Commure Up Close: Connor Leads With a Client-First Mindset

Healthcare is undergoing structural transformation. According to Commure CEO Tanay Tandon, the most consequential role of artificial intelligence today lies in concrete changes to how health systems operate versus speculative applications.

“Artificial intelligence is going to play a bigger role than people even realize in transforming the operating model and margin profile of health systems,” shared Tanay Tandon, CEO of Commure.

Across clinical and administrative domains, AI is already influencing the time clinicians spend with patients, the cost structures of provider organizations, and the quality of the patient experience.

Returning Time to Physicians by Eliminating Redundant Work

Commure’s approach begins with one of the most frequently cited burdens on clinicians: documentation. With Commure Ambient AI, health systems are reducing the need for manual note entry by capturing and structuring conversations in real time. The result is a measurable return of time to providers and staff.

“One of the most beautiful things we get to do is give physicians their time back—whether that’s at the end of the day or during the patient encounter,” Tandon shared. “A couple of hours a day, per physician. That translates into millions of dollars of productivity for a system.”

This regained time directly impacts both the financial and human aspects of clinical practice, supporting not only efficiency but also the physician-patient relationship.

Reducing Operational Waste in Revenue Cycle Functions

A second area of impact is revenue cycle management (RCM). Administrative processes, particularly those involving claims and denials, have historically required extensive manual labor. With tools like Commure RCM, health systems can now apply large language models to accelerate and simplify these functions.

“A single claim denial today might require five different people to touch it,” said Tandon. “With large language models, that can become one person reviewing the output. That’s not a five-year or ten-year vision—that’s an 18 month vision.”

By automating repetitive processes and reallocating staff time, health systems may significantly lower their cost to collect from insurance companies.

“The exciting thing there is, if we reduce the cost to collect using LLMs as part of the Commure RCM solution, we can put those dollars back on the table for health systems to serve their patients and their communities.”

Improving Patient Experience with 24/7 AI Guidance

Patients, too, face persistent friction in their healthcare interactions—particularly around scheduling, preparation, and information access. Commure Engage offers intelligent assistance to guide patients through their care journeys, regardless of time of day.

“In some cases, your LLM has the information ready to go, pulled from the EMR. It can respond via text or through a phone call with a natural-sounding voice that’s incredibly helpful to the patient and can guide them through their care journey,” said Tandon.

This continuous availability reduces no-shows and ensures patients arrive informed and prepared. As a result, care encounters become more productive for clinicians and less stressful for patients.

The Cumulative Effect: Toward a More Rational System

What unites these disparate use cases is their cumulative impact. Together they represent a meaningful shift in how health systems manage resources. Time regained for providers becomes capacity for additional patients. Dollars saved on collections may be reinvested in staffing or care delivery. Patients better supported between visits are more likely to return, adhere to care plans, and avoid preventable complications.

None of these improvements require speculative technologies or future-state projections. They are available now, contingent only on careful implementation and a willingness to reconsider legacy workflows. As Tandon’s remarks suggest, the opportunity for transformation lies not in replacing clinical expertise, but in removing the noise that obstructs it.

In short, the application of AI in healthcare operations need not be radical to be consequential. It need only be precise, pragmatic, and anchored in the actual workings of care.

Welcome to Commure Uncharted, a Q&A series where we sit down with healthcare industry thought leaders to discuss what the future of AI in healthcare could look like.

This installment, we are joined by Commure’s Chief Medical Officer, Dr. Jamie Colbert, MD, MBA, who still sees patients and works with clinicians and clients on how AI fits into care. Jamie discusses privacy and the sanctity of the exam room, explains when AI tools can help versus when a person needs to be in the loop, and shares what actually builds trust in busy workflows. He also offers a realistic take on accountability and bias and sets expectations for the next five years.

Q: Looking five years ahead, where do you see AI in healthcare? Will doctors still be face-to-face with patients?

Dr. Colbert:
It’s important to remember that AI is still in its infancy. ChatGPT has only been available for less than three years, so it is hard to predict exactly where things are going. Today, most organizations are not comfortable putting patients in front of AI without a human in the loop for anything high stakes. By high stakes, I mean clinical decisions about how to treat a patient or how to handle a symptom or concern related to their health.

However, I do expect the field to evolve. It may not be very far down the road before we feel confident that AI is drawing on the right body of evidence, providing high-quality recommendations, and handling cognitive tasks that today belong to people with 10 or 15 years of specialized training.

That being said, I do not expect AI to completely replace physicians. AI will replace many aspects of healthcare, but there will still be a need for someone to sit with you, hold your hand, and lay a stethoscope on you. There is a science of medicine, and there is an art of medicine. The humanistic component is essential. It is health care because there is care in it. In the near term, say five years, I do not see a point where we feel cared for entirely by AI.

Q: What are the most common concerns you’re hearing from patients about AI in healthcare?

