AI in Healthcare: Where We Stand & Where We're Headed

Part 1 of 8

A few years ago, I was asked to give a short presentation on artificial intelligence (AI) in healthcare to a group of Medical Group Managers here in West Virginia (WV). It was meant to be a quick talk with just an overview and a handful of slides. But that brief conversation turned into something much bigger for me.

Since then, I’ve spent countless hours digging into the subject. I’ve read peer-reviewed studies, followed pilot projects, talked with doctors, nurses, and administrators, and reflected on my own years in healthcare IT.  It led to more than a few late-night pondering sessions about what AI really means for patient care, for the business of medicine, and for the people on both sides of the stethoscope. And I’ve concluded, as we all have at this point, that AI is not just another “shiny new thing.” It’s a disruptive force that’s already reshaping healthcare behind the scenes, and its impact is going to be felt in every exam room, ER, and back office.

For me, this isn’t theoretical. My career in healthcare IT began in the mid-90s at St. Joseph’s Hospital in Parkersburg, WV, back when we had a single personal computer and NCR and IBM mainframes ran the show (I can still see the green and amber screens scorched into my retinas!). I stayed through multiple ownership changes and department outsourcings with moves to Systematics, Alltel, Eclipsys, Columbia HCA, and ultimately HCA Healthcare before taking similar jobs with Triad Hospitals and then Perot Systems. 

The next chapter was founding Biztec in 2008.  One of our biggest verticals was healthcare - naturally because of my network of connections. We started serving hospitals, medical groups, clinics, and ambulance services across the state. Needless to say I have seen some serious changes, I’ve lived through Y2K, HIPAA’s rollout, the rise of PACS and EMRs, bedside charting, barcode scanning, and pharmacy robotics.

That’s the lens I’m bringing to this blog series: not a tech futurist looking in from the outside, but someone who’s been inside the engine room for three decades, watching technology change the way care is delivered. (Goodness, I am getting old.)

I’ve seen technology ease burdens and improve patient care. I’ve also seen technology, poorly implemented, ultimately becoming a barrier between provider and patient.

It is a big subject, and I can get windier than a sack of rear-ends. But don’t fret, we will split this bad boy up for you.  This is the first post in a multi-part series, and it’s the “big picture” one; it’s the roadmap, if you will. We’ll cover the state of AI in healthcare today, explore three high-impact tools, look at risks and rewards, and talk about how these changes could play out in West Virginia and beyond. In future posts, we’ll take each of these areas and drill deeper.

Where We Are Now

If you are a nerd like me and follow healthcare headlines, it might seem like AI is everywhere in healthcare (Cue scary music and visions of SkyNet). There are tools that help in diagnosing cancers, predicting cardiac events, chatting with patients. And yes, there’s been an explosion of AI tools and pilot programs. All of that is amazing. But when you dig deeper, you’ll find a more modest reality: most AI in healthcare is still in its early stages, especially outside large academic medical centers. They always get the cool toys first.

Right now, and I know this is highly generalized, but most AI adoption falls into three categories:

• Automation of administrative tasks – coding, documentation, scheduling.

• Clinical decision support – highly focused tools in radiology, dermatology, pathology.

• Operational optimization – predicting staffing needs, managing supply chains.

A 2024 Health Affairs survey found that fewer than 20% of U.S. hospitals use AI routinely for direct patient care decisions. The back office is where AI is gaining traction first. I know they do not need my endorsement, but I have found that to ring true in my real-life observations.

Here in WV, the picture is a mixed bag. Large systems like WVU Medicine are experimenting with AI imaging support, predictive analytics for patient deterioration, and chatbots for appointment triage. In contrast, smaller rural hospitals and independent clinics often don’t have the IT infrastructure or bandwidth to test these tools.  I have had these talks with the people that are in the game, and I’ve heard administrators say bluntly, “We don’t even have enough bandwidth for Telehealth, let alone AI.”

Even so, the direction is clear as we see this pick-up steam; and it will run you over if you don’t get on the train. As of the last few months, The FDA has approved more than 1000 AI-enabled medical devices according to data I found from several sources. In anticipation of this trend, the WHO has issued ethics guidance for AI in health, emphasizing transparency, human oversight, and equitable access. The National Academy of Medicine is drafting an AI Code of Conduct. It is not just coming down the pike, it is here, and it’s bringing its friends.  If that information is not enough, follow the money.  It always tells the tale: major industry players are embedding AI into the very systems healthcare already uses:

• Epic – Dominates the U.S. EHR market and is embedding Microsoft Azure-powered AI tools directly into clinical workflows.

