As artificial intelligence becomes more embedded in healthcare, medical information (MI) professionals are facing a new frontier. While AI offers powerful tools for efficiency and scale, it also introduces complex ethical, regulatory, and human challenges. In this evolving landscape, MI professionals are not just users of technology. They are stewards of patient information, responsible for safeguarding trust, transparency, and accountability.

Where AI adds value in medical information

AI is proving most effective when applied to repetitive, structured tasks that support, not replace, human decision-making. In medical information call centers, AI is particularly useful for:

• Triaging inquiries and routing callers to the appropriate departments.
• Detecting adverse events in real time.
• Retrieving and summarizing structured documents such as product labels.

These applications streamline workflows and improve the customer journey. However, much of the data in MI is unstructured and spontaneous, coming directly from patients and healthcare professionals. This level of data requires careful contextualization and review by trained professionals. Insight generation from such data must be handled with caution, as the output of AI systems in these cases is not always reliable without human oversight.

Valid concerns from physicians and patients

Studies show that both patients and physicians are excited about AI but remain cautious. Their concerns are valid and rooted in historical lessons. Past failures in drug safety underscore the importance of communication, safeguarding, and accountability.

Medical information professionals carry the weight of decades of hard-won trust. Any application of AI must respect this legacy and prioritize patient safety. Transparency about how AI is used is essential to maintaining credibility and mitigating risk.

Transparency is non-negotiable

As AI begins to mimic human conversation, the risk of misidentification grows. Patients and HCPs may not realize they are interacting with a machine, leading to misplaced trust. To address this, MI teams must:

• Clearly label AI-generated or AI-supported responses.
• Provide confidence scores and accuracy indicators.
• Maintain disclaimers that clarify the role of AI in communications.

This level of transparency helps users assess the reliability of the information they receive and ensures that human judgment remains central to decision-making.

Ethical data stewardship

One of the most important principles in medical information is that professionals do not own patient data: they are custodians of it. This ethical stance must guide every decision about how data is used, shared, and protected. AI tools must be implemented with strict adherence to privacy laws and ethical standards.

Best practices include:

• Ensuring human oversight in all AI-supported processes.
• Validating AI systems for accuracy and transparency.
• Clarifying liability in case of errors or breaches.
• Advocating for shared accountability across industry stakeholders.

The emphasis on keeping a human in the loop is a step in the right direction, but more work is needed to define liability and ensure ethical use of patient information.

Preparing for cybersecurity risks

Cybersecurity is no longer just a technical issue. It is a patient safety issue. Breaches, attacks, and system failures can compromise sensitive data and disrupt care. But the more insidious risk lies in the infiltration of datasets and algorithms, which can introduce bias and distort outputs without detection.

To mitigate these risks, MI teams must:

• Implement robust validation and monitoring protocols.
• Secure every link in the data and technology chain.
• Maintain transparency about AI usage and data sources.
• Ensure traceability for audits and regulatory compliance.

AI is only as good as the data it is trained on. If that data is flawed, the output will be too. Medical information professionals must remain vigilant and proactive in protecting the integrity of their systems.

The future of medical information in an AI-enabled world

Looking ahead, AI should become a background engine that enhances human performance rather than replacing it. MI professionals will evolve into more specialized roles, focusing on complex conversations, critical analysis, and strategic oversight.

This transformation will require:

• Upskilling in AI literacy and ethical data management.
• Cross-functional collaboration with tech and regulatory teams.
• Continued emphasis on accuracy, reliability, and patient-centered care.

AI can help MI teams spend less time on repetitive tasks and more time on meaningful interactions. But the core mission remains unchanged: to provide trustworthy, accurate medical information that supports safe and effective patient care.