Is there liability insurance for autonomous AI agents acting on a company's behalf?

Yes. A small but growing market now exists for AI agent liability insurance—coverage designed for companies that deploy autonomous or semi-autonomous AI systems that can take actions on the company’s behalf. It is not yet as standardized as cyber insurance or general liability, but insurers and specialty providers are developing products specifically around agentic AI risks.

Typical coverage areas may include:

• Unauthorized or erroneous actions — e.g., an AI agent sends the wrong instructions, approves an incorrect transaction, or makes a damaging business decision.
• Financial losses caused by agent execution — such as overspending, incorrect refunds, contract mistakes, or workflow failures.
• Data and privacy incidents — including accidental disclosure or misuse of information.
• AI errors and omissions (E&O) — similar to professional liability, covering claims that an AI system provided harmful or inaccurate outputs.
• Cyber-related AI incidents — such as prompt injection, tool misuse, or an agent being manipulated into taking harmful actions.

How it fits with existing insurance

Companies usually look at a combination of:

• Technology E&O / professional liability — for claims arising from software or services.
• Cyber liability — for breaches, attacks, and data events.
• Errors and omissions endorsements for AI use — where available.
• Standalone AI liability policies — newer products aimed specifically at autonomous systems.

The challenge is that traditional policies often were not written with an AI agent that can independently call APIs, move money, communicate with customers, or alter workflows in mind. Insurers are therefore adding AI-specific language, endorsements, or exclusions rather than assuming existing coverage applies.

Examples of emerging providers

Some companies and insurance programs in this space include:

• Armilla AI — offers AI-related liability and assurance products, including coverage tied to AI system performance and failures.
• Mount — developing insurance focused specifically on deployed AI agents.
• Redberry Labs — markets coverage for organizations deploying AI systems in production.

Important limitations

Before buying, a company would want to check:

• Does the policy cover the AI agent’s own actions, not just a human’s negligence?
• Are autonomous decisions covered, or excluded as “algorithmic” risk?
• Does coverage apply when the agent has authorized access but makes a harmful choice?
• Are losses from hallucinations, bad tool calls, or prompt injection included?
• Are first-party losses covered, or only lawsuits from third parties?

For a company deploying agents that can do things like approve purchases, interact with customers, modify systems, trade assets, or execute contracts, it is increasingly common to treat AI liability as a distinct risk category rather than assuming ordinary software insurance is enough.

The short answer is no, there is no comprehensive, off-the-shelf "Autonomous AI Agent Liability" policy widely available today . Instead, the insurance industry is experiencing a massive tug-of-war between companies deploying agentic AI and insurers trying to mitigate completely unquantified machine risks.

As autonomous agents move past simple text-drafting into independent tool-calling, executing transactions, and modifying systems without human sign-off, the landscape of liability insurance is shifting rapidly:

1. The Rise of Explicit AI Exclusions

Rather than designing new coverage for autonomous agents, major insurance ratings and advisory organizations (like the Insurance Services Office—ISO) have rolled out explicit exclusions.

• Commercial General Liability (CGL) Exclusions: Standard policies are introducing specific endorsements (such as ISO form CG 40 47 ) designed to strip out bodily injury, property damage, or advertising liability arising from generative or autonomous AI.
• The "Silent AI" Problem: Traditional policies (like Errors & Omissions or Cyber Liability) assume a human error at the wheel. If an autonomous agent makes a multi-million-dollar financial blunder, triggers a chaotic supply-chain loop, or sends defamatory data without a traditional cyber breach (like a hack or data intrusion), traditional policies will likely fight or deny coverage.

2. Why Insurers Are Hesitant

Underwriters are pumping the brakes on autonomous agents for a few primary reasons:

• Unpredictable Scale & Correlation: If a single foundational model or widely used autonomous agent framework has a systemic flaw, it can cause identical losses across thousands of client companies simultaneously. Insurers hate correlated systemic risk.
• The "Black Box" Problem: True agentic workflows often lack a clean, human-readable audit trail of why the machine made a specific decision, making risk assessment nearly impossible.