• Cerner/Oracle Health – Epic’s main EHR competitor, now backed by Oracle’s AI and cloud infrastructure.

• Microsoft – Owner of Nuance (Dragon Medical and DAX), powering many ambient documentation and voice-to-note systems.

• Google – Through Google Health and DeepMind, building AI models for imaging, EHR analysis, and predictive care.

• Amazon Web Services (AWS) – The largest health data cloud host, offering specialized AI services for analytics and model deployment.

• Philips, Siemens Healthineers, GE Healthcare – Global leaders in imaging systems, now embedding AI directly into diagnostic equipment.

The decisions these companies make from what AI features they build, how they integrate them, to how they price them, will shape adoption timelines nationwide, including here in WV. Incoming!!!!

The Series Ahead: Exploring AI in Healthcare

Hopefully I didn’t bore you too much because there is much more to cover. This is just the beginning. In the coming weeks, we’ll break down the most promising AI tools and strategies in healthcare. I will sort through the hype and focus on the practical realities, the risks, and the potential rewards. Here’s what’s coming:

• Part 2: Ambient Documentation – Bringing Back the Human Side of Medicine.

• Part 3: Imaging Assist – When AI Sees What We Might Miss.

• Part 4: Revenue Cycle Automation – The Hidden Hero Keeping the Lights On.

• Part 5: The Dual-Track Strategy – Winning Now While Building for Tomorrow.

• Part 6: Keeping AI Safe – Managing Bias, Burnout, and Bad Habits.

• Part 7: The Road Ahead – AI in Healthcare Over 5, 10, and More Years.

• Part 8: Making Sure West Virginia Isn’t Left Behind.

In Part 2, we’ll dive into ambient documentation - how it works, what the research says, and how it might just be the burnout cure rural clinics have been searching for.

Sources

American Medical Association. “For Every Hour of Direct Patient Care, Nearly Two Hours of EHR Work.” Health Data Management. Accessed August 2025. https://www.healthdatamanagement.com/articles/ehr-use-consuming-physicians-time-for-patients.

Sinsky, Christine, et al. “Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties.” Annals of Internal Medicine, vol. 165, no. 11, 2016, pp. 753–760. https://adfm.org/media/1476/ann-2016-time-study.pdf.

U.S. Food and Drug Administration. “Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices.” Accessed August 2025. https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices.

MedTech Dive. “FDA Authorizes 950 AI/ML-Enabled Medical Devices as of August 2024.” August 7, 2024. https://www.medtechdive.com/news/fda-ai-medical-devices-growth/728975/.

Becker’s Hospital Review. “FDA’s List of Authorized AI-Powered Medical Devices Quietly Grows.” Accessed August 2025. https://www.beckershospitalreview.com/supply-chain/fdas-list-of-authorized-ai-powered-medical-devices-quietly-grows/.

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About the Author

Joe Sams is a seasoned business and technology leader with decades of experience building high-performance teams and scaling IT organizations. He has led transformational initiatives in cybersecurity, managed services, and cloud technologies. His leadership philosophy centers on mission-first thinking, servant leadership, and cultivating cultures of accountability and innovation.

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Definitions:

• Artificial Intelligence (AI) – Technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy. (IBM) 

• Information Technology (IT) – A broad term that defines the use of computer systems or devices to access information. (CompTIA)

• Health Insurance Portability and Accountability Act (HIPAA) – The HIPAA Act of 1996 establishes federal standards to protect sensitive health information from being disclosed without patient consent. (CDC)

• Picture Archiving and Communication Systems (PACS) – A digital medical imaging technology system used to store, retrieve, and transmit medical images captured from devices like MRI, CT, and PET scanners. (HIPAA Journal & TechTarget)

• Electronic Medical Records (EMR) – An electronic, or digital, collection of medical information about a person that is stored on a computer. This includes things like vaccination records, medical diagnoses, tests, and more. (National Cancer Institute)

• Telehealth – The use of digital information and communication technologies to access and manage healthcare services remotely. (Mayo Clinic)