Dr. Colbert:
There are a few broad categories of concern. First, there is the issue of privacy and what happens to patient information after it is shared with AI. If a large language model owned by a big tech company like Google or OpenAI is involved, what happens to the data that is recorded to generate a note or to power a chatbot? Who has access to it? Could it be used to develop new products? Could someone trace it back to them? Patients worry that the exam room is no longer a sacred space and that their words could show up elsewhere.

Another category is trust in the technology itself and whether AI can provide accurate answers. Is it trustworthy? Is it drawing on appropriate resources? Was it trained on up-to-date datasets, clinical evidence, and studies?

A third category is concern about losing the human connection. Patients value and trust their providers. They worry hospitals and health systems will try to replace that connection with technology, so they no longer have a friendly face when they are not feeling well. There is no substitute for someone holding your hand when you are in pain or uncomfortable. Even if the AI has the correct answers, being alone in a sterile room without a person to offer comfort and reassurance would feel like a loss.

However, on the whole, I find that the overwhelming majority of patients are excited about the potential of AI to help improve their healthcare experience. While they may have concerns, they are on the whole hopeful that AI will be a net benefit to them. 

Q: Do patients trust AI more when it works behind the scenes versus when it interacts with them directly?

Dr. Colbert:
It depends on how the AI is used. When AI works behind the scenes to help physicians stay current and summarize treatment options, the patient is still interacting with their doctor, and the role of the AI is more in the background. In my experience, this tends to be acceptable to nearly all patients. 

Direct interaction varies by task. For something algorithmic like scheduling, many patients are fine with an agent because it is a discrete task that gets them an appointment. When the interaction moves into clinical territory, like what to do next for pain or shortness of breath, the threshold for trust is higher, and some patients will want a person who can answer questions and handle more complex situations.

Q: What’s driving clinician hesitancy around utilizing AI tools in daily workflows?

Dr. Colbert:
A couple of reasons come to mind. Firstly, physicians have been misled in the past by technology that promised efficiency and ended up adding work. Many tools translated to more clicks and more administrative tasks, so there is skepticism about whether AI is really helping or just a shiny object that generates buzz, versus something that will truly make their jobs better and more efficient.

Trust is another issue. For a complex case that might take two or three hours of literature review, AI could summarize the research so a provider spends 20 minutes instead. That can be valuable, but clinicians need to feel confident that the model used the right studies, is current, and did not miss important evidence. The same questions apply to ambient AI. If it listens to a 20-minute conversation and condenses it into 250 to 300 words, it has to be accurate. It also has to make judgment calls about what stays in the note and what gets left out, and providers need to trust how those decisions are made.

There is also the transparency challenge. AI can sometimes feel like a black box, and a physician may not know exactly which sources the AI used to generate its response. Citation is getting better, but there are still questions.

Q: How much of the hesitation around AI comes from technical limitations versus a general fear of change and disruption?

Dr. Colbert:
They are both equally important. It depends on who you speak with and what they worry about, but each is a real barrier to broader adoption. We have not solved the workforce questions yet: where AI fits in the workflow, what changes we make to daily routines, and how those changes make physicians happier and more productive. Providers also look at the outputs that define their work, which vary by role and setting. They want tools that help increase productivity and revenue where relevant, while still letting them enjoy what they do and helping patients feel more cared for.

On the technical side, the models are still evolving. The way to address that is to keep watching them, testing them, and continuing to really poke at them. We need to understand the limitations and the biases, and make sure we do not have blinders on that cause us to miss issues that come from relying too heavily on AI. That ongoing scrutiny surfaces problems and blind spots, and over time it gives us a path to address them as the tools improve.

Q: If AI makes a mistake in a clinical setting, how should health systems think about accountability?

Dr. Colbert:
When a physician has a treatment relationship with a patient, the doctor is ultimately responsible for the care. Physicians who use AI should continue to own the information shared with patients, the visit documentation, and any AI output that directly affects care. That is why there still needs to be a human in the loop for anything that interfaces with patients. The physician is still the one who signs their name and is the one who can be sued if something goes wrong.

Q: How should health systems address potential bias when using AI?

Dr. Colbert:
One approach is to consult other sources and use AI as one tool rather than fully relying on it when there are concerns about bias. Bias can show up in many ways. If a model is more oriented to patients of a certain race or demographic, and the patient in front of you does not fit that profile, you can try to tweak the AI by introducing the patient’s unique characteristics.

If the patient has a disability, for example, make sure the system accounts for the special considerations that come with that. My hope is that as these models improve, we will better account for potential biases by acknowledging differences between patients and steering the output toward recommendations that match what makes that individual patient special, instead of generic defaults.

Q: What is one myth or fear about healthcare AI you wish we could put to rest for good?

Dr. Colbert:
The myth that AI is replacing doctors. Right now, that is not the reality, and patients/doctors should not worry about it. I am not seeing any widescale attempt to fully replace clinicians with AI. Patients should think of AI as tools that help deliver better care so they have a better experience and achieve better outcomes.

Welcome to Commure Uncharted, a Q&A series where we sit down with healthcare industry thought leaders to discuss what the future of AI in healthcare could look like.