3. Emerging (Narrow) Solutions and Workarounds

A small handful of specialty carriers and niche products are beginning to bridge the gap, though they come with heavy caveats:

• Specialty Riders & Add-ons: Some cyber and tech E&O insurers offer restricted AI security riders. However, these typically require strict underwriting prerequisites, such as proof of rigorous pre-deployment red-teaming, documented human-in-the-loop guardrails, and deterministic logging.
• Traceable/Insurable Architecture: A rising trend among enterprise software vendors is marketing "verifiable" agentic platforms that log every API call and state change to make the AI's autonomous path auditable enough to satisfy cautious underwriters.

If you are deploying autonomous agents, I can help you look into:

• Contractual risk transfer (indemnification clauses with your AI vendors)
• Specific policy audits to check if your current commercial lines have hidden AI exclusions

Let me know what your AI agents are authorized to do (e.g., financial transactions, customer communication, code deployment) to narrow down your exposure.

Yes, specialized liability insurance for autonomous AI agents exists , though it is a rapidly evolving market. Traditional policies like Commercial General Liability (CGL) or standard Errors & Omissions (E&O) frequently exclude multi-step autonomous decision failures, hallucinations, or unprompted agent errors.

To close this gap, specialty insurers and AI-native carriers have introduced dedicated risk-transfer products.

Would you like to:

• Review the key underwriting criteria insurers use to evaluate autonomous AI risk?
• Explore how indemnification clauses in vendor contracts address AI agent failures?

Yes. As of 2026, insurance for companies using autonomous/agentic AI exists, but it is still an emerging specialty market rather than a standardized insurance product. There are now insurers/MGAs offering affirmative AI-liability coverage specifically for organizations deploying AI, including coverage aimed at autonomous agents.

The important distinction

A company generally has several possible layers of coverage:

• AI-specific / affirmative AI liability — emerging policies explicitly cover losses arising from AI use, including certain autonomous-agent errors and decisions. Some newer products are specifically designed around an agent's delegated authority and execution errors.
• Technology E&O / professional liability — potentially covers errors in technology or professional services, but whether an autonomous agent's actions qualify depends heavily on the policy wording.
• Cyber insurance — useful when the agent causes a breach, unauthorized access, or other cyber incident, but ordinary cyber policies may not respond to an AI making a bad business decision that isn't itself a security event.
• Commercial general liability / product liability — potentially relevant where an agent causes bodily injury, property damage, or certain third-party harms, but AI exclusions and the exact trigger matter.
• D&O and other specialty policies — relevant to downstream corporate/regulatory consequences, but generally aren't substitutes for AI-agent coverage.

The fundamental problem is that traditional policies were written around human employees, conventional software, and relatively predictable automated systems. An agent that can independently decide, call APIs, send money, modify records, communicate with customers, or take other consequential actions creates a different risk. The insurance industry itself is describing this as a new liability category sitting between cyber, technology E&O, professional liability, and product liability.

What would an AI-agent policy actually insure?

Imagine a company gives an agent authority to:

approve refunds up to $10,000, purchase supplies up to $25,000, modify CRM records, negotiate with vendors, and send customer communications. A purpose-built policy could potentially address losses such as:

• The agent pays the wrong vendor $100,000.
• It makes an unauthorized transaction.
• It exceeds its delegated authority.
• It makes a materially erroneous decision that causes a third-party financial loss.
• It takes an action outside its intended workflow.
• A model/vendor failure causes the agent to execute incorrectly.

Some emerging products explicitly frame the insured event as an AI agent executing an action outside defined authority limits, rather than trying to insure whether the underlying model "reasoned correctly."

There's a big catch

Don't assume your existing E&O or cyber policy covers this.

A 2026 analysis from Ropes & Gray notes that businesses are discovering substantial gaps between their existing insurance programs and the liabilities created by agentic systems. Coverage varies substantially by policy and insurer.

