Inherent risks of AI scribes and how to stay ahead of them

Published on: October 5, 2026

Artificial intelligence (AI) scribes are rapidly transforming healthcare documentation by passively capturing and summarizing clinical conversations. According to a 2025 article published in JAMA, their adoption has accelerated across healthcare systems because they can reduce documentation time, decrease administrative burden, and lessen clinician burnout. While these benefits are alluring, implementation has outpaced validation, transparency, and regulatory oversight, creating important patient safety and risk management concerns.

A 2025 article in Digital Medicine clarifies that AI scribes differ substantially from traditional human scribes and speech-recognition tools. Although they may reduce some transcription errors, they introduce different failure modes that can directly affect patient care, including:

• Hallucinations: Documentation of findings, diagnoses, or examinations that never occurred.
• Critical omissions: Failure to capture symptoms, concerns, assessment findings, or treatment discussions.
• Misinterpretations: Incorrect documentation of medications, treatment plans, or clinical context.
• Speaker attribution errors: Confusion between patient and clinician statements.

Even relatively low error rates can have serious consequences in healthcare. Inaccurate documentation can contribute to misdiagnosis, delayed treatment, inappropriate interventions, medication errors, and liability exposure.

AI scribes also introduce a transparency challenge. Clinicians may have limited insight into how information is processed, filtered, or summarized. Because generated content can appear clinically plausible even when it is inaccurate, errors may not always be immediately obvious, making quality assurance and bias assessment more challenging.

AI scribes may also affect the volume and usefulness of documentation. Capturing too much of the clinical interaction can produce lengthy records that are difficult to review, while automated filtering or summarization may omit information that later proves clinically important. Both can create challenges for continuity of care and communication between providers.

Emerging research comparing AI-generated and physician-authored notes reinforces the need for careful review. In a 2025 study, involving 97 clinical encounters across five specialties, physician reviewers narrowly preferred physician-authored notes for overall quality, accuracy, succinctness, and internal consistency, while AI-generated notes scored higher for thoroughness and organization. Hallucinations were identified in both groups but occurred more frequently in the AI-generated notes.

A separate study published in April 2026 compared notes from 11 AI scribe platforms with physician notes generated from the same five simulated patient encounters. Across all five cases, human-generated notes received higher overall modified Physician Documentation Quality Instrument (PDQI-9) scores, with AI-generated notes showing deficits in areas including thoroughness, organization, and usefulness.

These findings do not suggest that human documentation is error-free. Rather, they reinforce an important risk-management principle: AI-generated documentation should not be assumed to be accurate simply because it is polished, detailed, or clinically plausible.

Physicians remain responsible for the final record

Regardless of how a note is generated, physicians should carefully review and revise AI-generated documentation before electronically authenticating it.

A 2026 narrative review from the Mayo Clinic emphasizes the importance of physician review of AI-generated encounter notes. Until or unless the FDA approves AI systems that autonomously document care, AI scribes should be treated as tools that assist with documentation — not as replacements for physician oversight.

Before signing a note, physicians should verify that it accurately reflects the encounter, including relevant history, examination findings, clinical reasoning, diagnoses, treatment plans, medications, follow-up instructions, and other clinically significant information.

Address consent, privacy, and patient expectations

The risks associated with AI scribes extend beyond documentation accuracy. Their use can raise important questions about informed consent, privacy, data security, health equity, and the secondary use of patient information.

Many AI scribe platforms capture or process conversations between patients and clinicians. Practices should understand applicable notification and consent requirements, including state laws governing the recording of conversations. Certain states (including California) require “two party consent” for the recording of conversations, which necessitates formal consent before AI scribes can be used.

Practices should also establish a process for documenting consent and responding when a patient declines the use of an AI scribe.

Privacy considerations extend beyond the clinical encounter. Recorded conversations, transcripts, and other AI-generated data may be retained or used in ways patients do not expect, including potentially for system development or training. Practices should understand how vendors collect, store, use, share, and destroy patient information before implementation.

Health equity should also be considered. Research has identified differences in speech-recognition accuracy among certain racial and ethnic groups, people with accents, and individuals with limited English proficiency. Practices should consider whether these performance differences could result in inaccurate or incomplete documentation for some patient populations.

Practical steps to reduce AI scribe risks

Before implementing an AI scribe, practices should consider safeguards that address both documentation quality and patient privacy:

• Independently evaluate the platform’s accuracy, completeness, and reliability.
• Require clinicians to review and correct AI-generated notes before authentication.
• Establish auditing and quality-assurance processes.
• Develop clear patient notification, consent, and privacy procedures.
• Establish retention and destruction policies for audio recordings, transcripts, and other AI-generated data.
• Clearly define responsibility and oversight for the platform within the organization.
• Establish a process for responding to AI-related errors or patient harm.
• Train clinicians not only to use the technology, but also to recognize and correct common AI documentation failures.

Looking ahead

AI scribes offer meaningful opportunities to reduce documentation burden and improve efficiency, but these benefits must be balanced against risks to patient safety, documentation integrity, privacy, and equity. AI-generated documentation is not without its shortcomings — and neither is traditional physician-authored documentation. As AI technology continues to evolve and become increasingly sophisticated, its role in clinical documentation is also likely to grow.

For physicians and healthcare organizations, the goal should not be to avoid these tools, but to prepare for their responsible use. Establishing clear best practices, internal processes, and appropriate safeguards now — including appropriate validation, governance, and ongoing oversight — can help practices adapt as the technology advances while keeping documentation integrity and safer patient care at the forefront.