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Cyber Risks of AI-Driven Practices: More Than Just Data Breaches

May 2, 2025

The healthcare sector has always been a target for cybercriminals. But as artificial intelligence becomes embedded in clinical workflows, cyber risk is expanding in ways many brokers—and clients—haven’t fully accounted for.

AI-driven tools can improve diagnostics, automate admin tasks, and enhance patient engagement. Yet these same tools often increase a practice’s exposure to data breaches, system manipulation, and operational failure. For brokers advising medical clients, cyber coverage must now be evaluated with these emerging threats in mind.

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How AI Changes the Cyber Risk Profile

Traditional cyber liability policies were built around the risk of stolen data, ransomware attacks, and phishing scams. While these remain core concerns, AI systems introduce new layers of vulnerability.

First, AI platforms often require integration with multiple third-party systems—patient records, cloud services, scheduling tools—which expands the potential attack surface. A weak link in any of those integrations can compromise the whole practice.

Second, AI systems themselves can become the target. From adversarial attacks that trick diagnostic models to direct breaches of automated scheduling or triage tools, AI opens new front doors for threat actors.

Third, AI systems frequently process large volumes of patient data to deliver results. If the AI is hosted or operated by a third-party vendor, questions of data ownership, security responsibilities, and compliance with HIPAA become more complex.

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The Consequences Go Beyond Privacy

When AI systems are compromised, the impact often reaches beyond data exposure. In a clinical context, the consequences may include:

• Incorrect diagnoses or treatment recommendations based on altered or corrupted algorithms

• Missed appointments, delays, or procedural failures from disrupted scheduling systems

• Loss of patient trust due to perceived overreliance on opaque or vulnerable technology

• Regulatory penalties if HIPAA or state-level data protection laws are violated

In short, AI-related cyber events can have clinical, reputational, and regulatory consequences. A standard cyber policy focused on data breach response may not be enough.

Medical malpractive insurance is an often misunderstood, yet critical component in the realm of healthcare. It serves as a protective barrier, not just for medical practitioners against unforeseen legal claims,

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What to Look For in Cyber Liability Policies

As a broker, reviewing your client’s cyber policy should now include a closer examination of how well it covers risks related to AI infrastructure and AI-driven decisions. In particular, brokers should assess:

1. Definition of Covered Systems: Does the policy explicitly cover AI platforms, SaaS tools, or embedded software used in patient care?

2. Bodily Injury Exclusions: Some cyber policies exclude claims involving physical harm. If an AI system is compromised and delivers faulty recommendations, will that claim be covered under malpractice, cyber, or neither?

3. Business Interruption Coverage: If an AI system goes down and forces the practice to close or reschedule operations, does the policy provide for income loss?

Policy coordination is especially important. In the event of a major AI-related incident, both the malpractice and cyber liability carrier may be involved. Gaps between the two can create confusion—and leave the client underinsured.

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Coordinating Malpractice and Cyber Coverage

An AI-related incident might start as a cyber breach and evolve into a malpractice claim. For example, if an adversarial attack alters the output of an AI diagnostic tool, and a provider relies on that output to treat a patient, the result is both a tech failure and a clinical misjudgment.

This overlap highlights the importance of:

• Understanding how AI tools are integrated into the practice’s workflow

• Making sure both carriers are aware of these tools

• Confirming which scenarios are covered, and which are not

In some cases, cyber carriers are starting to offer endorsements that address algorithmic liability, especially for AI-as-a-Service platforms. Brokers should be aware of these options and bring them into the conversation when coverage feels incomplete.

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Conclusion

AI brings real operational benefits to healthcare practices—but it also exposes new vulnerabilities. For brokers, that means taking cyber liability coverage seriously, asking more targeted questions, and ensuring clients are protected from the risks they can’t see coming.

As AI becomes more central to healthcare delivery, the line between clinical and technological failure will continue to blur. Brokers who help clients anticipate and close those gaps will earn their trust and their business.