We are excited to be joined by Dr. Jean-Luc Neptune, MD, MBA. Dr Neptune has seen plenty of tech waves hit healthcare, but says this one feels different. As Executive Medical Director at Commure, he’s deep in the conversations shaping the future of AI-powered care. In this Q&A, he breaks down what’s more than just hype and how AI is reshaping trust, risk, and the role of the physician.

Q: What makes this wave of AI more transformative than past tech shifts in healthcare?

People forget how disruptive the mass adoption of the Internet was 20 years ago. It gave patients access to previously hard-to-access information, helped them look up symptoms or treatments, and shifted how they interacted with providers, for better and worse. But it didn’t really change how doctors practiced medicine.

What’s different now is that AI, especially the advances we’ve seen since the pandemic, is starting to shift how doctors actually think, diagnose, and recommend treatment.

We’re getting close to a point where patients could have healthcare encounters that are handled entirely by AI, without a human involved.

That kind of interaction would be a major shift from anything we’ve seen before.

If you had asked me five years ago whether a computer could handle an inbound patient question with 95% satisfaction, I would’ve said not a chance. But we’re on the verge of that now. We may not be ready to let AI run fully on its own, but the tech is at a point where it could handle a lot more than we’re currently allowing.

Q: Where do people most misunderstand AI’s role in clinical care?

The biggest thing people miss is how fast this technology is evolving. We tend to think about rate of change in linear terms, but tech often evolves in an exponential fashion. There have been decades of work behind the scenes on AI, and now it's finally starting to show up in real clinical settings. What feels advanced today will likely look basic in five to ten years or less. Most people aren’t prepared for how different things could look in a short period of time.

Q: As AI takes over more of the technical (administrative) tasks, what will define a great doctor?

What makes a great doctor hasn’t really changed; it’s still about communication. Patients remember the doctors who listened and connected with them. But the profession has long prioritized memorization and clinical reasoning. That’s what gets rewarded in medical school and residency.

As AI takes over more of those tasks, the real value will shift to how well a doctor can communicate, build trust, and leverage information.

When you encounter a brand-new patient in the clinic and you don’t know anything about that person, it takes skill and presence to collect what you need to make a diagnosis and build a care plan.

Beyond communication, doctors will need stronger management skills. Today, a typical primary care physician manages 2,000 to 3,000 patients. With the right technology to scale our clinical efforts, that number could grow massively - why not to 10,000 or more? AI can help identify who needs attention and when, but doctors will have to think more like care managers, not just clinicians. That shift isn’t emphasized in training today, but it’s going to become essential.

Q: Will physicians shift from diagnosing to orchestrating care?

I think you’d have to be naive to believe there won’t be a day when computers are better at diagnosis than people. We’re in the middle of that transition now as providers and patients are starting to see the potential, but are still adjusting to the idea.

At some point, maybe sooner than we expect, patients will trust the machine’s answer more than the doctor’s. Patients will ask their doctor, “What did the computer say?”

This mental shift happened long ago in areas like weather forecasting, where no one asks for a human opinion; they just check the model. Even as a physician, I’ve reached a point where I want to know what the AI thinks. When my wife had a mammogram recently, we opted for the AI readout (which cost an extra $25) because I believe it can add real value.

If AI handles more of the diagnostic work, then physicians will need to focus on what happens next. That means making sure patients get their medications, stay on their treatment plans, and understanding why they’re not following through if they aren’t. It also means shifting attention from what happens in the office to what’s happening outside the office. Patients spend most of their time outside the clinic, and that’s where their care often breaks down.

Q: With the rise of 24/7 AI-driven care, how do you see continuity of care evolving? Can technology really support long-term patient relationships?

As long as it’s clear that the technology is being used to support the care team, not replace it, patients are generally comfortable. When I worked at Memora (which was acquired by Commure in December 2024), that was always our message: this is a tool that helps your providers take better care of you. People were open to that and willing to engage.

As the technology improves, it becomes easier to imagine a different kind of patient experience. Instead of brief check-ins every couple of months, we could move toward continuous care, with your providers always present in the background.

In an ideal future, your doctor will be monitoring your status around the clock. Most of the time, nothing of clinical importance happens. But when something does (for example, your blood pressure spikes or your diabetes gets out of control), that’s the day your care team gets notified and steps in. That’s the kind of real-time responsiveness we’ve never had at scale, and that’s where this technology has real potential to raise the quality of care.

Q: Who’s accountable when AI gets it wrong: the doctor, health system, or developer?

That’s the big question, and it’s one I rarely see people address, probably because most people have never had to purchase malpractice insurance and think through the medicolegal questions associated with practicing. I purchased my own malpractice insurance for a number of years when running my mental health/substance use startup, and I can tell you that it really impacts your thinking and the risks you’re willing to take as a provider.

Right now, if there’s a bad clinical outcome, the physician and the provider organization are almost certainly going to get sued. But what happens when that bad outcome occurs because of a bad recommendation from an AI system?

