What Clinicians Actually Think About AI Notes (The Good and the Annoying)

The promise of clinical documentation efficiency is a siren song for any clinician drowning in administrative work: more time for patients, less time charting. The reality, however, is a mixed bag of “this is amazing” and “ugh, not again”. For every nearly perfect note, there's another that's generic, misses critical nuance, or contains a subtle error that takes longer to fix than just writing it yourself.

The conversation has moved beyond whether AI is good or bad; it's about what actually works in practice. Based on real clinician feedback, here's the unvarnished good and the bad about AI clinical notes.

Why Clinician Perception of AI Notes Counts

The success of AI in healthcare isn't just a technical challenge; it's a human one. A tool can be technologically brilliant, but if it fails to align with the workflows, values, and expectations of the clinicians who use it daily, it will be abandoned.

Ultimately, clinical perception dictates everything from trust and adoption rates to the very real impact on burnout and patient safety. It's the bridge between a vendor's promise and a clinician's reality.

Changing Expectations In Clinical Documentation

Clinicians are no longer asking if AI can simply generate text, but whether it can produce clinically coherent and efficient documentation. The expectation has shifted from novelty to utility. As evolving clinician surveys indicate, the general attitude toward AI is positive; however, various concerns persist regarding its implementation.

Impact On Burnout, Trust, And Care Quality

A well‑designed AI tool that gets it right can significantly reduce cognitive load and administrative burden, directly combating burnout. Conversely, a tool requires constant vigilance to catch errors, destroys trust, increases frustration, and risks diverting focus from the patient to the chart, potentially compromising the quality of care.

AI Adoption Vs. Frontline Usability

There's often a gap between the promise of AI adoption at an organizational level and its frontline usability, a common obstacle for new health technology. A tool is only “adopted” when it's seamlessly integrated into a clinician's daily routine. If the process of reviewing and correcting AI drafts takes longer than writing the note oneself, the technology becomes a hindrance, not a help, ensuring it will be quietly sidelined.

What Clinicians Actually Think About AI Notes in Practice

Clinician sentiment on AI clinical notes is a study in contrasts. There is genuine appreciation for reduced administrative burden and more patient‑focused visits. However, this is tempered by daily frustrations over errors that require fact‑checking and editing, often negating time savings.

The prevailing sentiment is cautious optimism. Most clinicians see the potential and wouldn't return to full manual charting, but their trust is conditional. Their approval hinges on a simple ratio: does the time saved outweigh the time spent correcting mistakes? This balance defines their daily experience and ultimate verdict.

The Good: How AI Clinical Notes Are Helping Clinicians

While not without flaws, AI medical scribes are delivering tangible benefits that are transforming the daily workflow for many clinicians. Here’s how:

• Time Savings & Reduced Burnout:
  • By generating draft notes, AI scribes directly attack the primary driver of clinician burnout: after-hours charting.
  • This aligns with physician priorities, as a recent AMA survey found that 57% of physicians believe the biggest opportunity for AI is to reduce the administrative burdens that contribute to burnout and workforce shortages.
  • By automating documentation, AI directly gives clinicians their evenings back and contributes to improved well-being.
• Improved Efficiency in Documentation:
  • AI streamlines the entire documentation process. It automatically structures conversations into SOAP/DAP format, pulls in data from the EHR, and ensures codes are included, significantly reducing the number of clicks and steps required to complete a note.
  • This efficiency gain allows clinicians to see more patients or finish administrative tasks within their working hours.
• Enhanced Note Quality And Consistency:
  • AI tools can help standardize clinical documentation efficiency across a practice. By using structured templates, they ensure all required elements for a specific level of care or specialty are included, reducing variability.
  • This leads to more complete and compliant notes that are less likely to be downcoded or flagged in an audit. A report in Perspectives in Health Information Management highlights how AI can assist in creating more robust documentation.
• Better Focus on Patient Interaction:
  • This is often cited as the most significant benefit. By listening attentively, the AI medical scribe allows the clinician to maintain eye contact and engage in the conversation without being tethered to a keyboard.
  • This restores the human connection of the visit, as clinicians report feeling more present and able to listen actively, knowing the documentation is being handled.

The Annoying: Where AI Clinical Notes Still Fall Short

How to Fix What Annoys Clinicians the Most in AI Clinical Notes

The most common frustrations with AI Notes aren't dead ends; they are solvable challenges. Here's how to address them:

• Mandate Human Supervision & Final Review

Treat every AI‑generated note as a draft, not a final product. The clinician's role moves from author to editor, focusing on verifying accuracy, adding nuance, and ensuring the note reflects their clinical judgment before signing.

• Be Discerning About When and Where to Use AI

AI excels with structured, routine visits (e.g., follow‑ups, physicals) but often struggles with complex, multi‑system reviews for novel presentations. Develop clear guidelines on which visit types are appropriate for AI assistance to maximize efficiency.

• Strategic Integration Into Clinical Workflows.

The AI tool must fit seamlessly into your existing EHR workflow. The best AI works invisibly within your current charting process, pulling data directly into the note and saving drafts to your inbox for easy review.

What Clinicians Expect Next from AI Notes

The current generation of AI notes is just the beginning. Based on evolving needs, clinicians expect future tools to move beyond simple transcription to become intelligent partners in care.

• Predictive Clinical Insights: AI that analyzes the session data to flag potential diagnoses and recommend evidence-based next steps.
• Seamless Multimodal Integration: Tools that combine voice, EHR data, and vitals from connected devices to create a comprehensive note.
• Proactive Administrative Automation: The AI auto-populates forms, submits prior authorizations, and schedules follow-ups based on the assessment and plan.
• True Adaptive Learning: Systems that deeply learn from the clinicians' preferences and style to produce notes.
• Enhanced Patient Engagement Tools: Features that generate personalized patient summaries and education materials in plain language directly from the note, improving communication and adherence.

Conclusion

AI Clinical Notes are a powerful but imperfect tool. It saves time and reduces burnout, but it requires human oversight to ensure accuracy and safety. The future of AI lies in becoming a true clinical partner, offering insights, not just transcription. The key is balance. Use technology to support your expertise, not replace it. This is the principle behind Twofold: building AI tools that adapt to your workflow, protect your time, and uphold your standard of patient care. For clinicians seeking specialized support, this is what defines the best therapy notes software today.