Assessing and Insuring AI Exposure
The practitioner's course: assess the AI exposure in a submission, place it with the right wordings, endorsements and exclusions, read the pricing signals, and handle an AI-driven claim when it comes. This is where the earlier cores turn into terms on a schedule.
Take an AI risk from submission to terms, and stand behind it at claim
This is the applied core. It assumes you can already name AI failure modes and read governance, and it puts that to work: finding the exposure in a real submission, choosing the wordings and endorsements that respond, pricing the residual risk, and holding a coverage position when an AI-driven loss arrives.
- Work through a submission and surface its AI exposure, including where AI is embedded in a product or a vendor and not disclosed on its face.
- Match an exposure to the wordings, endorsements, buy-backs and exclusions that respond, and identify where cover is silent or in dispute across a programme.
- Read the pricing signals in an AI risk and know what further information to request before you quote, so the rate reflects the exposure you are actually taking.
- Handle an AI-driven claim, from establishing what the system did to reasoning about which policy responds and documenting the coverage position.
Six lessons, about six hours
Self-paced and on demand. Each lesson ends with a short knowledge check; a final assessment, earns the certificate of completion.
01 Finding the AI exposure in a submission
A method for reading a submission for AI: where it is declared, where it is embedded in a product or supply chain, and the questions that pull hidden exposure into the open.
02 The wordings that respond, and where they fall silent
How cyber, professional and general liability, property and motor wordings treat an AI loss, where an AI failure triggers cover and where the policy simply does not speak to it.
03 Endorsements, buy-backs and exclusions
The affirmative AI grants, exclusions and buy-backs now appearing in the market, what each one does to the risk transfer, and how to build a coherent position across a tower.
04 Pricing signals and information to request
Reading an AI risk for the factors that should move rate, the additional information worth requesting before you quote, and the limits of pricing a risk with little loss history.
05 Structuring the cover across a programme
Putting a defensible AI risk-transfer structure together across lines and layers, closing silent gaps deliberately, and avoiding accidental overlap or double cover.
06 Handling an AI-driven claim
Working a claim where an AI system caused or contributed to the loss: establishing what happened, applying the wording, documenting the position, and the final assessment.
Built for the desk that has to put terms on the risk
This is the most applied of the CAIIP cores. It assumes you can already name AI failure modes and read governance, whether from the earlier cores or from experience, and turns that into decisions on wording, price and claims. If you set terms, place risk or settle losses, this is the one that shows up in your day.
Underwriters
You quote risks with AI exposure and need a defensible line on wording, endorsements and price rather than a blanket exclusion.
Brokers and account teams
You place AI-exposed risks and want to structure a programme that responds, and to explain to a client exactly what they are and are not buying.
Claims professionals
You handle losses where an AI system was involved and need a clear method for establishing the facts and applying the wording.
One core course in a larger certification
Assessing and Insuring AI Exposure is one of the 4 core courses that make up the CAIIP certification, the Certified AI Insurance Practitioner. Complete all of them, choose one specialization, and pass the proctored exam to become certified. CAIIP is coming 2026.
AI Foundations
View courseUnderstanding AI Risks and Exposures
View courseGoverning and Managing AI Risk
View courseAssessing and Insuring AI Exposure
AI Risk in Cyber Insurance
View courseAI Risk in Liability Insurance
View courseAI Risk in Property Insurance
View courseAI Risk in Motor and Autonomous Systems
View courseAbout this certificate course
No. Assessing and Insuring AI Exposure is a certificate course, which is shorter than a certification. You earn a certificate of completion, not a certification credential.
It is the most applied of the four cores and builds on being able to name AI failure modes and read governance. You can take it on its own if you already have that grounding from experience; if not, the earlier cores are the natural lead-in.
There is a final assessment. Each lesson has a short knowledge check along the way, and the final assessment confirms you are ready for the certificate of completion.
It works through the way current wordings, endorsements, buy-backs and exclusions respond to AI losses across lines, as a method you can apply to your own forms. It is training, not coverage advice on a specific policy.
Yes. Assessing and Insuring AI Exposure is one of the four core courses of the CAIIP certification, the Certified AI Insurance Practitioner, which is coming in 2026. Taking it on its own still earns the standalone certificate of completion.
From AI exposure to terms on a schedule
About six hours to assess AI exposure in a submission, place it with the right wordings and endorsements, price it, and stand behind it at claim. A certificate course, and a CAIIP core course.