If it’s a malfunctioning product, I know there’s a product liability framework that can be used to address any harms done to a patient, but it’s something we’re going to have to reckon with, especially as we move toward AI-only interactions.

In my opinion, we are already seeing this liability concern slowing adoption rates. Physicians don’t think in aggregate; they think in individual outcomes. One mistake can ruin a career, so providers tend to be very cautious in how they embrace new tools.

In the tech world, a 98% success rate is considered excellent. In healthcare, however, 98% isn’t good enough if the remaining 2% leads to real harm.

Q: What do you see as the most important opportunities—and risks—that AI brings to healthcare right now?

It’s a really exciting time, but big shifts like this can be unsettling. One of the many concerns we hear from customers is about job loss. That’s understandable, many people live with real financial insecurity, and the idea that new technology could make large parts of their workforce obsolete is hard to hear.

But AI also gives us a chance to finally address some of the biggest issues in healthcare. Thirty million people in the U.S. are uninsured. For many of them, even a solution that’s 90% as good as seeing a doctor, but costs $10 a month, could be life-changing. Too often, we treat “not perfect” as unacceptable when in reality, a lot of people have no access at all. We’re already seeing people use tools like ChatGPT to self-diagnose, which provides way more accurate results than when people first started using Google as an alternative to speaking with their physician. That’s not ideal (I think patients should be working with providers to access health resources), but it’s a signal that people are ready to engage if the tools are there.

Cost is the next challenge. We’ve been talking about rising healthcare costs since I was in business school over two decades ago, and they’ve only continued to rise. If we can use machines to deliver care more efficiently, we have a real shot at making the system more sustainable.

And then there’s quality. Doctors are human; we make mistakes, we fall behind on guidelines. AI can help raise the baseline by making sure we’re working with the best available information. There are still plenty of tough questions to answer, but the momentum is real. AI isn’t going away, and you can’t put the genie back in the bottle, so we have to figure out how to make it work.

At this year’s MUSE Inspire Conference, Dr. Geoffrey Burnham, Hospitalist Medical Director at Medical City Dallas, one of the largest hospitals in HCA’s system, joined Commure’s Chief Business Officer, Hersh Solanki, for a fireside chat at Commure’s Product Showcase: “Seamless, Smart, Ambient: Redefining Healthcare Workflows with Commure and MEDITECH.”
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As a proud MEDITECH Alliance partner, Commure kicked off with a live demo of Ambient AI, a MEDITECH-vetted solution that seamlessly integrates with Expanse. The conversation then pivoted to Dr. Burnham’s first-hand insights into developing and rolling out Ambient AI, and the impact it’s already having. 

What started as a pilot program with one physician has now expanded to the Medical City Dallas team and across the rest of the facilities within the HCA North Texas division, with roughly 200 users in total. According to Dr. Burnham, the change has been fast, meaningful, and driven by a strong partnership between clinicians and Commure’s engineers.

Since deploying Commure Ambient AI, providers in the North Texas division have experienced: 

From accurate documentation and improved reimbursement to more time for meaningful patient care, Dr. Burnham shares how this MEDITECH-integrated solution benefits every stakeholder.

“There’s the provider, there’s the patients, and then there’s the hospital itself.”

Focusing More on Patients with Faster Notes

Dr. Burnham explained why he was eager to try ambient documentation in the first place: “One of the things I've always kind of despised about medicine is writing notes.”

Dr. Burnham is not alone in this perspective. In a recent survey, 62% of providers pointed to administrative work as their top source of burnout. Dr. Burnham shared that since its roll out, Commure Ambient AI has made a tangible difference in how he and his team approach documentation at Medical City Dallas. "I know everything I'm doing is getting captured and I just kind of have to put that little bow on it and I'm done.”
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That extra face time has had a ripple effect across the patient experience: “I never want patients to feel like I'm rushed.  This helps make sure they don’t.”

Driving Better Coding and Billing, For the Provider and the Hospital

Beyond just saving time, Commure Ambient AI directly impacts billing and reimbursement by improving the quality and completeness of documentation. It does this by acting as a built-in safety net for coding:

“[Ambient AI] helps with my coding too. Sometimes I’ll catch something I missed, like a patient mentioning they were constipated, and realize I forgot to order Miralax. It gives me little reminders.”

The end result? More accurate documentation, better reimbursement, and more time for meaningful patient care.

“I don’t have to rush through my day. I can actually sit there, spend the time I need with the patient.”

Co-Creating the Product in Real Time

What made this rollout different, Dr. Burnham emphasized, was how closely he was able to collaborate with Commure’s engineering team.

“I was a “guinea pig” with HCA’s Digital Transformation and Innovation team.  I started working with Commure about a year ago... we took it from the beginning and built it into what it is now.”

He had a direct line to the Commure’s Forward Deployed Engineering (FDE) team, even after hours:

“I’d be texting them at 1:00 in the morning with ideas and feedback and a couple of them would still be awake because they’re okay with it. That’s when I was writing my notes.”

