- Medical negligence remains Beazley’s most frequent and severe digital health claims driver, while improper supervision ranks second.
- Multi-risk insurance adoption rose from 40% in 2024 to 53% in 2026 as AI-related incidents increasingly span professional liability, cyber, technology E&O and general liability.
- Claims handling has overtaken price and coverage as the top insurer-selection factor, while silent AI wording remains a major placement issue for digital health firms.
Digital health companies are adopting AI faster than insurance programs are adapting to the resulting exposures, according to Beazley’s 2026 Digital Health & Wellness report. The study surveyed 600 executives across Europe, North America and Asia, while its claims analysis draws on roughly a decade of Beazley’s own healthcare loss data.
Beazley writes digital health insurance and therefore has a commercial interest in the market examined by the report. Its longer claims history nevertheless provides a useful comparison between the risks executives worry about and the losses appearing most often in practice.
Medical negligence ranks as both the most frequent and most severe cause of loss in Beazley’s healthcare claims book. Improper supervision ranks second by frequency, even though executives surveyed were more focused on cyberattacks and workforce competency.
That difference becomes more important as AI moves into diagnosis, triage and treatment processes. A single patient injury involving AI-assisted care could produce claims under several insurance policies at the same time.
Beazley describes this as a liability chain spanning medical professional liability, cyber insurance, technology errors and omissions and general liability.
Responsibility could extend beyond the treating clinician to software providers, healthcare organizations and other parties involved in delivering the service.
Marc Martin, product leader for digital healthcare at Beazley, said interconnected AI-enabled healthcare systems increase the number of parties likely to face claims after patient injury. Developers, physicians and client organizations could all become involved depending on how the technology was designed and used.
Insurance purchasing patterns are already changing alongside these exposures. The share of digital health companies buying one tailored multi-risk policy increased to 53% in 2026 from 40% in 2024, according to Beazley.
Separate policies create potential coverage gaps when one incident crosses several insurance lines. That issue becomes harder to manage when medical treatment, software performance and data handling are part of the same event.
Legal analysis is also becoming clearer around who bears responsibility for AI-related harm. In July, the UK Jurisdiction Taskforce published its Legal Statement on Liability for AI Harms, concluding that existing English law is capable of dealing with such cases without new legislation.
The statement starts from the position that AI systems don’t have legal personality and therefore aren’t themselves liable. Responsibility instead falls on the developers, deployers and users involved, depending on the facts of each case.
For insurance buyers, that allocation raises questions about where each party’s coverage begins and ends. Digital health programs therefore need to account for situations where several insureds and several policy types become involved in the same dispute.
Beazley’s survey also found a gap between executive concerns and its historical claims experience. Thirty-six percent of respondents cited professional misrepresentation as a significant concern, while improper supervision already ranks among the most frequent sources of claims.
Cyberattacks were identified by 32% of executives. Beazley’s claims data shows cyber losses occurring relatively often, but their severity currently ranks below several professional liability exposures.
Other loss sources receive less management attention despite appearing regularly in claims data. These include breach of contract, intellectual property disputes and miscommunication associated with AI-supported services.
For insurance brokers, the mismatch matters when clients allocate risk-management budgets. A digital health company concentrating heavily on cyber defenses could give less attention to professional liability, contractual disputes or supervision failures that generate substantial claims activity.
The report also shows a change in how digital health companies select insurers. Fast and reliable claims handling has moved ahead of price and coverage as the leading purchasing consideration among surveyed firms.
Beazley links this shift to disputes that are becoming harder to investigate and resolve. Privacy litigation and AI-related errors increasingly involve several parties, while misinformation distributed through social media adds another source of potential conflict.
Claims handling therefore carries greater weight during insurance placement. Digital health companies need to consider how insurers coordinate coverage when a dispute involves professional liability and technology exposures at the same time.
Policy wording is changing as insurers address so-called silent AI exposure. These are situations where existing policies neither expressly include nor exclude losses connected with artificial intelligence.
For digital health companies, the issue cuts across several coverage lines because AI increasingly sits inside both clinical and administrative workflows. Unclear wording leaves uncertainty over how medical professional liability, cyber and technology E&O policies respond when an AI-related incident occurs.
For brokers, the report points to three areas requiring attention before renewal discussions. They include whether one incident receives coordinated coverage across relevant policies, whether management priorities match actual claims experience and whether policy wording clearly addresses AI-related losses.
Those questions are becoming more relevant as AI moves further into patient-facing healthcare systems. Beazley’s findings suggest that insurance structure, claims response and wording clarity are becoming as important as the underlying technology risk itself.
