The 2026 AI Threat Landscape in Healthcare

AI has outpaced enterprise security. Generative AI fraud will hit $40B by 2027 1 , putting PHI, patient trust, and regulatory compliance in even greater jeopardy. Driven by AI-native attacks that never sleep, adapt in real time, and deploy convincing impersonations that humans detect only half the time, 2 this is infrastructure-level risk. Download the guide to see where attackers are targeting healthcare organizations and see what it takes to defend against it.

In this guide you’ll learn

Legacy security like knowledge-based authentication are no longer sufficient. Healthcare organizations must transition to a multi-layered verification model that correlates media integrity, behavioral signals, device telemetry, and network intelligence.

Why AI-native attacks are now an infrastructure-level risk: Attackers have shifted from manual scams to automated operations that run continuously, refine scripts in real time, and deploy synthetic media humans only detect with ~50% accuracy.2
Where AI attacks are landing in healthcare: Highly sensitive clinical and financial data, including PHI and HSA accounts, are at risk of exposure through multiple attack surfaces, from hiring fraud and helpdesk impersonations to reconnaissance and account takeover, includes findings from Pindrop’s own hiring pipeline, where 1 in 6 applicants showed signs of fraud.3
The three questions every identity system must answer: Is this a machine or human? Is this a bad actor? Is this your patient, member, or provider? Plus how to make those decisions defensible at the moment trust is granted.

Digital trust isn’t optional—it’s essential

Take the first step toward a safer, more secure future for your business.

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