That real-time support helped accelerate development and adoption, according to Dr. Burnham: “It took us two to three weeks and then I could start signing those notes for my patients in the hospital and feel comfortable doing so.”

From that starting point, his team helped shape key features like History & Physical (H&Ps) specific templates, discharge summaries, and embedded feedback tools to the engineering team, which were often improvements that Commure’s FDE team implemented in just a matter of weeks.

Boosting Trust and Adoption Through Transparency

For many providers, handing off documentation to AI raises important concerns about accuracy and accountability. Dr. Burnham acknowledged that building trust was a key part of adoption, and that transparency was critical in making that possible.

“The last thing any clinican wants is any kind of legal issue where it’s like, ‘Okay, you documented this in the note.’ You’re like, ‘No, that wasn’t me, that was the AI.’ But when you have those track changes and you can see what’s going on, you can trust in the product.”

That’s where Commure Ambient AI’s “track changes” view comes in during the clinician’s review. Providers can see a side-by-side comparison with red and green highlights and strike-through formatting. “That transparency is critical for trust,” he said. “If the AI took this out of my last note and added this to my current note, then I know it has everything I need, and I can move on.”

The impact of this close partnership and solution is catching on as the North Texas division adopts Ambient AI at all sites, and providers are eager:

“Most providers were asking us, ‘When can we get this? Is it our turn yet?’ The adoption rate has been great.”

What’s Next: Further Enhancing and Iterating at Speed

Looking ahead, Dr. Burnham sees even more potential. He outlined several needs and future features:

• Discharge summary optimization
• Automated admission order sets
• Medication formulary mapping
• Color-blind accessible diff view
• Summarization of outpatient encounters and inbox messages

Some of these features are already in development, including order queueing and real-time voice queries into MEDITECH.

Dr. Burnham shared, “There’s a lot more we can do, but the pace we’re moving at is faster than I ever expected in a system of this size, with an EHR of this size.”

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Advice for Other Health Systems Considering AI

For leaders exploring ambient documentation or clinical AI tools, Dr. Burnham offered straightforward guidance:

“Having the folks who are willing to partner with you... that’s what you need to build a great product.”

He underscored the importance of involving providers early and often, and building a system that allows feedback in real time. All levels of the organization need to be bought-in, from senior levels of leadership down to end-users.

“The easier that is, the easier the change can be made... because we all practice differently, we all train differently. No one of us writes notes the same.”

Reclaiming Time in Medicine with Ambient AI

Commure Ambient AI has helped transform documentation from a burden into a streamlined, provider-friendly process at Medical City Dallas. But perhaps most importantly, it’s given time back to clinicians, so they can give more of it to patients.

As Dr. Burnham summed it up, “I think probably for most of us, 10% of your day is actually practicing medicine and the other 90% is writing notes or doing billing. This helps shift that balance back to where it should be.”

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Learn More About Ambient AI for MEDITECH

Tell us a little bit about yourself—what do you like to do outside of work?

Outside of work, you can find me attending concerts, trying new restaurants, at the gym, or rollerblading on the boardwalk in LA. I consider myself a massive foodie, and I love a great dining experience. I think it's the best way to bring people together. 

I am an avid traveler as well, and find so much joy from learning about new places and cultures. Most recently, I went to Medellín. My favorite place I have visited, and continue to visit, is London. Don’t sleep on the food scene there! It is truly incredible. 

I am a textbook extrovert and love meeting new people in any setting. My friends describe me as the most extroverted person they know. Makes sense why I ended up in a people-centric job!

As a kid, what did you want to be when you grew up?

So many things! At first, I wanted to be an ice skater. After watching Tara Lipinski compete at the 1998 Olympics, I was obsessed. I even dressed up as her for Halloween once. 

After I decided that becoming a professional ice skater wasn’t in the cards for me, I turned to another likely profession: becoming a pop star! I love music and singing, and spent many years in choir and learning guitar. Unfortunately (and unsurprisingly), that didn’t work out for me either. 

In college, I majored in finance, but always knew my strength was in People. After working at a FinTech startup and doing a stint in real estate, I made a very conscious pivot into recruiting. I had sat next to the recruiting team at my first job out of college, and always felt curious and interested by their day-to-day. I decided to make the leap and started my recruiting career at Uber. After a year, I knew it was a great fit for me. 5 years later, I've found my niche. No looking back.

Describe a day in the life of your role.

My day-to-day involves working with candidates and internal stakeholders. I conduct first-round interviews with candidates multiple times a day for various roles, and love learning about people’s backgrounds and what they specialize in. I then take candidates through the entire interview process. My favorite part of the role is extending offers to candidates and having them join the Commure team. It makes me feel like I make a difference. 

Internally, I partner with leaders within Commure to understand what they are looking for in the ideal candidate to join their teams. I love being able to understand the nuances of the various positions here and how our teams operate. 

