Combating artificial intelligence fraud and identity theft in healthcare

Within the healthcare industry, artificial intelligence (AI) has emerged as both a promising defense and a risky threat. Such technologies have come a long way and have transformed how healthcare organizations diagnose, treat, and monitor patients. Additionally, AI technologies nowadays play a pivotal role in data cybersecurity.

See also: HIPAA compliant email: The definitive guide (2026 update)

The growth of sophisticated cyberattacks in healthcare

Criminal organizations target healthcare because protected health information (PHI) is sensitive and worth a lot of money. The primary motivation behind healthcare cyberattacks remains financial gain, given its value to hackers. Criminal marketplace pricing demonstrates the demand clearly, with a driver’s license reportedly selling for about $20 while a complete identity package can reach $1,000.

The Health Insurance Portability and Accountability Act (HIPAA) is designed to protect patients’ PHI and keep the confidential data from being disclosed without a patient's consent or knowledge. Unfortunately, healthcare data breaches continuously occur, even with HIPAA safeguards in place, putting patients in danger from PHI and identity theft. Major healthcare breaches that occurred in 2025 alone affected more than 35 million individuals.

Given the existence of such lucrative information, cyberattacks against healthcare providers have become more sophisticated, fueled in part by the growth in technologies to exploit, such as AI. An immediate AI-related concern is how threat actors embrace AI to enhance their criminal operations. Artificial intelligence helps hackers take advantage of unsecured systems and untrained staff to target healthcare organizations for cyber fraud.

More about: The complete guide to HIPAA violations

The human factor

Human error remains a weak entry point in strong cybersecurity. This vulnerability is especially concerning in healthcare systems where staff sometimes prioritize patient care over security protocols or their personal needs during critical situations. Human error and inadequate employee training can be the root causes of cybersecurity incidents.

Staff-related cyber risks are prevalent because healthcare employees can be more vulnerable to phishing and social engineering. Human vulnerabilities reflect the fundamental psychological predispositions that make individuals susceptible to deception. A report on breaches notes that many breaches in 2025 ultimately traced back to employee actions.

Security issues stem from a lack of awareness of potential threats and the security tools meant to safeguard them. The problem is exacerbated by the fact that healthcare professionals often lack awareness of AI-specific threats. Traditional security training may not prepare staff to recognize the signs of adversarial AI attacks, which can appear as system quirks or false positives rather than deliberate attacks.

AI-driven cyber fraud and identity theft in healthcare

According to IBM, AI “is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy.” Artificial intelligence systems can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Cybercriminals exploit AI tools to create fake identities, deep-fake employees, and forge insurance-related documents.

Issues such as weak access controls can lead to costly data breaches because they easily allow unauthorized access to and the misuse of sensitive information. With AI, attackers can bypass conventional security layers and enter a healthcare organization’s network.

According to a 2023 white paper by the U.S. Department of Health and Human Services’ Health Sector Cybersecurity Coordination Center (HC3), AI tools like the platform “FraudGPT” are available “for a relatively cheap price—a $200 per month or $1,700 per year subscription fee—which makes it well within the price range of even moderately-sophisticated cybercriminals.” Attackers can exploit vulnerabilities with such AI tools, tricking systems into executing harmful actions and letting cybercriminals in.

Artificial intelligence tools can effortlessly penetrate traditional defensive shields, giving hackers easier access to healthcare systems.

Examples of AI-driven cyber fraud and identity theft tools

Malicious AI models: Models designed to write convincing phishing emails or create malware code

Shadow AI: Unsanctioned AI tools used without approval or oversight that can lead to risks and leaks

Autonomous AI agents: Rapid multistage automated campaigns to scan for vulnerabilities, craft code, and quickly exfiltrate data

Deepfake impersonations: Attacks that use fake information, such as voice cloning and/or deepfake videos of doctors and pharmacists

AI-enhanced social engineering: Craftier, more personalized messages to make individuals more easily reveal sensitive data

Synthetic patient identities: Fabricated patient data merged with real patient data to pass initial insurance checks and commit insurance fraud

AI-generated medical records: Realistic clinical notes, imaging, and diagnostic reports to support false claims

Counterfeit pharmaceutical scams: Deepfakes that promote and/or sell unsafe medications

Consequences of AI-related breaches

IBM’s 2025 Cost of a Data Breach Report noted that 97% of organizations that experienced an AI-related security incident lacked proper access controls that could block AI. Moreover, the report also showed that 63% of organizations surveyed did not have AI governance policies in place to manage AI usage or prevent the proliferation of shadow AI.