For example, suppose your agent sends an erroneous recommendation to a customer, and the customer loses $2 million. That's not necessarily a cyber claim. It may be professional liability, technology E&O, AI liability, or potentially uninsured depending on the policy wording.

And insurers are increasingly asking about how autonomous the system is, what authority it has, what systems it can access, whether humans approve actions, and whether actions are logged and reversible.

A particularly interesting development

There are now companies building insurance specifically around autonomous agents, rather than merely adding an AI endorsement to an existing policy. For example, RiskHelm describes coverage for "execution error" and authority breaches by AI agents, while Redberry Labs describes first- and third-party AI coverage for organizations deploying agents in areas such as finance, healthcare, logistics, and customer-facing operations.

There is even an emerging proposed standard, AIPS-1, intended to make an AI agent's insurance status machine-verifiable to counterparties.

If you're thinking about this commercially

There's an interesting distinction between "insurance for AI" and "insurance for an AI employee."

The latter is potentially a much bigger market.

If an enterprise can give an autonomous agent a defined identity, authority limit, bank/payment permissions, system permissions, and audit trail, you could theoretically insure:

Agent identity → delegated authority → permitted actions → actual actions → financial consequence → insurer pays.

That is considerably more tractable for underwriting than trying to insure "hallucinations" in the abstract. The emerging agent-specific products are already moving in this direction.

So the short answer is yes—and the market is just beginning to form. There isn't yet a universally accepted "autonomous AI agent liability policy," but specialized affirmative AI coverage and agent-specific products are now appearing, while conventional E&O/cyber policies are being adapted and scrutinized for gaps.

If you're asking because you're considering building or buying this type of insurance, I can also map out what an actual AI-agent liability policy might cover, how you'd underwrite it, and who is already selling it in the U.S. in 2026.

Yes, specialized liability insurance for autonomous AI agents exists as a distinct and rapidly evolving commercial insurance category.

Because autonomous AI agents differ from static chatbots—they can actively execute multi-step workflows, call tools, access internal software, move funds, and negotiate contracts with minimal human supervision—they present unique risk profiles that standard commercial policies generally fail to cover.

The Traditional Insurance Gap

Traditional commercial general liability (CGL), standard cyber policies, and traditional Technology Errors & Omissions (Tech E&O) were built for human decision-making and human-directed software errors.

• The Exclusion Wave: Many commercial carriers have introduced absolute AI exclusions or narrow endorsements explicitly removing coverage for bodily injury, property damage, and financial losses stemming from generative AI outputs or unmonitored agent actions.
• Silent vs. Affirmative Policies: Policies that were once "silent" on AI have largely shifted to explicit exclusions or strict affirmative warranties. If an AI agent "goes rogue," hallucinates a binding policy, misallocates funds, or triggers a faulty automated system shutdown, standard policies will often deny the claim.

The Rise of Dedicated AI Liability Insurance

To bridge this gap, a dedicated market for AI liability and autonomous agent insurance has emerged, backed by specialty markets and InsurTech carriers:

• Specialized InsurTechs & MGA Products: Specialized providers (such as Klaimee , which specifically targets autonomous agent risks for enterprises, and startup-focused carriers like Corgi ) write policies covering first- and third-party harm caused by autonomous agent mistakes, overspending, and multi-step logic failures.
• Standalone and Endorsed Generative AI Policies: Firms like Armilla offer standalone AI liability and performance warranties backed by institutional capital like Lloyd's, covering regulatory violations (such as under the EU AI Act or Colorado AI Act), data leakage, and harmful agent actions up to significant limits. Other providers like HSB (Munich Re) offer targeted AI liability extensions for small-to-medium businesses utilizing operational or customer-facing AI.

What Underwriters Look For

Securing coverage for autonomous AI agents is heavily contingent on a company's internal governance framework. Underwriters typically evaluate:

• Scope of Authority: Whether the agent can only draft text or has direct execution rights to send, delete, update, or trigger financial transactions.
• Access Boundaries: What software, inboxes, and external APIs the agent can reach.
• Documented Controls: Pre-deployment risk assessments, audit logs, adversarial testing records, and clear boundaries for human-in-the-loop escalation.