Recruiting is a fast-paced, high-intensity environment. We move fast, and staying organized is paramount to success. I always want to ensure I am providing a white glove experience to candidates and hiring managers, which involves a high level of communication. I'm sure some hiring managers are sick of seeing my name pop up on their screen asking for feedback, but it's an important part of the job.

I have hired individuals across almost every department: Sales, Product, Marketing, Engineering, Accounting, Finance, and Operations. 

What made you decide to join Commure?

One of the main things that drew me to Commure was its mission. I love working for a company that actually makes a difference in people's lives, specifically in a space where so much improvement is needed. It makes coming to work each day a bit more meaningful. 

Additionally, I loved that Commure is such a fast-growing company. I have learned more over the past 2.5 years than I have in the previous 4. The ability to work on so many different roles with so many different stakeholders keeps me on my toes and has helped me to become an even more impactful recruiter. 

How would you describe the Commure company culture?

Commure moves faster than any company I have ever worked for. In order to be successful here, you need to be able to keep up with an ever-changing environment. What I love about this is that we have such large scopes of work, and you are able to make a tangible impact fast. 

We are a culture of thinking outside the box, and we encourage people to try new things. There is very little red tape here, which gives employees autonomy to do their work and progress fast in their careers. It's something that I have never seen anywhere else, and one of the main draws to working here.

I have seen us grow so much over the past 2.5 years, and there are no signs of slowing down. I can’t wait to see what the next 2.5 years have in store for us. 

What advice would you give someone on their first day at Commure?

You might be overwhelmed with how much there is to learn, but don’t fret. We have a team of amazing individuals who want to help you learn and grow. Things can feel fast, but after you adjust, you realize it’s one of the greatest benefits and strengths of this company. 

I always let new hires know that the people who do the best here are not afraid to ask questions and to ask for help. We have amazing people and leaders who want to see their teams succeed, you just have to be willing to raise your hand!

What has been your greatest accomplishment so far at Commure?

I think my greatest accomplishment has been hiring some amazing senior leaders here at Commure. It has been awesome to see how the investment in amazing leadership has paid off for our company’s growth. 

Additionally, I love to see how far the recruiting team has come since I joined. I started at Commure with a recruiting team of 2, with very little process or structure. Now, as a team of close to 10, we operate a well-oiled machine. I can’t take the credit for this (shoutout Jason Wong), but it’s been really rewarding to be a part of the transformation.

Interested in a career building the next generation of healthcare technology powered by AI? We are always looking for talented people across our departments.

Explore Career Opportunities

Interest in healthcare AI is growing fast. NVIDIA’s 2025 State of AI in Healthcare and Life Sciences survey found that 63% of respondents (more than 600 healthcare professionals spanning medical technology/tools, digital healthcare, pharmaceutical, payers, and providers) are actively using AI and 81% say it has helped increase revenue at their organization.

As innovative health systems and practices across the country are implementing AI solutions to streamline their workflows, some patients and care teams remain hesitant. The caution makes sense. Questions about safety, transparency, and reliability are valid in an industry where there’s little margin for error.

It’s up to healthcare leaders and technology providers to bridge that gap. Building trust in AI means understanding the concerns behind the skepticism and addressing them directly.

Common AI-Related Concerns Among Patients and Providers
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• Privacy and security: Patients and providers worry about data misuse or breaches. In one survey, 63% of patients and 87% of physicians flagged privacy as a top concern.
  
  
• Transparency: AI systems often lack clarity around how decisions are made, raising fears of hidden bias or errors.
  
  
• Accuracy: Misinterpretations can have serious consequences, especially when AI is used in diagnosis or treatment planning.
  
  
• Job security: Some clinicians see AI as a threat to their roles, which can slow adoption and fuel skepticism.
  
  
• Education gaps: Many users don’t fully understand what AI can and can’t do, making trust harder to build.

Turning AI Skepticism into Confidence

Patients and providers have valid concerns about AI in healthcare. But when implemented responsibly, AI can free up clinical time, reduce administrative burden, and improve the consistency of patient communication. For healthcare leaders, building trust starts with selecting the right solutions and creating clear strategies to earn buy-in across the organization.

‍Choose AI Tools With Safety at the Core

AI in healthcare takes many forms. Some tools generate responses from training data, while others rely on preset clinical content. Large language models are now capable of generating responses to a wide range of inputs and can even perform tasks such as data entry. However, AI models can also provide inaccurate responses. Grounding these models in clinical data, clinical guidelines, and scientific evidence helps to ensure that answers will be on-target. Furthermore, some AI systems also include safeguards that include continuous monitoring of model performance to minimize that risk. 

For health systems, trust begins with choosing technology that’s designed for safety. Leaders should evaluate how each system works, what information it relies on, and how it supports clinical oversight. Those decisions help ensure the tool strengthens care while minimizing risk.

Know the Source of Your AI’s Data

AI is only as good as the data behind it. When inputs are flawed, outputs follow suit. Inaccuracies, hallucinations, and outdated information have already cost organizations across industries. In healthcare, these risks are even more pronounced as they carry both a financial risk and are tied to patient trust. One Medscape survey found 88% of physicians worry about generative AI delivering inaccurate health guidance. Meanwhile, a Salesforce survey found 63% of patients share concerns about compromised or misleading information.

