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AI doesn’t understand words, meaning, or human consequences. It analyzes data, detects patterns, and applies probability. The difference matters—especially in industries where errors have real-world impact.
AI doesn’t think. It doesn’t understand meaning, intent, or consequences. It processes data, identifies patterns, and makes statistical predictions. The difference is critical—especially in industries where mistakes carry legal, financial, or even life-threatening consequences.
At Brand Voyagers, we’re studying this issue because AI adoption is outpacing risk management. Companies integrate AI into critical workflows assuming it “knows” what it’s doing. It doesn’t. And when AI gets it wrong, the fallout raises complex questions—who’s responsible? Who pays for the damage? How do businesses protect themselves?
The Risks of AI Errors in High-Stakes Industries
Healthcare: Misdiagnosis and Medical Malpractice
Sol Rashidi, Head of Technology for Startups at Amazon, recently shared a story about an AI misdiagnosing a patient and how this underscores a growing concern. A doctor trusted an AI-generated diagnosis, nearly prescribed unnecessary, aggressive treatment, and later discovered the AI had misinterpreted an MRI anomaly. The mistake was caught—but what if it hadn’t been?
Who’s liable in cases like these? The doctor, for blindly trusting AI? The hospital, for implementing the system? The AI vendor, for training a model that made a fatal error? Malpractice insurance traditionally covers human errors, but AI introduces a gray area. Some insurers now offer AI liability policies, but coverage depends on who is classified as the decision-maker—the AI or the human using it.
In 2022, a hospital in the UK piloted an AI-powered radiology tool that flagged tumors for review. Doctors later discovered a flaw—it misdiagnosed 12% of cases, leading to delayed treatments. Patients suffered. The hospital faced lawsuits. The AI company, meanwhile, claimed it only “provided recommendations.”
Key Takeaway: AI doesn’t absolve professionals of responsibility. Human oversight remains non-negotiable.
Finance: Algorithmic Trading and Market Manipulation
AI-driven trading systems execute financial transactions at lightning speed, often without human intervention. When they go wrong, the consequences are immediate and widespread.
- The 2010 Flash Crash saw the Dow Jones plunge nearly 1,000 points in minutes. High-frequency trading algorithms reacted to each other, triggering a downward spiral no human could stop in real-time.
- In 2021, an AI trading system at a major hedge fund made incorrect risk calculations, causing billions in losses before human traders intervened.
Banks and hedge funds increasingly use AI insurance policies to cover AI-related errors, but these policies come with fine print. Many insurers require proof that AI decisions were monitored, audited, and adjusted by humans before payouts are issued.
Key Takeaway: AI must be treated like any other high-risk financial tool—audited, monitored, and regulated.
Legal: AI-Generated Falsehoods in Court
In 2023, lawyers submitted a legal brief that included case law entirely fabricated by AI. The attorneys, assuming AI would produce accurate research, failed to verify the citations. The judge not only dismissed the case but also sanctioned the attorneys for negligence.
This wasn’t an isolated incident. AI can “hallucinate”—meaning it generates entirely false but convincing information. In law, the consequences go beyond embarrassment. If an AI-generated legal brief misleads a judge or results in a wrongful conviction, the responsibility falls on the lawyer. AI is not legally recognized as an “agent,” meaning courts hold the human using it accountable.
Key Takeaway: AI-generated content must always be verified. The cost of misinformation is too high.
Journalism: AI-Generated Fake News
AI writing tools can generate news articles in seconds, but what happens when they get facts wrong? Major media outlets have already faced backlash for publishing AI-generated stories riddled with inaccuracies.
- In 2023, an AI-generated obituary claimed a still-living professor had passed away. The false information spread before corrections were issued.
- An AI-generated sports article referred to a baseball player as “[Player Name]” because the model didn’t fill in real data. It was published as-is, damaging the outlet’s credibility.
- AI-written political articles have spread misinformation, contributing to election-related confusion.
Media companies rushing to automate content risk lawsuits, retractions, and loss of public trust. If AI-generated news results in defamation, who gets sued? The journalist? The publication? The AI company? These questions remain legally unresolved.
Key Takeaway: AI can’t replace editorial judgment. Misinformation damages reputations—and leads to legal action.
Cybersecurity: AI Flagging the Wrong Threats
AI powers many modern security systems, identifying potential cyber threats. But false positives can cripple operations while false negatives leave organizations exposed.
- A major bank’s AI security system misinterpreted normal traffic as a cyberattack, shutting down critical services for two days and causing millions in losses.
- An AI fraud detection tool flagged legitimate customer transactions as fraudulent, locking thousands of users out of their accounts.
If AI falsely flags a customer as a security risk, who’s responsible for the financial loss or reputational damage? Some insurers cover AI-induced cybersecurity failures, but only when companies prove they maintain human oversight and have an appeals process for AI-driven decisions.
Key Takeaway: AI security systems should always include human override options. No system is foolproof.
Who’s Responsible When AI Fails?
When AI gets something wrong, responsibility becomes blurred between:
- The professional using AI (doctor, lawyer, journalist, financial analyst)
- The company implementing AI (hospital, law firm, newsroom, bank)
- The AI provider (tech company developing the system)
Legal frameworks are still catching up. Most courts hold humans responsible since AI lacks legal personhood. However, some AI vendors now include liability disclaimers in contracts, meaning buyers assume full responsibility for AI errors.
Businesses integrating AI into high-risk areas should:
- Review AI vendor contracts – Understand liability clauses before implementation.
- Secure AI insurance – Policies for AI-driven errors are evolving but require oversight proof.
- Develop internal AI governance – Clearly define where AI ends and human judgment begins.
AI Is a Tool, Not a Decision-Maker
AI isn’t the enemy. It’s a tool—one that requires guardrails, oversight, and accountability.
At Brand Voyagers, we’re studying how AI fits into decision-making across industries. Companies rushing into AI adoption without thinking through risk management, liability, and human oversight will face real consequences.
AI can assist, enhance, and optimize—but it should never replace critical thinking and expert judgment.
Because at the end of the day, AI doesn’t know what it’s doing. But you do.
