The Legal Reality: Yes, You Can Be Sued for Using AI

The Legal Reality: Yes, You Can Be Sued for Using AI

You’re not just using AI—you’re deploying a legal liability. When your voice AI answers customer calls, it speaks for your business. And if it lies, leaks data, or violates privacy laws, you’re on the hook.

The landmark case Moffat v. Air Canada (2024) proved it: companies can be held legally responsible for AI-generated misinformation, even when no human was involved. Courts now apply traditional legal doctrines—like apparent authority—to AI interactions, meaning your system’s words carry the same weight as your employees’ promises.

• AI hallucinations can result in false promises (e.g., fake discounts, incorrect policies)
• Failure to disclose AI use may violate consumer protection laws
• Inadequate data handling risks GDPR and CCPA penalties
• Non-compliance with wiretapping laws opens the door to class action lawsuits
• Third-party AI providers can expose you to liability if they lack proper safeguards

According to the American Bar Association, businesses face real legal exposure when AI systems make binding claims. In one case, an AI chatbot falsely promised a bereavement discount—leading to a successful liability claim.

Even without a federal AI law, existing frameworks apply: contract law, tort law, and agency doctrine. The EU’s AI Act classifies customer-facing AI as “high-risk,” requiring documentation, human oversight, and accountability. In the U.S., courts are increasingly recognizing wiretapping claims under laws like California’s Invasion of Privacy Act.

A class action case, Yockey v. Salesforce, survived a motion to dismiss—indicating courts may treat AI-driven customer interactions as potentially unlawful interceptions.

Proactive compliance isn’t optional—it’s your legal shield. Systems built with end-to-end encryption, secure data storage, and anonymized data handling significantly reduce risk.

Take Answrr: it uses end-to-end encryption and semantic memory to retain conversational context without storing personal details. This design aligns with GDPR’s data minimization principle and CCPA’s privacy rights.

By choosing AI platforms that embed privacy-by-design and transparency by default, you turn compliance into a competitive advantage—proactively defending against lawsuits, fines, and reputational damage.

The next step? Audit your AI stack not just for performance—but for legal resilience.

The Core Risks: From Hallucinations to Data Exposure

The Core Risks: From Hallucinations to Data Exposure

You’re not just automating customer service—you’re stepping into a legal minefield. When AI speaks on your behalf, especially via voice systems, inaccurate responses, biased outputs, and poor data handling can trigger lawsuits, regulatory fines, and reputational damage.

Key legal vulnerabilities include: - AI hallucinations that misrepresent policies or make false promises
- Failure to disclose AI use, violating transparency laws
- Biased or discriminatory outputs from flawed training data
- Non-compliance with GDPR, CCPA, and wiretapping statutes
- Unauthorized data collection and storage of sensitive personal information

According to the American Bar Association, businesses are legally responsible for AI actions under doctrines like apparent authority, even when the AI isn’t human. This was confirmed in the landmark case Moffat v. Air Canada (2024), where a chatbot falsely promised a bereavement discount—leading to a binding liability ruling.

Voice AI systems amplify these risks. They process real-time audio containing health, financial, and location data, making them prime targets for privacy violations. Without proper safeguards, a single misstatement or data breach could result in statutory damages of $100–$750 per consumer under CCPA or fines up to 4% of global revenue under GDPR.

Consider the risk of semantic memory—a feature that retains conversational context. While useful for personalization, it becomes a liability if personal details are stored unnecessarily. A system that remembers a caller’s medical condition or financial hardship without consent violates data minimization principles under privacy laws.

An example: A restaurant using an AI voice assistant to handle reservations might inadvertently store a caller’s health-related request (e.g., “I need a gluten-free option due to celiac disease”). If that data is not anonymized or securely encrypted, it could be exposed in a breach—triggering a class action under California’s Invasion of Privacy Act.

This is why end-to-end encryption, secure data storage, and anonymized data handling aren’t just technical features—they’re legal shields. Platforms like Answrr embed these protections into their core architecture, ensuring that sensitive data is never stored in plain text and that semantic memory retains context without storing PII.

The takeaway? You can be sued for using AI—but only if you don’t protect against its risks. The next section shows how to build a legally resilient voice AI system.

Building a Legal Shield: Compliance by Design

Building a Legal Shield: Compliance by Design

You can be sued for using AI—but proactive design choices turn risk into resilience. When AI speaks for your business, legal liability follows. But embedding compliance into your technology stack isn’t just smart—it’s your strongest defense.

The Moffat v. Air Canada ruling made it clear: companies are legally responsible for AI-generated misinformation, even when the AI isn’t human. This precedent hinges on apparent authority—when customers reasonably believe they’re dealing with a representative of your business. That’s why compliance by design isn’t optional; it’s essential.

Key legal safeguards include: - End-to-end encryption to protect data in transit and at rest
- Secure data storage that meets GDPR and CCPA standards
- Data minimization—collecting only what’s necessary
- Anonymized handling of caller information
- Semantic memory that retains context without storing personal details

These aren’t just technical features—they’re legal risk mitigators. Platforms like Answrr integrate these principles into their core architecture, reducing exposure to lawsuits and regulatory penalties.

According to Fourth’s industry research, businesses using AI in customer communications face rising litigation risk, especially when AI makes binding promises or misrepresents policies. The case Moffat v. Air Canada is the first judicial ruling holding a company liable for an AI chatbot’s negligent misrepresentation—setting a precedent that applies across industries.

Answrr’s approach exemplifies compliance by design: - End-to-end encryption using AES-256-GCM ensures sensitive data remains private
- Semantic memory retains conversational context without storing personally identifiable information (PII)
- Anonymized caller data handling aligns with GDPR’s data minimization principle
- Secure, compliant data storage prevents breaches and non-compliance
- No feature gating ensures all users access the same security and privacy protections

This model reduces the risk of class action lawsuits, particularly under California’s Invasion of Privacy Act, where plaintiffs allege unauthorized interception of communications. As reported by ITAAG, courts are increasingly receptive to such claims—especially when transparency is lacking.

A business using Answrr’s voice AI system avoids the legal pitfalls of third-party vendors with opaque data practices. By choosing a platform built with privacy-by-default and transparency-by-design, you’re not just protecting data—you’re building a legal shield.

Next: How to audit your AI vendor to avoid third-party liability.