Artificial intelligence is becoming part of behavioral health marketing, admissions, call management, reporting, and operational workflows. The technology can help providers respond faster, analyze more information, and reduce repetitive administrative work. It can also create serious privacy, compliance, and patient-experience risks when implemented without clear controls.
To explore where AI provides meaningful value and where behavioral health organizations need to proceed carefully, we spoke with Arin Gharapetian, founder of Brand House.
Gharapetian has more than 10 years of experience in the behavioral marketing space, including working directly inside treatment centers. His background extends beyond agency marketing. He has helped implement and manage CRM platforms, call-center technology, analytics, attribution systems, website infrastructure, lead-management processes, and AI-supported tools.
Through Brand House, Gharapetian now helps organizations connect marketing strategy with the systems used to generate, manage, and respond to patient inquiries. The agency provides SEO, paid advertising, website development, analytics, and addiction treatment marketing services designed around the operational realities of behavioral health organizations.
Where is AI having the greatest impact in behavioral health marketing?
Arin Gharapetian: The most valuable uses are not always the ones receiving the most attention.
When people hear AI and marketing, they often immediately think about content generation. That is one application, but it is not where I see the greatest operational value for behavioral health providers.
AI can be much more useful for analyzing data, identifying patterns, supporting communications, and connecting systems that have historically operated separately.
A behavioral health organization might receive inquiries through Google Ads, organic search, website forms, phone calls, live chat, professional referrals, and other channels. Marketing may track the original source, while admissions tracks whether the person scheduled an assessment or entered treatment. Those systems do not always communicate effectively.
AI-supported tools can help organizations review advertising search terms, campaign performance, phone-call outcomes, missed calls, lead-response times, follow-up activity, website behavior, admissions results, and the reasons qualified inquiries do not move forward.
The goal is not to let AI make every decision. It is to use the technology to organize large amounts of information and identify patterns that people can investigate.
For example, a call-analysis platform may reveal that families repeatedly ask about a specific insurance plan, level of care, or admissions requirement. That information can then be used to improve website content, paid advertising, call scripts, and staff training.
AI identifies the pattern. The organization still needs experienced people to determine what it means and what should change.
What are behavioral health providers getting wrong about AI?
Gharapetian: A common mistake is starting with the tool instead of the problem.
Organizations hear that they need AI, so they begin evaluating platforms without first defining what they are trying to improve. That often leads to purchasing technology that adds complexity without solving anything important.
A better starting point is a specific operational problem, such as unanswered after-hours calls, inconsistent admissions follow-up, disconnected marketing and CRM data, or a lack of visibility into lead quality.
Once the problem is clear, the organization can determine whether AI, traditional automation, staff training, or a different process is the appropriate solution.
Another mistake is assuming AI should replace the people already doing the work. In behavioral health, many interactions require empathy, judgment, and an understanding of circumstances that an automated system may not recognize.
The goal should be to make staff more effective, not remove people from every interaction.
How can AI improve website communication?
Gharapetian: AI chat agents can provide real value when they are carefully limited and trained on approved information.
A behavioral health website may receive visitors at all hours. Some people are researching for themselves, while others are trying to help a family member. They may not be ready to call, but they still need help finding information.
A properly configured chat agent can help visitors find information about programs, levels of care, locations, admissions hours, insurance processes, and how to request a callback. It can also guide users to relevant pages or collect basic inquiry information for follow-up.
The limits need to be clear.
A chat agent should not diagnose someone, recommend a clinical treatment plan, determine eligibility for care, or guarantee that insurance will cover treatment. It should only answer questions using information the organization has reviewed and approved.
There must also be a defined process for situations involving self-harm, overdose, withdrawal, abuse, or another urgent concern. A general automated response is not an acceptable substitute for a trained professional or an appropriate crisis resource.
Visitors should also know when they are communicating with an automated system. An organization should not create the impression that someone is speaking with a clinician or admissions representative when they are not.
What about AI voice agents and call-center systems?
Gharapetian: Voice technology is one of the most important areas because phone calls remain central to behavioral health admissions.
AI voice agents can support after-hours call answering, basic routing, callback requests, appointment requests, and responses to approved administrative questions.