If you're evaluating coverage for an upcoming deployment, let me know:

• What actions will your AI agent be authorized to take (e.g., executing payments, customer service, internal data processing)?
• What type of existing commercial policies (Cyber or Tech E&O) does your company currently hold?

I can help you outline the specific policy questions to ask your insurance broker.

Yes. As of 2026, insurance specifically addressing autonomous/agentic AI liability is emerging, although it is still a relatively young market and coverage varies substantially by insurer and policy wording.

The key distinction is between ordinary business insurance that happens to cover an AI incident and affirmative AI/agent liability coverage that explicitly agrees to insure the agent's actions.

What exists today

• AI-specific liability policies. Specialty insurers are offering affirmative coverage for losses arising from AI deployment, including erroneous AI outputs, autonomous decisions, privacy/IP issues, and in some cases bodily injury or property damage.
• Agent-specific coverage. Newer products explicitly target agents that can take actions—for example, executing transactions, changing records, communicating with customers, or operating software. Some products focus on the company's own financial loss when an agent exceeds its authorized limits.
• AI endorsements to existing policies. Cyber, technology E&O/professional liability, and general liability can sometimes respond, but whether they do depends heavily on the wording. Traditional policies weren't generally written with autonomous decision-making in mind.
• Layered programs. The emerging thinking is that there probably isn't one universal "AI agent policy." A company may combine cyber + Tech E&O + general liability + an affirmative AI endorsement/specialty policy.

The interesting issue: who is actually insured?

Suppose a company's purchasing agent has authority to spend up to $50,000, and an autonomous agent accidentally orders $500,000 of inventory.

There are at least three different insurance questions:

1. The company's own $450,000 loss — potentially first-party AI-agent/execution-error coverage.
2. A supplier's claim against the company — potentially third-party liability/E&O coverage.
3. A cyberattack that manipulated the agent — potentially cyber insurance, depending on the attack and policy.

Those are not necessarily covered by the same policy. For example, one current agent-specific product explicitly says it covers the organization's direct financial losses but not third-party lawsuits.

And legally, the fact that "the AI did it" generally doesn't make the company disappear from the liability chain. Current U.S. legal analysis generally expects accountability to remain with the people/entities deploying and controlling the agent.

What I'd ask an insurer/broker

For a company deploying autonomous agents, I would get written answers to these questions:

• Does the policy expressly cover actions taken autonomously by an AI agent?
• Is the agent treated as an employee, software, professional service, or something else?
• Are unauthorized transactions or decisions covered?
• Are hallucinations, incorrect decisions, or model failures excluded?
• What happens when the agent uses a third-party model such as an LLM?
• Are prompt injection and agent hijacking covered?
• Does coverage extend to third-party bodily injury/property damage, or only economic loss?
• Are privacy, IP infringement, discrimination, defamation, and regulatory claims covered?
• Does a human approval requirement affect coverage?
• Are there per-agent or aggregate limits, and are multiple agents treated as a correlated/systemic risk?

That last point is particularly important: if 10,000 agents use the same underlying model and the model has a systematic failure, insurers may view that as one enormous correlated exposure rather than 10,000 independent claims. The emerging insurance literature specifically identifies accumulation/systemic risk as a major issue.

Bottom line: yes, you can now find insurance specifically designed around AI and, increasingly, autonomous AI agents. But I would not assume that a company's existing cyber or E&O policy covers an agent simply because it covers "AI." The market is evolving quickly, and explicit affirmative coverage is much safer than relying on ambiguous legacy wording.

If you're asking because you're considering building or buying this type of insurance product, I can also map out the current market—who is offering it, what they cover, typical limits, and where there is still a gap.

Yes. As of 2026, there is a small but rapidly developing market for liability insurance specifically aimed at companies deploying autonomous/agentic AI. It is not yet as standardized or widely available as cyber, E&O, or general liability insurance.

