Two-thirds of American physicians already use AI to expedite patient note-taking, assist in diagnostics, create care plans, and more. In 2026 alone, AI adoption in the healthcare industry could save Americans up to $150 billion. These savings are largely driven by administrative automation, including billing and claims, as well as clinical efficiencies such as faster diagnostics and reduced hospital stays.

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While AI can lead to more informed health care decisions, faster treatment timelines, lower costs, and a reduction in human error, it also raises concerns about patient security. Security in medical AI is paramount, particularly in the context of patient care, to minimize unnecessary escalation and safeguard patient data.

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Strategic importance of AI security in healthcare

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AI-enabled care delivery models are the future, and stakeholders agree. According to a National Association of Insurance Commissioners survey, 84% of health insurers already use AI and machine learning across multiple health plan types, reflecting widespread industry adoption.

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With the increased adoption of AI, decision makers at healthcare organizations need to ensure partner solutions have established effective guardrails to minimize legal risks, including sharing or exposing Protected Health Information (PHI) with the wrong party or offering harmful medical advice.

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Solutions like Counsel’s responsible medical AI, mitigate potential security risks before they arise, having been designed with safety guardrails and physician supervision.

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Technical standards and best practices

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To safeguard patient data, defend payers against liability, and minimize the risk of leaks, breaches, and errors, it is critical for solutions to meet certain requirements, including:

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• ‍Encryption: Encryption obscures data as it’s sent between different servers, such as those of patients and an AI platform. If hackers manage to intercept this encrypted data, they won’t be able to make sense of it as they won’t have the key to unscramble its contents.‍
• Secure messaging: Secure messaging ensures communication with the intended parties and prevents the correspondence from being intercepted. Counsel’s secure messaging practices include careful verification of approved doctors, reliable hosting for AI servers, and encryption to mitigate potential data leaks.‍
• Role-Based Access Controls (RBAC): RBAC assigns access permissions based on a user's role, rather than their identity or organization. RBAC means only certified, verified parties, such as doctors, nurses, and other medical professionals, can view patient information. RBAC also prevents unfettered data access by providing approved parties with only the information they need, rather than the entire patient’s profile.‍
• Continuous monitoring: Counsel constantly checks in with physicians and other partners for feedback on usefulness and accuracy. Similarly, security specifications are consistently weighed against the latest hacking methods to ensure the most recent, reliable protocols protect users and payers.

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In addition to these security features, AI-enabled care models should enforce strict compliance with:

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• ‍The Health Insurance Portability and Accountability Act (HIPAA): HIPAA is the golden rule in healthcare, and violating it leads to steep regulatory penalties. Organizations and individuals can be charged and persecuted for AI-based HIPAA violations. As such, safeguarding PHI is essential to an organization’s continued operations and personal safety.‍
• System and Organization Controls (SOC 2): SOC 2 is an organizational standard for data integrity, confidentiality, and reliability created by the American Institute of Certified Public Accountants (AICPA). It examines an organization's security controls so users can assess the risk of using their services. Counsel is SOC 2 compliant, having earned the AICPA’s seal of approval for security standards.‍
• Other regulatory frameworks: The healthcare industry is still working through AI adoption. The National Telecommunications and Information Administration (NTIA) itself admits the need for more rulings, cases, and guidelines on the evolving technology. Though our system is not regulated as a medical device, we choose to follow the relevant principles of development outlined by the International Medical Device Regulators Forum (IMDRF) in Good machine learning practices for medical device development.

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Compliance is especially important within enterprise systems since the more users on a platform, the greater the opportunities for a leak, breach, or malpractice.

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Enterprise-grade AI security protocols

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Security for PHI and sensitive data is crucial, but so are safeguards that prevent AI hallucinations, unvalidated advice, and malpractice. Counsel’s multi-agentic AI framework offers:

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• ‍Robust technical controls over AI interactions: This allows partner organizations to set response parameters and exercise maximum control over how an organization’s system interacts with patients.‍
• Intelligent emergency-detection features: If patients require immediate in-person care, an emergency agent defers to the correct care setting, ensuring the member’s health and safety.‍
• The ability to analyze and de-risk ambiguities: Triage is challenging, even during in-person interactions with qualified medical professionals. It can be even more difficult on digital platforms where users may not be able to fully express their symptoms. Counsel analyzes ambiguous health data and, if required, defers cases to qualified medical professionals for further consideration. ‍
• A fully-owned national medical group of physicians: When a member’s inquiry requires a diagnosis, medication prescription, treatment plan, or a member simply prefers to chat with a physician directly, Counsel provides the ability to connect with an in-house provider within minutes. This convenience is what members often describe as having a doctor in their pocket, one that is infinitely knowledge, accessible, and hyper personalized.

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Accountability also extends into record-keeping. Counsel ensures all documentation is audit-ready, accurately logging inputs, reasonings, and actions.

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Counsel’s chain of evidence tracks patient interactions from day one. This degree of documentation provides a reliable record to reference during internal payout assessments, patient interactions, and external audits. A digital paper trail not only keeps healthcare organizations audit-ready, but it also helps them maintain compliance.

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Ultimately, data security and AI in healthcare operate hand-in-hand to provide patients with more accessible, higher-quality medical services. They improve efficiency of payer operations and multiply clinical capacity.

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Advancing safety in AI-enabled care with Counsel

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At Counsel, we’re committed to protecting patient safety. Through our multi-agentic framework and physician oversight, we partner with health plans to deliver high-quality care that improves health outcomes, drives member engagement, and boosts network efficiency.

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Partner enterprise organizations are already experiencing measurable value with Counsel. Member’s satisfaction rate is 4.9/5, a satisfaction score that is possible with immediate, personalized answers from Counsel AI and the ability to chat with an in-house physician in under 2 minutes. Counsel has also been able to resolve 96% of concerns without escalations, and reduce unnecessary ER visits by 24% compared to consumer AI tools.

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The added benefit from partnering with Counsel as a payer is the ability to deploy its platform via an embedded, white-labeled option. Counsel fits into any portal or member applications, enabling brand continuity while extending clinical workflows and enterprise healthcare platform capabilities to any organization.

‍Discover how Counsel can drive your innovation strategy forward with its AI-enabled care model.