Independent brokerage · AI risk
Your AI can lose money in ways your policies never named.
Stoa maps your AI systems to concrete loss scenarios, shows where your current coverage responds, goes silent, or excludes — and places what's missing across every market. We sit on your side of the table; we don't underwrite our own paper.
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Describe your AI
Ten minutes, no jargon required. What your systems can touch, spend, and decide.
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See your loss scenarios
Not 'AI risk' — named events: the hallucinated promise, the injected agent, the authorized wrong action.
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Read your coverage map
Scenario by scenario: covered, silent, excluded, or only insurable in bespoke markets — and what we'd do about each.
Why now
ISO endorsements CG 40 47 and CG 40 48 introduce AI exclusions for Commercial General Liability policies, and major carriers are filing AI liability exclusions with state regulators.
The EU AI Act's high-risk obligations enforce from August 2026.
The same carve-out pattern created the standalone cyber market twenty years ago. AI risk is being carved out now — before dedicated capacity is broadly available.
Common questions
What the research says about AI risk and insurance.
The questions teams raise before a renewal, answered from published market research — each with its source.
Isn't AI risk already covered by my existing cyber and E&O policies?
Not reliably. Marsh finds generative-AI exposure runs across virtually all lines of commercial insurance — cyber, tech E&O, media, D&O, employment practices, IP, general and product liability — not just cyber. And as Insurance Thought Leadership puts it, many of those AI risks are “sitting silently inside existing policies, often unpriced, unmanaged, and waiting to materialize,” because AI losses don't map cleanly onto traditional lines.
Source: Marsh · Insurance Thought Leadership
Is AI failure a real, claimed risk yet — or still hypothetical?
It is already producing claims. Fact.MR projects AI-related legal claims worldwide to exceed 2,000 by the end of 2026, and identifies hallucinations and errors as the single largest driver — roughly 31% of the emerging market — alongside rogue autonomous actions and bias in lending and hiring. The Geneva Association describes the core failure mode plainly: models that “confidently output false or misleading information” or inadvertently replicate copyrighted content.
Source: Fact.MR · The Geneva Association
What does “silent AI” mean, and why does it matter?
It is coverage that was never affirmatively written for artificial intelligence — the form simply didn't contemplate it. Insurance Thought Leadership describes these as risks “sitting silently inside existing policies, often unpriced, unmanaged, and waiting to materialize.” Whether such a policy responds is then decided at claim time rather than before it, which is precisely the ambiguity an assessment is meant to remove.
Source: Insurance Thought Leadership
Is AI risk even insurable?
Partly, and unevenly — which is the point of assessing it. The Geneva Association flags three insurability obstacles: an excessive maximum possible loss from widespread failures, large average losses from events like misinformation or regulatory fines, and severe information asymmetry over how a business actually governs its AI. The market is responding three ways at once: AI endorsements bolted onto cyber and E&O, new underwriting (including parametric triggers), and standalone products such as Munich Re's aiSure.
Source: The Geneva Association
How is this risk actually underwritten — and why a specialist broker?
Through technical translation between how a system works and how a policy is worded. Fact.MR reports that specialist brokers and MGAs already hold roughly 46% of this market on the strength of that underwriting expertise, and the Geneva Association notes insurers increasingly approve cover only after “scrutinising insureds' AI systems and governance practices.” A broker that doesn't issue its own paper can run that scrutiny on your behalf and place across markets.
Source: Fact.MR · The Geneva Association
Does stronger AI governance lower my insurance cost?
It is the lever the research keeps returning to. Insurance Thought Leadership argues that robust governance, transparent validation, and continuous monitoring both reduce insurance costs and demonstrate trustworthiness to underwriters — treating “the whole workflow from data pipelines to prompts and APIs as the governed unit.” The Geneva Association expects insurers to require human oversight, bias checks, model audits, and reporting as conditions of cover. Our governance score is built from exactly those controls.
Source: Insurance Thought Leadership · The Geneva Association
How large is this market, and why act now?
It is forming quickly. Fact.MR values AI-agent liability insurance at about US$0.3B in 2025, rising to US$11.5B by 2036 — a ~36.8% annual rate — and the Geneva Association cites Deloitte projections of roughly US$4.7B in AI insurance globally by 2032. The Geneva Association's advice to insurers applies equally to buyers: define the risk and engage now “rather than waiting for perfect data,” while affirmative wording is still being written.
Source: Fact.MR · The Geneva Association
How much demand is there from businesses for this coverage?
Substantial, and willing to pay for clarity. In the Geneva Association's survey, more than 90% of respondents expressed a need for insurance covering generative-AI risks, and over two-thirds said they would pay at least 10% more in premium for explicit coverage — with demand concentrated in medium-to-large firms across technology and finance. The appetite is for affirmative cover, not for discovering at claim time whether a legacy form responds.
Source: The Geneva Association
Sources
- Marsh — “Generative AI: three myths about this pertinent risk” ↗
- The Geneva Association — “Gen AI risks for businesses: exploring the role of insurance” (2024) ↗
- Insurance Thought Leadership — “Managing and Insuring Generative AI Risks” ↗
- Fact.MR — “AI Agent Liability Insurance Services Market” (2025) ↗