That’s why healthcare leaders must evaluate where an AI platform’s information comes from and how it’s maintained. Commure’s patient experience solution, Commure Engage is built on a clinician-curated content database developed with ongoing input from health systems. This ensures guidance reflects current practice and stays within defined clinical boundaries, giving patients reliable support and keeping care teams in control.

Equip Your Teams With Clarity and Confidence

Uncertainty about job loss are common when new technologies are introduced, with 65% of physicians reporting concerns about AI making diagnosis and treatment decisions. But in healthcare, most AI tools are designed to streamline administrative tasks, not replace clinical judgment. Charting, patient follow-up, and care coordination are just a few examples of workflows AI can help simplify, giving staff more time to focus on patients.

Leaders play a key role in shaping how these tools are received. Clear communication about what AI can and can’t do helps reduce fear and misinformation. Staff should know how AI will be monitored, how it fits into care delivery, and how to raise concerns. With the right education, teams are more likely to adopt these tools with confidence and use them effectively.

Look for a Technology Partner with a Clear Responsibility Framework

Responsible AI begins with clear values. As developers adapt to a shifting ethical landscape, they should be able to show how their platforms are built with safety and accountability in mind. When evaluating vendors, ask whether their principles are designed specifically for healthcare and whether they’re embedded in the product, not just marketing.

At Commure, our framework focuses on:

• Safety and reliability: Built to perform as intended, with safeguards in place from the start.
  
  
• Human oversight: Designed to keep clinicians in control, with transparent review and feedback loops.
  
  
• Equity and fairness: Developed to reduce bias and expand access, especially for underserved groups.
  
  
• Privacy and security: Structured to meet HIPAA standards and protect patient data at every level.

Trust Drives Impact

AI has the potential to reshape how care is delivered. But its value depends on trust. For platforms to succeed, patients and care teams need to know the technology is safe, reliable, and thoughtfully designed. That trust is built when developers listen to users, address real concerns, and ensure every solution reflects the needs of the people it serves.

Ready to see why Commure Engage is trusted by both patients and providers?

Explore the Engage Platform

AI is taking the healthcare industry by storm, with nearly two-thirds of physicians reporting utilizing AI in 2024, up from only 38% in 2023. Being able to easily integrate AI tools into existing workflows and quickly find new use cases is key to success. This is where AI healthcare assistants are becoming essential tools. Unlike past digital assistants (such as chatbots or phone-based interactive voice response (IVR) systems), today’s AI healthcare assistants can adapt, learn, and operate across clinical, operational, and financial workflows.

Innovation leaders across the country are reviewing AI healthcare assistants and agents to streamline workflows from patient access to back-office operations. But with so many options, the questions remain: Which use cases are real? How are AI healthcare assistants actually delivering value today?

AI Healthcare Assistants vs Traditional Healthcare Automation

Traditional automation tools in healthcare (like IVR systems or chatbots) follow fixed scripts and often lack the flexibility to respond to real-world complexity. AI healthcare assistants (also known as AI Agents or Agentic AI) are built differently. By utilizing generative AI/natural language processing and integrating in real-time with EHRs and hospital systems, they support a wide range of users and tasks, from guiding patients through appointment scheduling to helping staff manage intake, billing, follow-up, and more.

These assistants work across clinical, operational, and financial workflows, processing information in real time. This ability makes them far more effective than earlier systems that required manual oversight or constant updates.

Commure Agents take typically point-solution-based AI healthcare assistants a step further by delivering these capabilities through a single, modular platform. Built in close collaboration with clinical teams, the tools are designed for ease of use and rapid deployment. They integrate with existing infrastructure, allowing health systems to address targeted needs first and scale over time. The result is a smarter approach to automation that improves outcomes without adding complexity.

Clinical, Operational, and Financial Use Cases for AI Healthcare Assistants

Clinical Use Cases

Leading health systems are embedding AI healthcare assistants into clinical workflows to increase efficiency and support care quality. One of the most prominent uses is ambient documentation, where the assistant captures and structures notes during a patient encounter. This reduces the time providers spend charting and improves the completeness of clinical records. Providers using Commure Ambient AI see an average 81% reduction in overall clinical documentation time.

AI healthcare assistants can also trigger timely post-visit follow-ups, checking on symptoms, recovery progress, or medication adherence. By automating these touchpoints, health systems can stay connected with patients between visits without adding to clinician workload.

Operational Use Cases

Front office staff also benefit significantly from AI healthcare assistants by automating patient intake, verifying demographic data, and flagging missing information before the visit even starts. AI healthcare assistants can also handle appointment scheduling and rescheduling, reducing call volumes and administrative backlogs.

Pre-visit instructions, such as fasting requirements or parking details, can be sent automatically and adjusted based on appointment type. These improvements enhance operational efficiency and patient preparedness, which translates into fewer delays and a smoother front-desk experience.