The important distinction is between legal liability and insurance coverage:

• If an AI agent acts on behalf of a company, the company can generally still be liable for the agent's actions. The AI itself isn't a separate legal person that can ordinarily absorb liability.
• Whether the company's existing insurance covers that liability is a separate question—and existing policies can have significant gaps or AI exclusions.
• New specialty products are emerging specifically to fill that gap.

What the emerging coverage looks like

There are now several companies offering or developing dedicated AI/agent liability products:

• Armilla AI has a standalone AI Liability Policy, with reported limits up to $25 million, covering risks associated with generative AI and autonomous agents.
• Redberry Labs offers coverage specifically for organizations deploying AI agents, assessing each agent based on its permissions, data access, deployment context, and usage.
• RiskHelm is developing AI-agent liability coverage focused on things such as unauthorized spending/transactions and execution errors beyond an agent's delegated authority.
• Castra Risk describes itself as a specialty MGA underwriting affirmative AI liability for autonomous systems and decision agents.
• Mount is building an AI-agent insurance carrier, with its initial product specifically aimed at liability arising from deployed autonomous agents.

There is even an emerging AIPS-1 standard intended to make insurance coverage for an individual AI agent machine-verifiable, reflecting the idea that an agent could eventually carry an identifiable insurance policy alongside its identity and authorization credentials.

What would actually be covered?

Imagine your company gives an agent permission to:

read email → negotiate with vendors → issue refunds → modify CRM records → spend up to $25,000 → communicate with customers

Potential insured events could include:

The really interesting development is that insurers are beginning to underwrite the agent's authority and controls, not merely the underlying model. Things like permissions, human approval checkpoints, logging, shutdown capability, tool access and transaction limits can affect insurability and pricing.

But there's a big catch

You shouldn't assume your existing E&O or cyber policy covers an autonomous agent.

For example, cyber insurance may respond to a conventional data breach but not necessarily to an AI agent simply making a bad decision. Similarly, E&O generally depends on whether the agent's activity falls within the policy's definition of professional services.

This is becoming known as the "silent AI" problem: traditional policies may neither explicitly exclude nor affirmatively cover AI-related losses, leaving considerable uncertainty about where the risk actually sits.

The bigger opportunity

If you're asking this from a business/product perspective, I think the more interesting model isn't simply "AI insurance." It's:

Agent → identity → delegated authority → continuous monitoring → insurance policy → counterparty can verify coverage.

In other words, an autonomous agent could eventually have something analogous to a human employee's authorization + corporate liability coverage, with the insurance limit dynamically tied to what the agent is permitted to do.

That's particularly compelling for agents that can move money, sign/accept transactions, access sensitive data, modify production systems, or make decisions affecting third parties.

The market is very early, though. A 2026 academic survey argues that agentic AI doesn't fit neatly into any one traditional insurance line and that the likely end state is a layered combination of cyber, technology E&O, product liability, performance warranties and affirmative AI liability, rather than one universal "AI insurance" policy.

If you're considering this for a company deploying agents, I can also break down what a $1M/$10M/$50M AI-agent liability policy would likely need to cover and what an insurer would ask during underwriting.

Yes, specialized liability insurance for autonomous AI agents exists , and it has rapidly evolved into a distinct commercial insurance category.

As companies deploy AI agents with "tool-calling" capabilities—systems permitted to read/write data, execute workflows, send communications, or move funds without human sign-off on every single step—traditional corporate policies have proven inadequate.

The Traditional Policy Gap

Most legacy commercial lines—such as Commercial General Liability (CGL), Cyber Liability, and Technology Errors & Omissions (Tech E&O)—were written for human-directed software errors or conventional network breaches. In response to rising agentic risks, a large percentage of standard commercial insurers have introduced explicit AI exclusions rather than leaving coverage "silent". If an autonomous agent hallucinates a contract, leaks sensitive customer data, or misallocates capital, standard policies often disclaim the loss.

