Mental health and addiction care are changing. Care teams now deal with more complex cases and urgent needs than ever. People face stress, loss, substance use, and mental health struggles, all at the same time.
This makes it harder for doctors, therapists, and case workers to stay on the same page. They need tools that help them act fast, stay informed, and make better choices for each person.
Alex Shohet, Founder and CEO of Evergreen Fund, and Co-Founder and CEO of MyAlyce and Red Door Life has spent over 20 years working in mental health and addiction care. He started in the tech world, but later focused on building better support systems for people in recovery.
His approach uses the 12 Dimensions of Human Health and Wellness model. It looks at areas like money, health, family, and beliefs.
Alex and his team use AI to track progress, plan care, and respond to daily changes. He also brings data from wearable devices to support patients in real time. He focuses on harm reduction, aiming to lower risks while helping people heal safely.
In this article, you’ll learn how AI in mental health supports care teams. We’ll explore how AI helps with daily planning, medication tracking, hard decisions, and future tools like wearables.
How AI in Mental Health Supports Addiction Care
AI is now a regular tool in mental health and addiction services. It helps teams work faster, ask better questions, and find useful support options without always turning to search engines. Many professionals now use AI daily to answer questions and plan care.
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Moving From Search to Smarter Tools
Instead of looking things up on Google, many now rely on AI tools like ChatGPT. They offer quicker, more direct answers. Some also try tools like Gemini, but results can vary depending on the version.
Gemini 2.5 Pro, for example, gives deeper answers than the regular version. It’s worth checking which version is being used to get better results.
Using a Simple Care Model
One helpful method is called the 12 Dimensions of Human Health and Wellness. This model looks at key areas like:
- Relationships
- Work and money
- Mental and physical health
- Social life
- Spiritual or personal beliefs
AI reviews changes in these areas. For example, if someone has a fight with their partner or loses a job, the system notices. It helps the care team decide what support to offer and which questions to ask.
Maintaining Privacy in AI in Mental Health
The AI system doesn’t use names or personal details. Each person gets a private profile with general info. Updates happen weekly, not monthly.
This gives a more accurate view of someone’s progress. The care team includes experts like psychiatrists who focus on real health needs, not just quick fixes.
AI helps make the process smoother, not colder. It supports the team, gives helpful ideas, and helps people get the care they need.
Why AI in Mental Health Became a Daily Tool
Mental health and addiction care change from case to case. Some situations need quick and clear action. AI now supports those moments. It gives teams fast input when pressure is high and time is short.
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Bringing the Care Team Together
A good care plan often needs:
- A psychiatrist in medicine
- A therapist for mental health support
- An advocate for daily needs
These roles connect to many parts of health. But if updates are missed, problems can happen. For example, confusion grows if the doctor changes a medicine but the therapist doesn’t know.
That’s why the providers use AI to stay on the same page. Every week, they share updates with the AI. In return, it offers clear suggestions that keep everyone aligned.
Handling Tough Moments with AI in Mental Health
Some patients use drugs like fentanyl during care. Pulling them out of treatment can raise risks. The focus stays on lowering harm for them and others. This approach is harm reduction.
AI helps the team manage these cases. When a tough case comes in, the team enters the facts. The AI replies with clear steps. It offers safety tips, helpful questions, and ways to keep control.
A Simple Start That Grew
It all starts with curiosity. One small question leads to better answers. Over time, the care providers:
- Shares weekly updates
- Adds custom treatment notes
- Uploads research and trusted sources
As AI learns, its support becomes smarter. It helps the team notice patterns, stay organized, and carefully respond. Now, AI isn’t just a tool for answers; it’s part of improving care for every person.
How AI in Mental Health Supports Daily Care and What’s Next
AI now helps with daily tasks in mental health and addiction care. It started as a tool for quick answers. Once care teams saw value, they trained it using real case data. This made the system more helpful, accurate, and grounded in real-life needs.
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Tracking Medication and Behavior
In treatment, patients often take many medications. These can interact in ways that are hard to track. By entering details like which medications were taken, missed, or changed, AI helps the team spot patterns.
It doesn’t replace doctors but helps them stay informed and focused on the most important changes.
Helping the Team Work Smarter
AI plays a key role in supporting two main roles:
- Advocates (case managers) – They gather and share information with the team. AI helps summarize the most important details, making it easier for therapists and doctors to catch up quickly.
- Clients with brain injuries or extra challenges – AI helps create to-do lists and find helpful exercises, like neurofeedback or TMS.
Exploring Psychedelics and Brain Health
Some teams explore how psychedelics might help. Small doses or guided sessions, like with ayahuasca, show promise for a few people. AI tracks the effects and links them to the care plan, helping improve results.
What’s Next: Real-Time Data from Wearables
The next goal is to connect AI with wearables that track heart rate, sleep, blood sugar, and more. Combining this data with behavior updates gives AI real-time, personalized support.
In the future, the aim is for patients to use AI as their main tool, with help from their care team, to improve their recovery journey.
How Private AI Models and Data Integration Can Improve Care
AI is helping mental health and substance abuse care teams become more efficient. Private AI models allow professionals to use their data while keeping it safe and secure.
Using Private Models for Better Data Control
Private AI models work within the care team’s system, keeping sensitive data secure. Unlike commercial models, these private systems do not share or use data for future training. Using custom data, the AI can offer personalized insights while protecting patient privacy.
- Data stays within the team.
- No sharing of sensitive information.
- Offers personalized and secure support.
This method helps track important details like medication changes and patient behavior. It allows teams to make better decisions without risking data loss or privacy concerns.
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Integration of Wearable Data for Personalized Care
Wearables like Fitbits and Apple Watches collect health data like heart rate and sleep patterns. Connecting this data to AI will give the care team real-time information. This will help them provide more personalized support and improve decision-making.
Though wearable data is still in separate systems, new technologies aim to connect them. In the future, AI will combine this data with other health information to make care smarter and more effective.
The Future of AI in Mental Health
Technologies like Model Context Protocol (MCP) will allow data from different systems to connect. This will make it easier for teams to access all relevant information in one place.
As more systems become compatible, AI will continue to improve care. Teams can adapt quickly and use the best tools available to support their patients.
Conclusion
AI is now a steady part of mental health care. It helps teams work faster, stay updated, and make better choices. Instead of long meetings or guesswork, they get clear support in real time. This helps everyone stay focused on the person, not the process.
Moreover, private AI tools make it safer to use sensitive data. The care team keeps full control while using the insights AI provides. That balance helps patients feel more secure and heard.
Wearables like smartwatches can also add value. They give health data like heart rate and sleep, which AI uses to track changes. When combined with updates from the care team, this creates a full picture of a patient’s progress.
That said, AI does not replace the care team. It supports them. It helps therapists, doctors, and case managers stay in sync and respond faster when something changes. Everyone works together with more ease and clarity.
AI in mental health is not about using big words or complex tools. It’s about making care smoother, more personal, and easier to manage. As new tools grow, the support will only get better.
FAQs
How does AI in mental health help new patients who don’t have a diagnosis yet?
AI can ask early questions, spot warning signs, and help care teams decide what steps to take next.
Can AI in mental health work without the internet?
AI can work offline using saved data if built into private systems, but live updates need internet access.
Does AI in mental health help with anxiety and depression tracking?
Yes, AI can look at mood logs, behavior changes, and daily notes to spot patterns in mental health.
How often should teams update AI in mental health systems?
Weekly updates work best. They help the AI notice small changes and give real-time, useful advice.
Can family members be involved in AI in mental health care plans?
Yes, with permission, family input can be added. It helps build a clearer view of the person’s life.
