AI Automation in Healthcare: Features and Examples
Hannah Heramia
November 13, 2025•11 min read
Fact checked by Shine Colcol
What Is AI Automation in Healthcare?
AI automation in healthcare refers to the use of artificial intelligence to streamline clinical workflows. It can also help ease the burden of manual administrative work, thereby reducing clinician burnout.
In this blog, we’ll explore how AI automation in healthcare brings value in real-world settings. We’ll also look into its impact on clinical workflows, followed by its key features and examples. Finally, we’ll highlight how Heidi’s AI-powered platform helps clinicians work efficiently to give more time for patient care.
The Impact of AI Automation in Healthcare
Administrative work has become one of the biggest barriers between clinicians and their patients. From documentation to coordination, much of a clinician’s day is still spent on tasks that don’t directly involve care. AI automation is changing that.
By streamlining routine admin tasks and improving how teams communicate, AI automation in healthcare helps restore time, focus, and presence to the clinical day. Below are four specific ways AI automation is transforming healthcare:
1. Automates Routine Administrative Tasks
According to a study conducted last year, clinicians spend up to 40% of their working hours on documentation tasks, which was linked directly to stress and reduced face-to-face time with patients.
AI automation now takes over much of the groundwork that used to fill a clinician’s day, such as form completion, appointment documentation, and note formatting. By looking after these repetitive tasks, it gives clinicians the time back for patient care and other more important matters like professional growth.
2. Improves Coordination Across Care Teams
When documentation and communication are consistent, coordination naturally follows. Automated workflows enable nurses, specialists, and allied-health professionals to share updates in real time, reducing handover gaps, delays, and duplication of work.
3. Strengthens Patient-focused Healthcare
Every improvement in workflow ultimately benefits the patient. With less time spent typing or navigating between multiple systems, clinicians can focus on listening, educating, and supporting the people in their care.

4. Helps Reduce Clinical Burnout
Administrative overload remains one of the top causes of clinician burnout. AI automation eases this strain in healthcare settings by cutting hours of manual record-keeping and follow-ups each week.
A study from the Journal of the American Medical Informatics Association found that working outside scheduled clinic hours was a measurable contributor to physician workload.
By streamlining documentation and surfacing key details quickly, AI automation allows clinicians to spend more of their shift communicating with patients and less time catching up on paperwork, which then supports their well-being and long-term retention across care settings.
In an interview with Dr. Shelagh Fraser, Director of Medical Excellence and Innovation at Priority Physicians, they often spent hours after clinic finishing their notes, the same time that should be spent on rest, reflection, and patient focus.
“There was a cohort of us who would just always be here an hour or so after work, trying to finish up notes,” she recalls. “The other thing that would happen is people would cut short a patient encounter, so they would have enough time to write their note before the next patient.”
Like many clinicians, she experienced how documentation demands can affect patient connection and contribute to burnout, a challenge that AI in healthcare aims to address.
After introducing Heidi, the change was immediate. Documentation became faster, smoother, and far less stressful, which shows a clear example of how AI automation in healthcare can streamline everyday clinical workflows.
“Previously, I would spend 2–2.5 hours writing notes for a full day of seeing patients. Now with Heidi, I’ve got that down to around 40 minutes,” Dr. Fraser shares.
For Dr. Fraser and her team, Heid, as their AI care partner, has not only saved time but has also restored balance and focus. By automating routine tasks and enabling conversational documentation, Heidi delivers the benefits of AI in healthcare in a way that feels safe, human, and clinician-led.
Key Features of AI Automation in Healthcare with Examples
Modern healthcare teams face the growing pressure to balance accuracy, safety, and patient time. AI automation tools are now helping clinicians manage tasks more efficiently without losing the empathy and professionalism that define quality care.
