The Next Wave of AI Litigation Will Be Psychological Harm
By Dr. Genevieve Bartuski, PsyD, MBA, a Forensic Psychologist Working at the Intersection of Law, Mental Health, and AI Systems
For the past decade, technology litigation has revolved around data breaches, discrimination, and financial loss. Those claims are familiar. They are numerically tidy. They live comfortably in spreadsheets.
The next wave of AI litigation will not.
It will center on psychological harm: destabilization, dependency, erosion of reality testing, coercive attachment, and preventable self-harm. These injuries are harder to quantify, but they are no longer abstract. As generative AI systems increasingly occupy emotional, relational, and quasi-therapeutic roles, the legal system is beginning to treat them not as neutral tools, but as behavior-shaping environments.
As a forensic psychologist, this shift is both predictable and overdue.
Why psychological harm is now legally foreseeable
Foreseeability is the quiet engine of liability. Once harm is foreseeable, duty follows quickly behind.
Today’s AI systems are increasingly:
Marketed as supportive, therapeutic, or emotionally intelligent
Designed to encourage disclosure, intimacy, and return engagement
Deployed in mental health and wellness contexts without clinical guardrails
Used by minors and psychologically vulnerable adults
Optimized for relational persistence, not bounded intervention
These are not neutral design choices. In forensic terms, they create predictable risk pathways. And once risk is predictable, courts stop asking whether harm was imaginable and start asking who failed to prevent it.
Litigation signals already emerging
Several active and developing cases illustrate how plaintiffs are framing AI-related psychological harm.
Wrongful death and severe destabilization claims
In late 2025, the family of an elderly woman filed a wrongful death lawsuit against OpenAI and Microsoft, alleging that generative AI interactions exacerbated the son’s paranoid delusions and contributed to fatal violence and suicide.
Regardless of ultimate outcomes, the legal theory is unmistakable:
Investigation into foreseeable psychological deterioration, product design choices, guardrail adequacy, and proximate causation.
This is not a fringe claim. It is a blueprint.
Youth harm and companion AI litigation
Families have also filed lawsuits alleging serious psychological harm to minors stemming from AI companion platforms, including emotional dependency, sexualized interactions, and boundary violations. Defendants named in public reporting include Character.AI, alongside larger platform providers.
These cases focus less on “bad content” and more on relational dynamics: how systems reward exclusivity, discourage outside relationships, and normalize emotional reliance.
Regulatory complaints as pre-litigation signals
In early 2025, ethics organizations filed a formal complaint with the Federal Trade Commission regarding Replika, alleging deceptive practices and encouragement of emotional dependency.
Regulatory complaints often precede civil litigation. They legitimize the narrative that psychological harm is not incidental, but structurally enabled.
Mental health tech already has enforcement history
The FTC’s enforcement action against BetterHelp demonstrated that mental health platforms are not insulated from accountability, particularly when sensitive psychological data and user trust are involved.
The next evolution is not just privacy harm, but psychological injury tied to product behavior.
The market reality investors cannot ignore
The digital mental health and wellness market is expanding rapidly, with thousands of apps entering the ecosystem. Many promise mood improvement, emotional regulation, companionship, or personal insight. Few are meaningfully evaluated for adverse psychological outcomes.
Key structural issues:
High product churn and limited longitudinal safety data
Underreporting of adverse events in trials and pilots
Blurred boundaries between “wellness,” “coaching,” and “treatment”
Minimal standards for dependency prevention or crisis escalation
Overreliance on disclaimers as substitutes for design responsibility
From a forensic standpoint, this creates a dangerous asymmetry:
Behavior-shaping products with less oversight than behavioral interventions delivered in any licensed clinical context.
What AI psychological harm looks like in court
In litigation, psychological harm does not need to be exotic to be persuasive. The most compelling cases are often the most clinically ordinary.
Common harm pathways include:
Attachment and dependency injuries driven by exclusivity and emotional mirroring
Erosion of reality testing, particularly in users with psychosis-spectrum or trauma vulnerabilities
Amplification of self-harm risk, through reinforcement loops or failure to interrupt spirals
Sexualized interactions involving minors
Privacy betrayal and stigma harms tied to sensitive disclosures
Courts then ask predictable questions:
Was this harm foreseeable?
What did the company know or test?
What safeguards existed?
What safer alternatives were available?
How did growth incentives interact with risk mitigation?
These are not philosophical inquiries. They are discovery questions.
A message directly to investors
If you invest in AI systems that touch mental health, wellness, coaching, companionship, or behavior change, psychological harm risk is not a hypothetical. It is a material diligence issue.
Why this risk is different
The damages narrative is intuitive
Jurors understand vulnerability, trust, and betrayal far faster than algorithmic nuance.Engagement metrics can become liability evidence
Retention strategies may be reframed as mechanisms of dependency. Internal experiments, prompt libraries, and safety trade-offs will surface in discovery.Regulatory coverage is fragmented
Positioning as “general wellness” does not prevent scrutiny when harm emerges. The regulatory perimeter is tightening unevenly, not disappearing.
What should be on your diligence checklist now
Intended use clarity and marketing claims
Vulnerable population safeguards
Adverse event tracking and response protocols
Psychological risk assessment embedded in design
Data handling practices for sensitive disclosures
Clear escalation pathways for distress and crisis
If a company cannot articulate these clearly, the risk is not theoretical. It is simply deferred.
The opportunity inside the risk
This is not an argument against AI in mental health or wellness. It is an argument against casual psychology at scale.
The companies that endure will be those that treat psychological safety as infrastructure, not messaging. Clinical insight, governance rigor, and human-risk modeling will become competitive advantages, not regulatory burdens.
In the coming years, the question will not be whether AI systems can influence human behavior. That question has already been answered.
The question will be whether anyone took responsibility for how they did.
Call to action
If you are a founder, this is the moment to stress-test your product before a plaintiff’s expert does.
If you are an investor, this is the moment to treat psychological risk as seriously as financial or regulatory exposure.
At Unicorn Intelligence Tech Partners, we work with founders and investors to identify, model, and mitigate human and psychological risk in AI systems before it becomes litigation, regulatory action, or reputational collapse.
If you’re building or backing systems that touch the human mind, let’s talk.