Emerging Standalone & Affirmative AI Coverage

To fill this gap, a new class of specialty carriers and insurtechs (such as Klaimee, Armilla AI backed by Lloyd’s, and Corgi ) provide dedicated AI agent and generative AI liability policies.

Key areas typically addressed by modern AI liability coverage include:

• AI Agent Output / Action Liability: Covers financial losses, third-party damages, and defense costs when an autonomous agent executes a faulty command, overspends a budget, or acts on bad logic.
• Data Disclosure & Privacy: Indemnifies the company if an autonomous workflow inadvertently exposes confidential corporate or customer data.
• Regulatory Proceedings: Defends against investigations and regulatory penalties arising from automated actions under frameworks like the EU AI Act or state-level AI laws.
• Algorithmic Bias & Discrimination: Covers claims if an autonomous hiring, lending, or pricing agent produces unlawful discriminatory outcomes.
• Intellectual Property Infringement: Protects against copyright or IP claims triggered by content or code generated during an agent's autonomous execution.

How Underwriting Works

Because the AI agent itself cannot hold legal personhood or sign a policy, the deploying or developing company is the policyholder. To underwrite autonomous risk, modern insurers look closely at your governance infrastructure rather than just traditional safety logs:

• Complete observability and audit trails showing every read, change, or trigger the agent makes.
• Hard authorization boundaries and approval thresholds built directly into the software architecture.
• Independent model verification or compliance certifications (such as AIUC standards).

If you are planning to deploy or insure autonomous agents, let me know:

• What specific tasks will the agent perform (e.g., customer service, financial transactions, data routing)?
• What level of human oversight or hard limits are built into its workflow?

I can help you evaluate what specific coverage extensions or policies your organization might need to look for.

Yes. As of 2026, insurance specifically aimed at AI/agentic-AI liability is emerging, although it is not yet a mature, standardized insurance category like general liability or cyber insurance.

The important distinction is that there are really two questions:

1. Is the company legally liable for what its AI agent does? Often, yes—the fact that an AI made the decision generally doesn't make the company immune from ordinary negligence, contract, privacy, IP, or other liability. Recent legal analysis around autonomous agents is emphasizing exactly this problem.
2. Does the company's insurance actually cover that liability? That's much less certain. Existing cyber, technology E&O/professional liability, and general liability policies can have gaps or AI exclusions.

What's available now

There are several emerging approaches:

There are now insurers/insurtechs explicitly offering the latter category. For example, RiskHelm describes coverage for financial losses when AI agents execute transactions beyond human-defined authority limits. www.riskhelm.com Redberry Labs describes agent-by-agent underwriting based on permissions, data access, deployment context, and users. www.redberrylabs.comwww.riskhelm.com And Armilla AI has announced standalone AI liability coverage with limits up to $25 million and coverage extending to autonomous agents.

There's also a broader AI-liability market emerging: Corgi launched AI insurance covering risks associated with autonomous AI decisions and failures, while Testudo offers AI liability coverage underwritten at Lloyd's.

The interesting part: insurance may be tied to the agent's "authority"

I think this is the most important development.

A conventional policy asks something like:

What business activity are you insuring?

Agentic insurance is beginning to ask:

What is this particular agent allowed to do?

For example, imagine a company deploys an AI procurement agent with authority to:

• purchase up to $10,000;
• use three approved vendors;
• access the company's procurement system;
• negotiate prices;
• never modify bank-account information.

An insurer can potentially underwrite that defined risk envelope.

If the agent somehow purchases $500,000 of equipment or sends money to an unauthorized account, the policy could potentially treat that as an agent execution error / authority violation, rather than simply trying to shoehorn the event into generic E&O.

That concept is already appearing in the new AI-agent insurance products.

But there is a major catch

Don't assume your existing insurance covers an autonomous agent just because it covers your business.

A July 2026 analysis from Ropes & Gray notes that companies are increasingly using a mixture of cyber, technology E&O, D&O and general liability coverage, but the applicability to AI varies substantially by policy and insurer. In particular, cyber insurance may not respond to an AI-generated erroneous output that causes something like a defamation or misrepresentation claim.