As also explored in how AI is used in healthcare, these tools are already part of everyday practice. Here is a list of even more impactful AI automation features transforming clinical workflows today, paired with real-world examples:
Ambient Medical Charting
Ambient medical charting uses secure, real-time transcription to capture clinical consultations and turn them into notes arranged by history, examination, plan, etc. Instead of typing or dictating every line, clinicians can review and approve accurate notes shortly after the visit.
For Example:
A general practitioner can use an AI medical scribe that listens during the consultation, transcribes the conversation, and generates a structured note. The clinician quickly reviews and edits the summary using personalized templates that match their documentation style and regional industry standards like RACGP and NHS frameworks.
Contextual Document Generation
AI automation can also generate medical documents that match the medical context, such as progress notes, discharge summaries, or specialist referrals, without having to deal with repetitive form-filling. Each document comes from the patient’s existing record and other relevant information sources to ensure accuracy and consistency across encounters.
For Example:
A psychiatrist at a community hospital uses AI form fillers that auto-complete referral forms with relevant patient information, such as lab results, diagnoses, and medication, then proceeds to review and approve the final document.
AI-Powered Patient Engagement
AI automation in healthcare enhances human interaction, not replacing it. In clinic groups or large health systems, clinicians can automate patient communications and routine follow-ups so that no concern goes unnoticed.
For Example:
A nursing team uses AI receptionists to document patient updates after discharge, recording the interaction and flagging further needs like medication reviews or upcoming appointments.. These automated call summaries can instantly be added to the patient record, minimizing the risk of missed information.
AI-Assisted Revenue Cycle Management (RCM)
AI automation can also support accurate medical billing and coding, as well as claim preparation. Instead of sifting through lengthy notes manually, clinicians can rely on AI automation to identify billable elements and suggest relevant codes, helping ensure that submissions are complete and compliant.
For Example:
At a multi-specialty clinic, doctors can use AI coding tools to automatically apply the appropriate codes, such as ICD-10 or SNOMED CT, helping reduce manual coding errors and finalize accurate claims. AI-assisted RCM can also shorten reimbursement cycles and give clinicians more confidence that every service provided is properly accounted for.
AI automation in healthcare is now reshaping how clinicians work: from simplifying documentation to improving communication, this only shows how spending more time on patient care is what really matters the most.
Supporting the concept that healthcare access should be accessible for all, Heidi helps in bridging that gap by making post-visit documentation swift and easy.
Try Heidi: AI Automation in Healthcare that Restores Time for Care
Heidi gives clinicians the time back through safe, efficient, and compliant documentation. Designed with human oversight at the forefront, Heidi supports safe and responsible clinical decision-making.
Here are some highlights from a recent impact assessment showing how Heidi improves actual clinical workflows:
- 75% believed Heidi helped them focus more on patient care
- 82% agreed that Heidi reduced mental effort during documentation
- 96% wanted to continue using Heidi AI scribe
Trusted by clinicians worldwide, Heidi supports over 2 million consults each week while meeting global privacy standards and local regulations. With Heidi, transform everyday workflows into moments that put care and people first.
Frequently Asked Questions about AI Automation in Healthcare
When was AI automation first used in Healthcare?
AI automation first appeared in the healthcare industry in the late 1950s when hospitals began using computers for payroll calculations and billing. Over time, digital systems evolved from early electronic health records to today’s real-time AI documentation assistants.
What are examples of AI automation in healthcare?
Examples of AI automation in healthcare include AI-enabled diagnostic imaging, which radiologists can use to identify abnormalities in scans quickly, and AI-powered predictive tools, which help monitor vital signs and lab results to flag early risks. AI automation also supports day-to-day clinical operations through AI medical transcription tools like Heidi.
What is considered advanced AI automation in healthcare?
Advanced AI automation goes beyond data entry to actively improve outcomes and efficiency. A notable example is drug discovery acceleration, where AI analyzes complex molecular data to identify potential treatments faster. Another example is adaptive documentation, where AI assists clinicians by generating contextual notes with full clinician oversight.
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