns, demonstrates reliability, and preserves therapeutic connection throughout the care experience.
Strategic opportunities for integration
Our survey reveals that AI acceptance varies significantly by function. While only 18% believe AI tools are “very reliable” overall, comfort levels increase substantially when discussing specific applications like appointment scheduling or administrative support. This function-specific pattern, combined with demographic receptivity, points toward several practical pathways for healthcare organizations to integrate AI meaningfully into their behavioral health services.
Integration with existing platforms shows strong potential. One-third of survey participants indicated they would be more likely to use AI-powered mental health tools if they were incorporated into services they already use, such as telehealth platforms or health insurance portals. This suggests embedding AI capabilities within familiar systems could be more effective than launching new standalone applications that require additional adoption steps.
Based on these findings, healthcare organizations might consider these promising applications:
- Administrative assistance: AI can optimize scheduling systems, reduce paperwork, and identify utilization patterns to inform resource allocation. This keeps AI focused on operational tasks rather than clinical decision-making while ensuring patients receive timely care based on provider-determined priorities.
- Information management: AI can assist with gathering and organizing pre-appointment information, helping clinicians prepare while keeping all clinical evaluations and treatment decisions in the hands of licensed providers.
- Targeted engagement: Custom approaches could help reach populations showing higher receptivity to technology-assisted care models, particularly parents and men who demonstrated greater openness in our survey.
These opportunities highlight AI’s true potential in behavioral health care: as a supportive tool that amplifies clinical expertise rather than attempting to replace the irreplaceable human judgment essential to quality care.
Building the human-AI partnership in mental health care
For AI to gain broader acceptance in mental health care, our survey identified several key factors that could significantly increase consumer trust. When asked what would make them more comfortable with AI-powered mental health tools, survey participants highlighted these top factors:
- Professional collaboration (39%): Mental health experts should be deeply involved in creating, training, and validating AI tools, ensuring clinical expertise is incorporated into technology development.
- Data privacy (35%): Robust encryption, clear retention policies, and transparent data governance must meet or exceed healthcare compliance standards for sensitive mental health information.
- Algorithmic transparency (34%): Providing clear explanations of how AI makes assessments or recommendations to avoid “black box” decision-making that operates without accountability.
- Human accessibility (32%): Ensuring seamless transitions to human clinicians when needed, in order to reinforce continuity of care and promote patient confidence in the technological support system.
- Institutional endorsement (27%): Approval from established healthcare organizations could lend credibility and reassurance to consumers considering AI-powered tools.
What might this human-AI partnership look like in practice? Consider an example where a telehealth platform uses AI to analyze appointment patterns. The system identifies that certain visit types consistently run longer than scheduled, creating cascading delays throughout the day. By flagging this pattern, the AI supports schedulers and clinicians in making informed adjustments to improve patient experience without removing human judgment from the equation.
How Iris is shaping the future of AI in behavioral health care
At Iris Telehealth, we view these survey findings as confirmation of our approach to technology integration. Rather than pursuing AI as an end itself, we focus on applications that enhance operational efficiency while preserving clinical judgment.
This philosophy comes to life through Iris Insights, our data visualization platform that addresses the very concerns highlighted in our survey. By focusing on operational metrics rather than clinical decision-making, we’ve helped partners achieve 38% improvement in depression symptoms over eight weeks while maintaining the human connection patients value. The platform exemplifies how AI can meaningfully support behavioral health care when implemented with attention to privacy and transparency. Our commitment to this technology is also exemplified in our recent evolution of Iris Insights and its risk-stratification analytics capabilities.
Want to learn how your organization can thoughtfully incorporate AI to enhance behavioral health services while maintaining the human connection patients value? Contact us today to learn more about our services.