AI can also be used after calls occur. Call transcription and conversation analysis can help leadership identify long hold times, calls ending without a next step, inconsistent insurance explanations, unanswered questions, and missed follow-up opportunities.
Instead of manually listening to hundreds of recordings, teams can use AI-supported analysis to surface calls that require closer review.
That can improve marketing, admissions training, and overall operational performance.
The danger comes when organizations try to use voice agents as a complete replacement for trained admissions staff. A person calling a behavioral health provider may be frightened, impaired, emotionally overwhelmed, or dealing with an urgent situation.
An automated system can assist with routing and basic information. It should not become a barrier between someone seeking help and a qualified person who can respond appropriately.
How can AI support CRM and admissions operations?
Gharapetian: CRM systems are often where the gap between marketing and admissions becomes visible.
Marketing may report that it generated a certain number of calls or forms, but that does not tell leadership what happened afterward. Admissions may know that someone did not enter treatment, but the original advertising source or website interaction may be missing.
AI and automation can help assign inquiries, create follow-up tasks, summarize prior communications, flag leads that have not received a response, identify duplicate records, and connect marketing sources with admissions outcomes.
This can help organizations move beyond surface-level metrics such as call volume and form submissions.
A campaign that generates fewer calls may produce more qualified admissions opportunities than one that generates a high volume of unrelated inquiries. Without the right systems, the organization may never see that distinction.
AI can help organize and analyze the data, but it should not independently make clinical placement decisions or determine whether someone is appropriate for a particular level of care. Those decisions require qualified human involvement.
Should behavioral health organizations use AI to write their marketing content?
Gharapetian: AI can support research and content workflows, but it should not replace subject-matter knowledge, original thinking, or professional review.
Behavioral health content deals with sensitive and sometimes clinical topics. Generic AI-generated writing may contain inaccurate claims, overly broad statements, fabricated details, or language that does not reflect how the organization actually provides care.
There is also a credibility problem. If every provider publishes interchangeable content, none of them clearly communicates why its program is different or who it is best positioned to help.
AI may be useful for organizing research, identifying common questions, comparing content coverage, reviewing structure, and finding gaps in existing information.
The final content should still reflect the provider’s actual programs, staff expertise, admissions process, clinical approach, locations, and patient population.
That requires input from real people inside the organization.
What should providers understand about HIPAA before using AI?
Gharapetian: The first step is understanding exactly what information the AI system will receive, store, process, or transmit.
HIPAA does not apply to a platform simply because the platform uses AI. Its application depends on the organization, the information involved, and how that information is being handled.
The HIPAA Privacy Rule protects certain individually identifiable health information, while the Security Rule requires covered entities and business associates to use administrative, physical, and technical safeguards to protect electronic protected health information.
When a technology vendor creates, receives, maintains, or transmits protected health information on behalf of a covered entity or business associate, the vendor may also have obligations under HIPAA.
A business associate agreement may be required, but signing one does not automatically make a system or workflow compliant.
The organization still needs to understand what information enters the platform, where it is stored, who can access it, whether subcontractors receive access, how long the information is retained, and whether it is used to train shared AI models.
The organization must also evaluate risks and vulnerabilities affecting electronic protected health information and implement appropriate safeguards. An AI tool connected to calls, chats, forms, or CRM records should therefore be reviewed as part of the organization’s broader security and risk-management process.
Are website analytics and advertising platforms part of this risk?
Gharapetian: They can be.
Healthcare organizations sometimes treat advertising pixels and analytics scripts as harmless because they are common on ordinary business websites. Behavioral health websites are different because a page visit, form submission, URL, search term, or interaction may reveal sensitive information about a person’s health interests or treatment needs.
HHS has issued guidance addressing the privacy and security risks associated with online tracking technologies used by covered entities and business associates.
Providers should not install every available analytics or advertising tool and assume the implementation is acceptable. They need to evaluate what data is being collected, where it is being sent, and whether that use is consistent with applicable privacy obligations.
HIPAA is not the only consideration. Certain health applications and technologies that are not covered by HIPAA may still fall under the FTC’s Health Breach Notification Rule.
