Digital Health & AI Insurance
Intended purpose, clinical reliance, data and technology dependencies classified before the cover is chosen - because the insurance boundary follows what the software actually does.
Specialist
Market access
Hard-to-place
Our focus
Australia
National broking
Recognition
The Tank take
Digital health and AI businesses commonly need technology professional indemnity and cyber insurance. Medical professional or products liability may also be relevant when software influences diagnosis or treatment, qualifies as a medical device or connects to supplied hardware.
Underwriters look straight past an 'AI disclaimer'. They assess intended purpose, real users, validation, human review, model and hosting dependencies, sensitive data, regulatory position, contracts and the consequence of inaccurate or unavailable outputs.
The four questions that classify a health platform
The insurance boundary follows what the software does and how people rely on it, not the marketing category.
Summarising a consultation is different from diagnosing, triaging or recommending treatment. The closer an output sits to a clinical decision, the closer the risk sits to the medical malpractice boundary.
Model evaluation, version control, monitoring and human escalation carry the accuracy narrative. An AI product that cannot show its validation gets priced for the uncertainty.
Health information, consultation recordings and cross-border processing increase privacy and breach severity. Data volume, retention and training use are standard questions.
Cloud, API, model and vendor outages can create correlated service failure across every customer at once. Underwriters distinguish a single tenant failing from the whole platform failing.
What a real AI health submission gets asked
When Tank took a consumer AI health app to market - an app that recorded consultations with consent and produced plain-language notes as a memory aid - the underwriting review was detailed even though the app did not diagnose or prescribe. Insurers probed validation, model provenance, privacy responsibility, data volumes, tenancy architecture and correlated downtime.
The instructive point: an alleged bodily injury could arise from a transcription, paraphrase or translation error alone. 'Free' and 'not medical advice' removed neither the technology exposure nor the privacy one.
We prepared the submission by positioning the app as genuinely non-clinical, disclosing the global download history, and approaching both technology and life sciences markets. The full question set is in our AI health underwriting checklist.
Complex science deserves a precise submission
Tell us what you advise on, build, test, supply or operate. We take the risk to insurers with genuine life sciences appetite and explain the terms before you decide.
The digital health structure to test
Core sections
- Technology PI for allegations that software or services caused a customer's loss
- Cyber for privacy liability, incident response, restoration and business interruption
- Public liability for premises and in-person exposures
Boundary-dependent
- Medical professional liability where outputs influence diagnosis or treatment
- Products liability where software is a regulated device or ships with hardware
- Management and media liability for founders, fundraising and IP disputes
Cyber and technology PI are sometimes packaged and sometimes separate. Whether privacy events and service-performance allegations sit in one wording or two changes how a claim lands.
How we place digital health risk
Classify the intended purpose
We document what the software is for, who uses each output and what decisions it can influence - the questions that decide the medical boundary and any software-as-device analysis.
Map the dependencies
Models, APIs, hosting and data providers are mapped so correlated failure and vendor risk can be presented rather than discovered.
Present the evidence
Validation, privacy architecture and incident controls go to insurers as a coherent story across technology and life sciences markets.
Check the current Australian guidance
Regulatory obligations sit outside your insurance policy. These official sources are the starting point.
External government and industry sources. Tank Insurance is not responsible for their content; confirm current requirements with the relevant body.
Related life sciences guides
Explore cover by business activity
Questions about Digital Health & AI
It can be both. Intended purpose, clinical reliance, regulatory status, data and contracts determine the classification, and both market types can be worth approaching.
No. The product's design, marketing, workflow and actual use carry more weight than the disclaimer alone, for both insurers and regulators.
Not necessarily. Some packages combine them, while others separate privacy and security events from service-performance allegations. The structure needs to be deliberate.
The insured may depend on a model it cannot fully control, audit or restore, creating accuracy, availability and contract risks that flow through to its customers.
General information only. This page does not take account of your objectives, financial situation or needs and is not legal advice. Cover depends on the insurer, policy wording, limits, excesses, exclusions and information disclosed. Read the relevant policy documents and obtain professional advice before deciding.
Put your life sciences risk in front of the right markets
Tell us what you research, build, test, supply or operate, plus any overseas exposure. We will explain the available terms and exclusions before you decide.