By Zac Amos, Features Editor, ReHack
LinkedIn:Â Zachary Amos
LinkedIn:Â ReHack Magazine
Artificial intelligence (AI) powers healthcare operations, clinical decision support and administrative efficiency, but cybercriminals use the same tools to carry out more convincing, scalable and adaptive fraud. AI-enabled schemes exploit complex systems, data and human trust, making strong governance, technical controls and organizational awareness essential. Following are  strategies to help healthcare organizations recognize and defend against AI-driven fraud.
1. Understand How AI Is Reshaping Healthcare Fraud
AI amplifies traditional fraud by increasing speed, scale and realism. Criminals use machine learning to analyze claims, predict payer behavior and produce realistic billing. In addition, large language models and deepfakes mimic emails, invoices, documentation, and even executive or clinician voices. The stakes are high. The average cost of a healthcare data breach reached $7.42 million per incident in 2025, the highest among all industries, highlighting the significant financial impact when fraud and cyberattacks succeed.
Recent regulatory guidance notes a growing convergence of cyber intrusion, identity theft and fraudulent billing. AI lowers the barrier to entry for these schemes, enabling rapid experimentation and increasing exposure for healthcare organizations with distributed systems and complex vendor relationships.
2. Strengthen Identity and Access Management Controls
AI-assisted fraud frequently begins with compromised credentials. Once attackers gain access, automated tools help them navigate systems efficiently. Healthcare organizations benefit from layered identity and access management strategies, including:
- Multifactor authentication for all privileged and remote access accounts.
- Role-based access control aligned with job responsibilities.
- Continuous monitoring for anomalous login patterns, including time, location and device indicators.
- Regular credential hygiene reviews, especially for third-party vendors and temporary staff.
3. Use AI Defensively to Detect Anomalies
AI remains a critical defensive asset when applied with transparent governance and oversight. Advanced analytics help identify subtle fraud indicators that rule-based systems often miss, such as unusual combinations of procedure codes or shifts in user behavior across electronic health record platforms. Healthcare organizations increasingly deploy machine learning models to analyze claim volumes, coding patterns and documentation consistency. Behavioral analytics further support detection by identifying deviations from established access and usage norms. These capabilities deliver strong results when combined with human review, reinforcing the need for close coordination among compliance, information technology and clinical leadership.
4. Secure Email and Digital Communication Channels
Phishing remains a primary method of delivery for AI-enabled fraud. AI-generated messages often appear grammatically precise, context-aware and personalized. Federal alerts indicate a 140% increase in mail theft over the past three years, underscoring how low-tech financial workflows can exacerbate AI-driven impersonation and fraud risks. Healthcare organizations reduce exposure by:
- Deploying advanced email filtering with machine learning classification.
- Enforcing domain-based message authentication, reporting and conformance protocols.
- Training staff to verify financial or access-related requests through secondary channels.
- Restricting executive-level financial approvals to documented workflows.
5. Elevate Workforce Awareness With Realistic Training
Human decision-making remains a central factor in fraud prevention. AI-generated content increases realism, making traditional awareness programs less effective on their own. Training programs deliver greater impact when they reflect actual operational scenarios rather than generic examples. Effective initiatives incorporate deepfake voice simulations, realistic billing anomalies and role-specific scenarios for revenue cycle, finance and information technology teams. Contextual training improves retention and reporting behavior, particularly when supported by clear escalation paths and well-defined response procedures.
6. Strengthen Data Governance and Audit Readiness
AI-powered fraud exploits fragmented data governance and limited visibility across systems. Healthcare data breaches now average $10.92 million per incident, underscoring how security gaps can rapidly escalate into substantial financial and fraud exposure. Strong governance frameworks help organizations identify irregularities earlier and respond more efficiently.
Healthcare organizations benefit from centralized logging, routine internal audits aligned with Centers for Medicare and Medicaid Services guidance, and ongoing data integrity validation. Incident response plans that integrate compliance, legal, and security teams support faster containment and regulatory readiness. Organizations with mature audit practices consistently demonstrate stronger outcomes in fraud detection and recovery.
7. Collaborate Across the Healthcare Ecosystem
Fraud actors operate across organizations, making collaboration essential. In 2025, 84% of healthcare organizations experienced a cyberattack, often involving phishing or account hijacking, highlighting the scope of these threats. Sharing information improves situational awareness and collective defense. Healthcare providers benefit from participation in:
- Health Information Sharing and Analysis Centers that distribute timely threat intelligence and mitigation guidance.
- Public-private partnerships coordinated by federal cybersecurity and healthcare oversight bodies.
- Cross-provider fraud reporting networks that surface recurring billing, identity or access abuse patterns.
- Peer forums and working groups that enable healthcare information technology and compliance leaders to exchange lessons learned and best practices.
- Academic and nonprofit initiatives focused on healthcare cybersecurity, data integrity and fraud prevention.
Building Resilience Against AI-Driven Fraud
AI-powered healthcare fraud magnifies familiar risks across identity, billing and communication systems. Strong governance, defensive analytics, workforce readiness and collaboration enable organizations to protect revenue, maintain trust and remain resilient in an AI-driven threat landscape.