Financial Use Cases

For billing teams, AI healthcare assistants ensure smoother transactions and better communication. They can verify insurance eligibility, confirm benefits coverage, and flag issues that might delay payment. By prompting patients to update insurance information or submit missing documentation, these assistants help reduce claim denials.

They also automate payment reminders and offer flexible payment plan options based on patient eligibility. This improves revenue cycle performance while making the process less confusing and more transparent for patients.

Closing the Gap Between Hype and Results

Virtual assistants used to mean clunky phone trees or websites that couldn’t answer basic questions. That’s no longer the case. The most effective tools today use advanced AI and are embedded in clinical and operational workflows, built for outcomes from the start. They integrate with existing systems, adapt to user needs, and begin delivering value without long implementation cycles.

Commure brings this into a modular, interoperable platform that is co-developed with the clinical teams using it. This foundation keeps the focus on what matters most, providing excellent care, capturing revenue, and making the most out of clinician time.

See What’s Possible With AI Healthcare Assistants

“I was getting to the point where I was considering changing my career because I just had no life… I’m now incredibly happy. I left for a two-week vacation with absolutely nothing on the table and could walk away without any stress.” - Andrea Hazelton, FNP-C @ Pioneers Medical Center

This is just one of countless examples of clinicians across the country who are drowning in documentation, and how utilizing AI-generated doctor’s notes can help.

In fact, clinicians now spend an average of 16 minutes per encounter in the EHR, 11% of it after hours. Nurses report spending 19–35% of their entire shift documenting, a sharp increase from 9% in the paper era.

With this much time spent on administrative work, it's no surprise that 43% of clinicians report at least one symptom of burnout.

To add to that, health systems are under more pressure than ever to improve efficiency and maintain rigorous documentation standards. AI-powered doctor's notes offer a promising path forward. Here's what you need to know.

What Health Systems Should Expect From AI Doctor’s Notes

AI-enabled documentation is rapidly becoming a baseline capability. But as the market grows more crowded, the gap between commoditized features and enterprise-grade performance is widening.

For health systems, the real question is not whether to adopt AI-generated notes, it’s how to choose a solution that delivers measurable, system-wide value. That starts with identifying the operational outcomes that matter most:

• Reducing denial rates and billing friction
  
  
• Accelerating reimbursement through more streamlined claims
  
  
• Lowering clinician after-hours charting time
  
  
• Improving consistency in documentation across teams
  
  
• Scaling seamlessly across departments without heavy lift

Vendors may check the same boxes on a feature sheet, but implementation success and sustained value hinges on how well those tools work in reality.

Why Going Beyond Dictation is a Necessity

Legacy AI doctor notes tools still require clinicians to record their thoughts after the visit and often involve manual entry or editing. That workflow hasn’t kept up with modern clinical demands.

More advanced AI-powered documentation tools change the dynamic:

• Documentation starts and ends in the exam room: No need to circle back post-visit or piece together notes from memory.
  
  
• Every note reflects the full clinical picture: Tools pull in prior labs, diagnoses, and medications automatically.
  
  
• Nuance is preserved, noise is removed: Small talk is filtered out while clinically relevant cues are retained.
  
  
• Less screen time, more patient time: Providers can engage directly without toggling between note fields.
  
  
• Notes are directly integrated with EHRs and beyond: Structured output drives billing, coding, reporting, and workflow handoffs.

These advanced tools are already in use at leading health systems. At Dignity Health, providers using AI-generated documentation cut their charting time by up to 41%, freeing them to focus more on patient care.

What Health Systems Should Look For When Choosing an AI Doctor’s Note Solution

Not all AI-generated notes are created equal. Health systems evaluating tools should ask:

• Does the solution support multiple languages across diverse care settings?
  
  
• Does it support real-time documentation during multi-speaker conversations?
  
  
• Are the outputs structured enough to feed into coding, billing, and compliance systems?
  
  
• How fast can the platform be deployed and configured for different specialties?
  
  
• What clinician satisfaction or adoption metrics has the vendor demonstrated post-implementation?
  
  
• How customizable is the system for different note styles, specialties, and documentation templates?
  
  
• What level of human-in-the-loop quality control or review is included in the workflow?
  
  
• How transparent is the AI’s decision-making when it comes to clinical inferences or omissions?

Ultimately, to drive real impact, documentation tools must enhance, not complicate, how providers work day to day.

Commure Ambient AI is Built to Deliver at Scale

Commure Ambient AI moves beyond basic transcription by generating complete, structured, EHR-integrated notes without added steps.

At Commure, health systems using Ambient AI report up to 81% less time spent on charting and a 25% drop in claim denials. That impact is driven by the system’s ability to understand clinical context, reference relevant history, and produce notes that are ready for coding, compliance, and reimbursement.

For health systems looking to modernize documentation, the goal should be better outcomes through streamlined workflows. Ambient AI offers a path to scale efficiency and quality without adding complexity.

Explore Commure Ambient AI