AI Attacks in Healthcare: Bots, Deepfakes, and Rising Risk

AI attacks in healthcare refer to the use of automated bots, deepfake technologies, and AI-driven scripts to impersonate individuals, bypass security controls, and access sensitive data or financial accounts. These attacks often target health saving accounts and contact centers and exploit weaknesses in legacy authentication systems.

AI bots are driving healthcare attacks at scale

AI bots are conducting large-scale, automated attacks on healthcare systems to gather sensitive data and enable fraud.

After implementing the Pindrop^® solution, a major U.S. healthcare provider uncovered bot attacks account for more than half of all fraud in their systems.¹ Bots like these systemically exploit healthcare contact centers, probing IVR systems for reconnaissance, using intel from the IVR to carry out social engineering schemes with live agents, taking over accounts, and in some cases, gaining access to HSA, FSA, and other employer-funded savings accounts.

This same customer saw over 15,000 unique bot fraud calls since the summer of 2025,¹ indicating that attackers are turning this tactic into a repeatable scheme. By deploying automated bots at scale, attackers can validate Social Security numbers, dates of birth, balances, and transaction histories—without ever speaking with a live agent.

Common AI bot attack methods in contact centers include:

How AI bot attacks are identified

AI bot attacks can be identified through behavioral patterns such as scripted commands, rapid interaction speeds, and environmental signals indicating coordinated, large-scale operations.

Despite the fact that our researchers aren’t seeing text-to-speech artifacts or lag, they’re noticing “programming-style” commands that suggest script-driven interactions. These commands let bots interact with near-human speed. Background noise analysis also suggests that attackers are in a call-center-style fraud operation, deploying their fraud schemes at scale.

Why healthcare is a primary target for AI attacks

Healthcare is a primary target because it combines high-value financial accounts, sensitive personal data, and legacy security systems that are easier to bypass with stolen information.

Healthcare is facing a perfect storm. The controls that once kept attacks manageable are failing at the exact moment that scams are getting faster, cheaper, and harder to spot. Legacy security checks are no longer a meaningful barrier when stolen personal data is everywhere. Nearly 60% of organizations now report fraudsters using compromised Personally Identifiable Information (PII) to quickly bypass knowledge-based authentication (KBAs).²

At the same time, generative AI has changed the threat landscape. According to Pindrop data, deepfake attacks exploded by 880% in 2024.³ This is not a theoretical risk. It is showing up at scale, in real accounts, with real losses.

Regulators are cracking down too. The largest general healthcare fraud takedown in U.S. history, charging 324 defendants tied to $14.6 billion in intended losses, signals a new era of scrutiny and enforcement.⁴ For healthcare, these forces collide at once: weak legacy defenses, AI-fueled attacks at industrial scale, and growing regulatory pressure.

The business impact of AI-driven healthcare attacks

AI-driven attacks impact healthcare organizations through financial loss, operational disruption, and erosion of customer trust.

AI-driven scams create real business damage fast. The most immediate impact is financial loss. Compromised accounts can lead to direct financial losses, especially when potentially high-balance accounts like HSAs and FSAs are targeted. Beyond that, indirect costs like investigations and reimbursements can quickly add up, turning a single incident into a significant financial loss.

Healthcare organizations are trusted with some of the most sensitive and valuable data and financial accounts consumers have. When those accounts are compromised, confidence in an organization can drop drastically.

Key impacts of AI fraud in healthcare may include:

Case in point: A U.S. healthcare provider faced over $40M in account exposure related to fraudulent AI bot calls in 2025.¹

Frequently asked questions

What is AI fraud in healthcare?

AI fraud in healthcare involves using bots, deepfakes, or automated scripts to impersonate individuals, bypass authentication, and access sensitive data or financial accounts.

Why are bots targeting healthcare organizations?

Bots target healthcare because of the combination of valuable personal data, financial accounts like HSAs and FSAs, and legacy authentication systems that can be bypassed using stolen information.

How do AI bots bypass security systems?

AI bots use stolen PII, scripted interactions, and automation to quickly navigate IVR systems and defeat knowledge-based authentication without raising immediate suspicion.

What are the risks of AI-driven fraud?

Risks include financial loss, regulatory exposure, operational disruption, and long-term damage to customer trust and brand reputation.