Affirmative AI Endorsements in Tech E&O Insurance

What They Are, Why They Matter and Why Silence Might Be Safer

Summary

As AI becomes central to SaaS, fintech, and data infrastructure platforms, insurers are responding with Affirmative AI Insurance Endorsements - policy add-ons that explicitly state what’s covered when artificial intelligence is involved.

But is affirmative AI language always better?

A growing set of legal and underwriting voices suggest that naming AI as a specific peril could inadvertently limit coverage. I tend to agree.

Below, we unpack both positions and offer clarity on what founders, CFOs, and brokers need to watch for.

What Is an Affirmative AI Insurance Endorsement?

An Affirmative AI Insurance Endorsement is a clause in a Tech E&O or Cyber insurance policy that expressly grants coverage for liabilities tied to AI use, development, or outputs. Common examples of covered risks include:

• Algorithmic decision errors (e.g., hiring, lending)

• Copyright claims from AI-generated content

• Regulatory actions tied to automated services

• Training data misuse

• Model hallucinations or consumer misguidance

Benefits of Affirmative AI Insurance Language

Benefit	Why It Matters
Clarity	Prevents ambiguity when AI tools are the cause of harm
Defense Triggers	Stronger argument for duty to defend
Risk Positioning	Signals maturity to underwriters, boards, and investors
Coverage for Automation	Bridges the gap between "professional services" and non-human decisions
Contractual Compliance	Satisfies enterprise vendor requirements that mandate explicit AI coverage in insurance programs
Investor Assurance	Demonstrates proactive governance and risk transfer to investors, boards, and auditors
Claims Process Clarity	Reduces friction at FNOL (first notice of loss) by eliminating ambiguity around AI-related incidents
Product Differentiation	Signals maturity to clients and partners by demonstrating accountability and insurability of AI components

The Other View: Silence Can Be Stronger

While affirmative endorsements clarify intent, some argue they come at a cost:

“When you name a peril, you define a peril.”

This legal principle suggests that naming specific risks may create an interpretive ceiling. If the claim doesn’t neatly fit within the listed AI perils, the carrier may deny coverage - arguing it falls outside the defined scope.

Analogy: What Entity Listings Teach Us About Named vs. Silent AI Coverage

Subsidiary Listing	Omnibus Entity Wording
Only named entities covered	All entities controlled >50% automatically included
Easy to overlook new subs	Automatically broadens scope
Safer on paper, but riskier in execution	Safer in real-world flexibility

This comparison mirrors how affirmative vs. silent AI coverage logic in Tech E&O policies:

How Silent AI Insurance Coverage Functions

The above comparison mirrors how affirmative vs. silent AI coverage functions in Tech E&O policies, and silent AI coverage under a broadly worded E&O policy may:

• Trigger broader duty to defend - Courts tend to interpret ambiguous language in favor of the insured, triggering earlier and stronger defense obligations.

• Avoid narrowing coverage to pre-defined AI use cases - Protection applies even as the company’s AI evolves or diversifies.

• Support judicial flexibility - Courts may more easily classify AI tools as part of professional services.

• Avoid sublimit restrictions - Without explicit AI carve-outs, full policy limits may remain available.

• Enhance early-stage flexibility - Particularly valuable for startups where product-market fit, use cases, and risk profile shift quickly.

This flexible structure can offer meaningful protection - not despite its ambiguity, but because of it.

Legal Theory: How Courts Handle Named vs. Unnamed Perils

U.S. Case Law Principles That Apply:

1. Contra Proferentem:If policy language is ambiguous, courts interpret it in favor of the policyholder. A silent policy may give broader protection than a tightly defined endorsement.

2. Duty to Defend Is Broader Than Duty to Indemnify:Even if coverage is uncertain, a broadly worded policy must defend the claim unless clearly excluded.

3. Expressio Unius Est Exclusio Alterius:If you expressly include some AI use cases (e.g., LLM-based chatbots), others may be implicitly excluded (e.g., vision-based systems).

Why Lawyers May Prefer Ambiguity

Many policyholder attorneys prefer "silent" coverage precisely because it preserves ambiguity. Under legal doctrines like contra proferentem, any unclear language is interpreted in favor of the insured. In litigation, this means the policyholder often receives the benefit of the doubt — and therefore, defense and coverage - even without explicitly named AI protections.

Why Insurers May Prefer Affirmative AI Endorsements

From the insurer’s perspective, affirmative AI endorsements offer greater control over exposure.

By explicitly naming AI-related activities and attaching sublimits, insurers can:

• Define the scope of covered AI risks

• Limit financial liability through targeted caps

• Avoid defending open-ended or unintended AI-related claims

In this way, affirmative AI language becomes a loss control mechanism, allowing carriers to rate, underwrite, and manage AI exposures with more precision - particularly in a rapidly evolving legal and technological landscape.

Is There Case Law on AI-Specific Endorsements?

Emerging but Thin - Here's What We Know

None that have resulted in binding appellate rulings on AI endorsements yet, but policyholder coverage lawyers are advising that silence is often more defensible unless coverage is otherwise excluded.

What Should You Do?

Ask These 5 Questions:

1. Does my current E&O policy define “professional services” to include automated tools?

2. Is there any AI insurance exclusion in the base policy?

3. Does the AI endorsement list specific tools, models, or activities - or does it stay broad?

4. If affirmatively added, is the AI endorsement subject to a sublimit?

5. Could the endorsement limit coverage by naming too narrowly?

   
   

Final Verdict: Affirmative AI vs. Silent AI Coverage

Affirmative AI Insurance Endorsements offer clear protection and may be required by investors or clients - but they must be drafted carefully to avoid narrowing the scope of coverage.

Silent AI coverage, when paired with broad definitions and no exclusions, may offer greater flexibility and better defense positioning - especially for evolving or experimental AI platforms.

The ideal approach is not choosing one or the other blindly, but using a risk-tiered framework to structure coverage based on risk strategy, contract requirements and discussions wiht their broekr and underwriters.

About URM's AI Insurance Practice

Upward Risk Management (URM) advises leading AI-native and AI-enabled companies on structuring insurance programs that actually respond to real-world risk. Our AI insurance practice doesn't just check a box - we analyze litigation trends, regulatory exposures, and evolving model architectures to build tailored solutions. Whether you're training proprietary LLMs, embedding AI in enterprise platforms, or leveraging third-party tools, we align coverage with how liability actually arises — not how it’s been historically underwritten.

Our work spans:

• AI D&O and governance liability

• Tech E&O with silent vs. affirmative risk strategies

• Cyber and IP exposures from data-driven systems

• Regulatory and discrimination claims tied to automated decision-making

If you’re navigating AI risk, we can help ensure your insurance program is as advanced as your technology.