The Real Value of AI Insurance Endorsements: Beyond the Buzzwords
Steven Barge-Siever, Esq.- May 1
- 4 min read
Updated: May 8
Learn what AI insurance endorsements really cover - and what they don’t. Discover the risks fintech and tech companies face when AI makes a decision, and how to close coverage gaps before claims arise.
Executive Summary:
AI systems are increasingly making business decisions, but most insurance policies haven’t caught up.
Most endorsements don’t fully cover algorithmic bias, IP claims, or regulatory investigations.
Companies must distinguish between building and using AI when assessing risk.
Even strong endorsements require professional interpretation and advocacy to be effective.
This article breaks down what to look for, what’s missing, and how to protect your company.
Intro to AI Insurance Issues
The AI your fintech just bought can scan millions of records, predict behavior, and make credit decisions in seconds.
But when it denies a loan…Discriminates against someone…Or scrapes data it shouldn’t…
Who’s responsible?
When a human makes the decision, liability is clear. When a third party model does it? Accountability, indemnification and subrogation get vague, fast.
Accountability Problem: Who’s actually responsible? When a human makes the decision, liability is clear.When a model does it? Things get vague, fast.
No matter what, if your company uses AI, you will be brought to the table, and if you are a director or officer, then your judgment will be questioned in tandem to the AI error/omission.
The insurance problem: Most insurance policies are designed to cover human mistakes. They were never built to cover machine-driven judgment errors. (Although, as their attorney I might argue that the machine is not truly making decisions…)
The litigation problem: If your model reflects biased data through bias behavior, does that mean your company has always been biased? A decent lawyer can (will) make this argument, probably via class action.
These questions are largely outstanding in the legal world, and partially answered in insurance through policy endorsements, we will review their efficacy below.
What Is an AI Insurance Endorsement, and Why It Matters
As AI-driven tools create new risk categories, insurers are trying to keep up - often by issuing endorsements.
In insurance, an endorsement is a formal modification to a policy. It can add coverage, limit it, or clarify how existing coverage applies. Think of it as a patch to the original policy form. This is especially important when the form was never designed for modern AI use cases.
That makes endorsements the first line of defense for companies using or building AI. But the quality of these endorsements varies widely.
Not All AI Companies Face the Same Risk
Before evaluating coverage, understand your company’s AI profile:
AI Builders - Create algorithms, infrastructure, or custom models. Their risk centers on model performance, IP infringement, and regulatory scrutiny.
AI Users - Rely on third-party tools. Their risk includes operational failures, biased outcomes, and liability for decisions made by systems they don’t fully control.
A one-size-fits-all endorsement won’t work. Effective policies must reflect whether your company builds or uses AI.
What a Good AI Insurance Endorsement Should Include
Done well, AI endorsements do three things:
1. Expand Key Definitions
Update terms like "Professional Services," "Technology Product," or "Technology Services" to explicitly include AI-driven platforms.
2. Carve Back Exclusions
Most policies exclude IP claims, discrimination allegations, and regulatory investigations. A strong endorsement will restore coverage for:
Algorithmic bias
AI-generated content/IP infringement
Defense costs for AI-related regulatory investigations
Client demands to remove or correct AI functionality
3. Provide Full Limits or Clear Sub-Limits
Even if coverage is limited to $250K, that’s far better than total denial.
Where Even the Best AI Insurance Endorsements Fall Short
Endorsements don’t guarantee protection.
Ambiguity: AI-related terms are often poorly defined.
Silent Gaps: Some endorsements reference AI but still exclude the core exposure.
Enforcement: Even great language can fail if no one advocates for its intent when a claim hits.
AI may be automated. But insurance claims are not.
Real-World Perspective: Drafting AI Coverage from Both Sides
We’ve drafted AI insurance endorsements for insurers, negotiated coverage and exclusions. I’ve also reviewed dozens of policies for AI-focused companies - from fintech lenders to infrastructure startups to model developers.
What I’ve learned: an informed, knowledgable broker makes all the difference. A single misplaced exclusion or vague definition can turn a high-profile claim into an uninsured loss.
If you’re an executive at an AI company, you don’t need theoretical coverage - you need enforceable language, carrier clarity, and someone who understands how AI decisions actually happen.
Why Professional Oversight Still Matters
Securing the right AI endorsement is only part of the battle. You still need a professional who understands:
How AI tools work
Where bias, IP, and operational risk emerge
How to enforce coverage in high-stakes, ambiguous claims scenarios
Without that, even the best language can fall flat.
Final Takeaway
AI endorsements are evolving. Some are real improvements. Many are not. The difference isn’t just in what they say - it’s in how they’re written, interpreted, and enforced.
If your business uses AI to make decisions, serve clients, or power your platform- don’t rely on legacy forms. Don’t rely on assumptions.
Review your policy. Understand your endorsement. And make sure someone at the table knows how to fight for it.
Need Help?
If your company builds or uses AI and you're unsure whether your insurance program actually covers the decisions being made, we can help.
Contact Upward Risk Management to schedule a review or learn more about Undr AI’s platform for real-time risk insights.
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