The consequences of AI breaches are similar to the consequences of traditional breaches but can have more of an impact because of how easily and how often they occur. Cybercriminals can set AI tools to assault multiple systems, multiple times, without pause. Examples of consequences of AI-related breaches include:

• The theft of sensitive information
• Operational disruption
• Financial loss
• Patient safety at risk
• Erosion of trust
• Compliance-related fines and penalties

Analysts predict that AI could drive fraud-related losses from $12.3 billion in 2023 to $40 billion by 2027.

Combating AI attacks with HIPAA compliant cybersecurity

HIPAA compliance involves continuously updating security measures to protect sensitive health information and avoid breaches. While defensive measures are crucial, there are several tactics organizations could implement to fully execute strong cybersecurity against AI tools.

1. Keep employees in the know with up-to-date AI policies and procedures
2. Clearly define roles, responsibilities, and incident response protocols around AI
3. Have business associates sign a business associate agreement and explain their use of AI and how they plan to block such attacks
4. Employ layers of HIPAA compliant technological safeguards, including encryption and access controls
5. If using AI security tools, log and encrypt all interactions and ensure AI transparency and explainability
6. Monitor all systems with behavioral analyses to flag AI interactions
7. Perform risk assessments and penetration tests regularly
8. Use incident response automation along with a traditional incident response plan in case it is needed

HIPAA compliance regulations aim to safeguard health information. Adhering to HIPAA standards helps providers protect privacy, leading to stronger systems and better patient outcomes, even with the growth of new, advanced cyberattacks.

Related: Using AI for HIPAA compliance

Building a culture of cybersecurity awareness in healthcare

A culture of security awareness is one in which employees actively participate in cybersecurity. Healthcare organizations must create a culture of security awareness within their systems to help protect their patients and themselves. It lowers the human factor related to cyber incidents.

A good starting point for this is implementing staff training, clear policies, and open communication channels to help employees understand how they can handle patient data. Healthcare organizations must improve their in-house security awareness to reduce human error that leads to data breaches and HIPAA violations. That, hand in hand with vital security features, such as HIPAA compliant email, keeps an organization strong.

A good defense is vital, but only in combination with a good offense. Regular communication about emerging threats, best cyber practices, and response protocols can help organizations maintain a good security posture.

Paubox email suite, AI, and zero trust

Paubox email suite is a HIPAA compliant email solution designed for healthcare organizations to securely communicate PHI without disrupting workflow. Paubox seamlessly encrypts all outbound emails, delivering them directly to recipients’ inboxes. It integrates with existing email platforms like Google Workspace and Microsoft 365, ensuring seamless security while maintaining ease of use.

A good example of zero trust and AI working together is in Paubox’s generative AI tool. Paubox combines a zero trust security model with AI-powered inbound email security to protect healthcare organizations from advanced phishing and impersonation threats. Using AI for behavioral analysis, Paubox also offers a secure email solution for organizations seeking a cybersecurity option tailored to one of their most vulnerable outputs.

With built-in threat detection, spam filtering, and robust encryption, Paubox email suite helps healthcare providers and health-related organizations and their business associates meet regulatory requirements while enhancing communication efficiency.

More on AI:

Risk of ungoverned AI use in healthcare

AI algorithmic bias in healthcare decision making

AI-assisted monitoring in HIPAA compliant email systems

The AI arms race in healthcare cybersecurity

How does AI improve defense against cyberattacks

The risks of using ungoverned AI in healthcare

Real-world examples of healthcare AI bias

Can deepfakes be beneficial in healthcare?

FAQs

How does HIPAA apply to the use of AI in healthcare?

HIPAA applies to the use of AI in healthcare, as it governs the protection of patients' medical records and personal health information. When using AI technologies, ensure compliance with HIPAA regulations to safeguard patient privacy and data security.

Do healthcare providers need consent to implement AI solutions?

Yes, healthcare providers typically need informed consent from patients before using AI technologies for diagnosis, treatment, or other healthcare purposes. Obtaining consent is mandatory to ensure transparency and respect for patients’ autonomy in the use of AI-driven healthcare interventions.

How do healthcare organizations balance the benefits of AI detection with patient trust and consent concerns?

They often implement privacy-by-design principles and attempt to keep AI operations invisible to patients, though public skepticism remains high.

What technologies can be used to integrate AI into healthcare processes?

Healthcare professionals can use various technologies to integrate AI into healthcare, including machine learning algorithms, natural language processing (NLP), computer vision, and predictive analytics.