Use case 9: Real-time guidance AI companion
Description:
An AI-powered real-time guidance companion analyzes client conversations and provides real-time guidance, then suggests evidence-based next steps (such as follow-up questions) and prompts that will help care providers enhance therapeutic engagement (such as focusing on active listening).
Example scenario:
During a routine counseling session, a care provider listens as the client talks about feeling anxious and overwhelmed in daily life. Unsure how to proceed, the care provider hesitates.
The AI companion analyzes the conversation in real time, recognizing meaningful phrases related to anxiety and low mood. It suggests evidence-based next steps to the care provider, such as exploring the client’s coping strategies and supporting the client in approaching rather than avoiding anxiety-inducing situations. The companion also tracks the care provider’s communication style, noting that they are speaking most of the time. It prompts the care provider to shift to a more listening-focused approach to enhance engagement.
After the session, the AI companion generates feedback on how the care provider responded to its suggestions and provides any recommended follow-up actions. The care provider feels more confident, knowing they maintained therapeutic fidelity while receiving real-time guidance.
Opportunities unlocked:
The AI companion tool could address several challenges in mental health task sharing programs, including the following:
- Supervisor overload. A single supervisor often supports multiple providers, so their response times to urgent queries can be delayed. The AI companion could provide real-time guidance to care providers while staying aligned with intervention protocols, which will help reduce the need for immediate supervisor intervention and ease workload pressures.
- Protocol drift. Supervisors may not be able to observe sessions directly and ensure that care providers are following protocol during and after the program. The AI companion could bridge this gap by offering on-the-spot recommendations and structured guidance so that providers can receive timely support regardless of their location.
- Variable oversight. Supervisors may vary in their focus day-to-day, sometimes prioritizing administrative tasks rather than overseeing clinical fidelity. The AI companion could consistently reinforce evidence-based protocols, ensuring consistent oversight and high-quality care.
How could the end user(s) benefit from this solution?
The primary end user who could directly benefit from this solution is:
- Care provider. Care providers could receive real-time guidance, suggested next steps, and structured feedback, allowing them to navigate complex cases with confidence and competence.