There's also a new phenomenon sometimes called "silent AI" exposure: an insurer may technically cover an AI-related loss because the policy doesn't exclude it, even though the insurer never specifically priced for autonomous AI behavior. The industry is now trying to figure out how to deal with that.

If you're thinking about this as a business opportunity

There is potentially a very interesting insurance product here.

The natural product isn't necessarily "insurance for AI." It's closer to:

Delegated-authority insurance for autonomous software.

The underwriting inputs could include:

• agent identity/version;
• model/provider;
• tools and APIs it can access;
• maximum transaction authority;
• financial limits;
• whether it can communicate externally;
• whether it can execute contracts;
• data it can access;
• human approval requirements;
• logging/auditability;
• sandboxing;
• prompt-injection defenses;
• rate limits;
• ability to revoke the agent;
• historical agent execution traces.

That makes the agent's permission set and execution history potentially as important to underwriting as the company's industry.

A June 2026 research paper on agentic-AI insurance similarly proposes underwriting based on autonomy, delegated authority, permissions, governance, dependencies, and observable traces rather than treating AI as a generic technology risk.

So the short answer is:

Yes—and the market is moving toward exactly the kind of "AI agent liability insurance" you're describing. But today, it's a fragmented emerging market, and the actual policy wording matters enormously.

If you're asking because you're considering building/selling autonomous agents for businesses, I can also break down what a practical $1M/$5M/$10M AI-agent insurance program could look like—including who would be insured (the agent owner, deploying company, customer, or model provider), what events should trigger coverage, and how premiums might be priced.

Yes, liability insurance for autonomous AI agents exists , but the market is shifting rapidly from a state of ambiguity to a heavily scrutinized, specialized landscape.

Because an AI agent is a software tool rather than a legal person, it cannot buy its own insurance. Instead, the company deploying or building the agent must hold the policy to cover the financial and legal exposure of the agent's autonomous actions (such as calling APIs, initiating financial transactions, or modifying enterprise databases).

The Current Insurance Landscape

1. The "Silent AI" to Exclusion Shift: Historically, standard commercial policies (like Cyber or Tech E&O) were "silent" on artificial intelligence, leaving companies to guess whether an AI mistake was covered. Many mainstream carriers have moved toward explicit absolute AI exclusions or specific restrictive endorsements. If you rely on an off-the-shelf, legacy policy, a rogue agent's error may not be covered.
2. Dedicated AI-Specific Insurers: Specialized and AI-native insurtechs (such as Klaimee , which focuses specifically on autonomous AI agent risks, Armilla AI , and Testudo , backed by institutional and Lloyd's capital) offer standalone policies or affirmative AI riders. These coverages specifically address model drift, autonomous decision errors, prompt injection, and multi-step workflow failures.
3. The Coordinated Stack: Protecting an enterprise utilizing agentic AI usually requires a layered approach rather than a single policy. This includes:
   • Technology Errors & Omissions (Tech E&O): Tailored to algorithmic or agentic decision failures.
   • Cyber Liability: Extended (via affirmative wording) to cover non-breach data leakage or unauthorized operational disruptions caused by tool-calling agents.
   • Directors & Officers (D&O) / Professional Liability: Increasingly tied to whether the organization maintained adequate AI governance and human oversight.

What Underwriters Look For

Securing coverage for autonomous agents requires proof of robust governance. Insurers typically evaluate:

• Scope of Autonomy: What systems, databases, and financial limits the agent can access without human-in-the-loop signoff.
• Auditability & Telemetry: How well the company logs, tests, and monitors the agent’s sequential decisions.
• Compliance Posture: Alignment with frameworks like the EU AI Act or NIST AI Risk Management Framework.

If you'd like to narrow this down for your situation, tell me:

• What specific tasks will your AI agent perform (e.g., handling customer funds, modifying data, customer-facing chat)?
• Are you building the agent or deploying a third-party tool?

I can help you identify which specific coverage gaps to look for in your current policies.