This is one reason marketing, operations, compliance, and technology teams need to work together. Privacy decisions cannot be left solely to the person installing the software.
Are there additional concerns for addiction treatment providers?
Gharapetian: Yes. Substance use disorder treatment providers may also need to consider the federal confidentiality requirements commonly referred to as 42 CFR Part 2.
Part 2 protects the confidentiality of certain substance use disorder patient records and governs when and how those records may be used or disclosed.
The exact application depends on the organization, the records involved, and the circumstances. That determination should be made with qualified legal and compliance guidance.
Operationally, addiction treatment providers should be cautious because many routine marketing and admissions interactions can reveal highly sensitive information.
Examples may include a form requesting help for opioid use, a recorded call discussing withdrawal, a chat conversation about alcohol treatment, a CRM note describing prior care, or insurance information connected to a treatment inquiry.
The fact that information originated through a marketing channel does not automatically make it ordinary marketing data.
What questions should a provider ask an AI vendor?
Gharapetian: Providers should ask direct questions and require clear answers.
They should understand what problem the platform solves, what information it collects, where that information is stored, who can access it, and whether customer data is used to train shared models.
They should also ask which subcontractors are involved, how long calls and transcripts are retained, whether retention settings can be adjusted, and whether records can be deleted or exported.
If a business associate agreement may be required, the provider should confirm whether the vendor will sign one and review what the agreement actually covers.
Providers should also ask how the system handles inaccurate responses, how urgent communications are escalated, whether users can easily reach a person, and what happens to the data when the contract ends.
A polished sales presentation is not enough. The provider needs to understand the actual data flow and operating process.
What is the safest way to begin implementing AI?
Gharapetian: Start small and solve one defined problem.
An organization does not need to connect an AI platform to every system on day one. In many cases, that is the wrong approach.
A safer process begins by selecting a specific use case, such as reducing unanswered after-hours calls, improving lead routing, or making campaign reporting more efficient.
The organization should then document what information the system will receive, where it will go, who will have access, and how long it will remain available.
The vendor should be reviewed carefully, including its contracts, privacy terms, security controls, retention policies, model-training practices, subprocessors, and incident procedures.
The initial implementation should be limited. The platform should not receive more information or system access than it needs to perform the defined task.
Clear escalation rules should be established, especially for patient-facing chat and voice systems. The organization should test real outputs and assign someone internally to monitor performance, correct information, and handle exceptions.
The results should be measured against more than efficiency. Providers should also evaluate accuracy, response time, lead quality, patient experience, staff workload, escalation failures, and admissions outcomes.
Will AI replace behavioral health marketing and admissions teams?
Gharapetian: It will change how people work, but it should not eliminate the need for experienced people.
AI can process data faster, summarize conversations, route inquiries, identify patterns, and automate repetitive tasks. Those capabilities can make teams more effective.
But AI does not take responsibility for the outcome. It does not understand a provider’s mission, clinical philosophy, reputation, operational limitations, or community in the same way the organization’s people do.
It also cannot replace the empathy required when someone is seeking behavioral health or addiction treatment.
AI should not replace clinical assessment, crisis intervention, compassionate admissions conversations, compliance review, marketing strategy, original organizational messaging, or human accountability.
The strongest AI implementation is not the one that automates the most. It is the one that solves a meaningful problem while protecting sensitive information and preserving the human experience.
What should behavioral health leaders take away from this?
Gharapetian: AI should be treated as part of a larger operational system, not as an isolated marketing feature.
A chat agent affects the website, admissions team, privacy process, and patient experience. A call-analysis platform affects staff training, data retention, CRM records, and compliance. An automated reporting tool affects how leadership interprets marketing performance and makes budget decisions.
Organizations need to consider all of those connections.
Behavioral health providers can benefit from AI, but implementation should begin with a clear use case, a documented understanding of the data, careful vendor review, and defined human oversight.
The technology should help people work more effectively. It should not weaken the trust, privacy, empathy, and accountability on which behavioral healthcare depends.
This article provides general marketing and operational information and does not constitute legal, regulatory, privacy, security, or compliance advice.
