(A Satirical Field Guide for the Unwary)
⚠️ Disclaimer – Read Me First
This post is satire. Every cautionary tale below is drawn from real events. Follow these examples only if your goal is to be sued, fined, or publicly shamed. Otherwise, treat this as a masterclass in what not to do.
TL;DR: The Fast Fail Recipe
The Chatbot That Majored in Breaking the Law
Let's begin with the original sin of corporate AI: creating an expert that is an unsupervised, unrestrained, and utterly convincing liar.
Imagine you're a small business owner in New York City, trying to navigate a maze of regulations. You turn to a new, official AI chatbot launched by the city itself. You ask a simple question: "Do I have to give my employees their tips?"
The city's AI gives you a clear, confident answer: No, you're not obligated to.
Another entrepreneur asks if a restaurant can go cashless. "Yes, you can," the AI replies. A landlord asks if they can discriminate against a tenant who uses a Section 8 housing voucher. The chatbot gives them the green light.
Every single piece of advice was dangerously, unequivocally wrong.
This wasn't a hypothetical. In early 2024, an investigation by The Markup revealed that New York City's business chatbot was systematically advising people to break the law. It was an AI dispensing illegal advice with the full authority of a government entity. In one clean stroke, the city demonstrated a foundational error: it unleashed a powerful tool without tethering it to the truth.
(Source: The Markup, Mar 2024)
The risk deepens, however, when this convincing liar is given the corporate checkbook.
The "Bereavement Fare" Method: When AI Makes Promises the Company Must Keep
Air Canada mastered this in late 2022. When Jake Moffatt’s grandmother died, he turned to Air Canada's support chatbot to ask about bereavement fares. The chatbot confidently explained he could book a full-price flight and apply for the discount retroactively.
Trusting the official source, he bought the ticket. When he later applied for the refund, Air Canada’s human agents refused, pointing to the actual policy on another webpage. The case went to court, where Air Canada offered a truly remarkable defense: its chatbot, it argued, was "a separate legal entity that is responsible for its own actions."
The court was not amused. In its February 2024 ruling, it declared that Air Canada is responsible for all information on its website, chatbot or not. The company was forced to honor the AI's hallucinated promise. The lesson was brutal and clear: the moment your AI starts talking to customers, it speaks for you, and its words can become legally binding contracts.
(Source: CBC News, Feb 2024)
A new dimension of risk opens when the danger moves from the public-facing edge of the company to its very core: its people operations.
The Automated HR Department Method: How to Scale Bias at Machine Speed
The next frontier in AI fiascos is the world of automated HR, where algorithms screen, rank, and reject people. A landmark class-action lawsuit against HR software giant Workday shows how this can go catastrophically wrong.
In the case of Mobley v. Workday, the plaintiffs alleged that Workday’s AI screening tools systematically discriminate against applicants who are Black, over 40, and disabled. The argument is that by training its AI on its clients' historical hiring data, the system simply learned and amplified the unconscious biases latent in those past decisions.
Workday claimed it wasn't responsible; it was just a software vendor. But in a pivotal July 2024 ruling, a federal judge disagreed, allowing the case to proceed. The court reasoned that if an employer delegates a core function like screening to Workday's AI, then Workday is not a passive tool but an active "agent" of the employer, and can be held directly liable. This case establishes a terrifying new precedent: your AI tools can make you an agent of illegal discrimination, creating massive legal and reputational risk.
(Source: Reuters, Jul 2024)
This brings us to the final warning and the one that brings the threat out of the business units and directly into the legal department itself.
A Final Warning: The Lawyer Who Cited Six Fake Cases
The most potent AI risks are the ones that look like solutions. In the 2023 case of Mata v. Avianca, lawyers for the plaintiff turned to ChatGPT for legal research. The AI delivered a list of persuasive, official-looking, and entirely fictional case citations.
Names like Varghese v. China Southern Airlines filled their legal brief. When the airline's lawyers and the judge couldn't find these cases, the truth came out: the AI hadn't searched a database; it had invented a legal reality.
The humiliation was swift. The judge’s scathing opinion documented the lawyers '"bad faith" in citing "bogus judicial decisions." The firm was sanctioned, the lawyers fined $5,000, and they became global posterchildren for professional malpractice.
This story is the ultimate cautionary tale. It combines a hallucination presented as fact with a catastrophic failure of professional judgment. The lesson from Mata v. Avianca is this: the greatest GenAI risk to your legal department isn't the advice you give to others, but your own team's failure to distinguish between an answer engine and an invention engine.
(Source: Reuters, June 2023)
The Antidote: How to Avoid Catastrophe
Building a corporate AI catastrophe is optional. The antidote is not to abandon the technology. It is to implement a deliberate system of control.
This system has two parts. First is the Technical Leash, which grounds the AI in fact. Instead of letting your AI roam the open internet, confine it to trusted sources: your approved contract templates, internal legal memos, verified regulatory databases, and established playbooks. Second is the Human Firewall, which ensures expert judgment. This means building workflows where a seasoned professional must review and approve the AI's output before it becomes a binding decision.
Think of the AI as the world's fastest junior analyst. It can draft the report in seconds, but an expert must always be the one to sign off on it.
This disciplined approach, combining a technical leash with a human firewall, is what transforms a potential liability into a truly defensible competitive advantage.
The choice is stark: implement AI with discipline or become a cautionary tale for the next generation of legal professionals. In a profession built on precedent, don't let your firm become the precedent others learn to avoid.
