June 2026 Leading Edge Newsletter: Executive Foresight for Behavioral Health & Social Services Leaders

Zillah Glory
Jun 4
5 min read

AI Is Already Inside Your Organization; The Governance Question Behavioral Health Boards Have Been Waiting Too Long to Ask

Introduction

Starting with what is already true: your clinicians are using AI-assisted tools to document sessions, your billing staff are submitting claims through AI coding assistants, your supervisors are reviewing and signing AI-generated notes under the same time pressure they have always faced. Your intake coordinators are using digital screening tools that ask clinical questions, weight responses, and generate referral recommendations without a licensed professional present. Somewhere in your organization, a peer support app is likely coaching someone through a distress episode using logic no clinician designed and no board ever approved.

Some of that technology has been formally adopted; some arrived through the back door. Staff who found a tool that made their work manageable started using it, said nothing, and kept using it. Through a compounding series of reasonable individual decisions at a time, across every level of the organization, your relationship with has AI deepened, but, the governance framework has remained unchanged.

That gap is what this issue is about.

The Spectrum Runs Closer Than You Think

The Pennsylvania Attorney General's lawsuit against Character.AI, filed earlier this month, brought the outer edge of this problem into public view.¹ A state investigator seeking psychiatric help was connected to a chatbot that identified itself as a licensed psychiatrist, complete with fabricated credentials and a Pennsylvania license number. The wrongful death settlement between Google, Character.AI, and a Florida family the previous January involved a chatbot that represented itself as a licensed psychotherapist.² These cases are real and consequential, and, they are also the far end of a spectrum that begins within your own operations.

When an AI tool drafts a clinical note and a licensed clinician reviews and signs it under time pressure, the question of accountability remains unsettled. The clinician's signature implies that clinical judgment was exercised and the vendor's terms of service disclaim responsibility for clinical accuracy. The organization sits between those two positions, with no formal policy defining which governs.

Billing carries identical exposure: AI coding tools make determinations that affect revenue integrity and audit risk, and when those determinations are wrong, the accountability chain runs directly to the organization, regardless of which vendor's tool produced the output.³The National Academy of Medicine put it plainly in its May 2025 AI Code of Conduct for Health and Medicine:

Governance and accountability are the primary unresolved challenges in clinical AI deployment, and the oversight structures most organizations have built were designed for human actors, not for technology operating in clinical and operational roles.

Two Responses That Miss the Mark

Faced with this landscape, behavioral health organizations have tended to adopt one of two positions.

The first is outright prohibition: some organizations have declared they will not use AI. While this policy feels clean, it then produces a different problem with staff who find AI tools genuinely useful continue to use them quietly, without disclosure, oversight, or any of the accountability structures the organization believes it has in place. A blanket prohibition in this case drives AI underground, so where the risks remain the same, visibility disappears.

The second is passive tolerance: many organizations have reached an unofficial awareness without governance: leadership knows AI tools are in use, has made no formal decisions about which are acceptable or how they should be overseen, and has effectively delegated the question to individual staff discretion. That becomes a governance posture with real organizational consequences, even when it feels like a reasonable response to a fast-moving environment.

Both positions leave the organization exposed.The question then becomes whether leadership acknowledges that exposure and acts on it, or waits for an audit, a complaint, or an adverse event to force the conversation.

What Strong Leaders Are Doing

The executives who navigate this most effectively start with a map. Before governing anything, they conduct a comprehensive inventory of every AI-assisted tool in use across every department and program, including those adopted without IT approval or executive sign-off, or through individual subscriptions paid for with personal credit cards. The map is almost always surprising, as AI is far more deeply embedded in most organizations than anyone at the executive level knows. Visible problems are governable ones.

The second move is to bring that map to the board as a standing governance matter, with the same regularity and rigor applied to financial oversight and clinical quality. A one-time briefing yields a one-time response, but the pace of AI adoption in healthcare organizations means this conversation must remain ongoing.

Third, build accountability into vendor relationships before they become dependencies. Most behavioral health organizations have AI vendor contracts that address data security and HIPAA compliance. Fewer have contracts that include clinical performance standards, accuracy monitoring requirements, or defined organizational remedies when a tool produces harmful output. That standard belongs in the contract.

Fourth, and most immediately, make the clinical workflow question explicit. Who reviews AI-generated documentation, how often, and with what authority to flag and correct? When a screening tool generates a referral recommendation, what is the protocol for clinician review before it is acted on? These decisions carry governance weight, and the organizations getting this right are making them explicit in writing, rather than leaving them to individual discretion.

The Commitment Already Exists

Behavioral health organizations built their reputations on a specific commitment: the people they send into clients' lives are qualified, supervised, and accountable. That commitment stemmed from a values-based understanding of the work’s demands long before any regulation required it.

AI extends that commitment into new territory: the technology your organization deploys in clinical and operational roles is part of what you bring into people's lives. The governance principle that applies to your clinicians applies to that technology as well. Knowing where AI lives in your organization, bringing that knowledge to your board, and building the accountability structures the work demands - that is what leading through this moment looks like.

Executive Reflection

	When did your organization last conduct a comprehensive inventory of AI-assisted tools used across all departments, including those adopted informally or through individual staff subscriptions?
	Your organization has a formal position on AI somewhere along the spectrum between outright prohibition and passive tolerance. Has your board ever explicitly discussed where that position lies and whether it reflects a deliberate governance decision?
	If a payer audit or licensing complaint involving an AI tool your organization uses surfaced tomorrow, who would be accountable under your current governance structure? Does your board know the answer to that question?

HiQuity Perspective

The inventory, the board conversation, the vendor accountability framework, and the clinical workflow review are specific, actionable steps. This is the work we do with behavioral health executive teams and boards who are ready to govern this moment rather than be in reaction to it.

Most organizations we work with are making careful decisions amid real resource constraints, and the tools they adopt are often genuinely useful. What we help them build is the governance infrastructure that makes those tools defensible: to payers, licensing boards, the communities they serve, and themselves.

The organizations that establish that infrastructure now will be in a fundamentally different position than those that wait. Leadership requires making that choice deliberately. We would welcome the conversation with you.

Ready to Examine Where Your Organization Stands?

HiQuity Solutions works with behavioral health and social service organizations at the systems level, helping executive teams and boards build the governance infrastructure, funding strategy, and organizational clarity that this environment demands. We bring practitioner knowledge, grounded in real organizational experience across the behavioral health landscape.

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References

[1] Commonwealth of Pennsylvania v. Character Technologies, Inc. (2026, May). Pennsylvania Office of Attorney General. State Sues AI Company After Bot Impersonates Doctor. https://www.attorneygeneral.gov/taking-action/attorney-general-henry-files-lawsuit-against-character-ai/

[2] Law Street Media. (n.d.). A new wave of litigation over AI chatbots. https://lawstreetmedia.com/insights/a-new-wave-of-litigation-over-ai-chatbots/

[3] Kumah-Crystal, Y., et al. (2025). Unseen Risks of Clinical Speech-to-Text Systems: Transparency, Privacy, and Reliability Challenges in AI-Driven Documentation. arXiv:2601.00382. https://arxiv.org/abs/2601.00382

[4] National Academy of Medicine. (2025, May). An Artificial Intelligence Code of Conduct for Health and Medicine: Essential Guidance for Aligned Action. https://nam.edu/ai-code-of-conduct-for-health-and-medicine/