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By Michelle Lopez
Artificial Intelligence (AI) is reshaping countless industries, and healthcare is no exception. From administrative efficiency to support in clinical settings, AI holds immense promise.
According to a paper from the National Bureau of Economic Research, private payers could see annual savings of $80 billion to $110 billion over the next few years due to AI. And physician groups stand to save between 3% to 8% of their costs, which could mean an additional $20 to $60 billion in savings.
Many organizations have already begun cautiously implementing the new technology. A recent report from Becker's Healthcare shows that 68% of survey respondents in the medical field are currently using AI in their work, with 19% using it daily. From the patient perspective, 96% of those surveyed believe that AI can improve health outcomes, improve the patient experience and lower patient costs.
Yet, healthcare businesses leaders should be aware that this transformative technology also raises critical questions about regulation, reliability and equity in healthcare delivery. The greatest reservations respondents had about the applications of AI all related to privacy, security and ethics.
If you ask any expert in the healthcare field, they will tell you AI has been around for years. Ashwin Kumar Singh, vice president of revenue cycle management at Miami's Jackson Health System and a member of the FIU Healthcare MBA (HCMBA) program advisory board, has been in the industry for nearly 23 years. According to him, anything created to help a human do their job more efficiently could be referred to as artificial intelligence, but he prefers the term "synthetic intelligence."
Singh's primary responsibility at one of the largest health systems in the United States is to preserve the revenue generated by the health system, and to help him do this, he had to create a few of his own algorithms.
"We looked around in the market and there are obviously solutions which are prebuilt but will not take your custom developed algorithms or custom developed solutions," said Singh. "So, we said, ‘You know what? We'll develop our own applications.'"
"When you have the artificial intelligence app listening in the ambient environment, it can summarize, and it's smart enough to learn that there are multiple people in the room. It can differentiate the voice of the patient, and the voice of the two parents or grandparent or anyone and it will gather the clinical data and summarize it."
– Ron Ford
Singh helped develop several complex mathematical models and algorithms, including predictive models that can help anticipate a bad financial outcome before it happens. To bring all the models together in a user-friendly format, Jackson Health System created an entire web application to infuse all the data and generate workflows for users.
"Every tool, every model, this is what the approach was, so that we not only keep an eye on expenses, but we actually ended up optimizing our resources in a big way," said Singh. "It plays a big role in doing more with less. We cut down our expenses in a significant way."
And Singh says the proof is evident.
"Last nine years, we've never missed our cash goal. In fact, we've far exceeded our cash flow for the organization," Singh noted. "You see all the buildings we are building and all the new service lines we're starting right – this all comes out of better financial sustainability."
AI's impact on healthcare can already be seen in areas like medical imaging, administrative tasks and telemedicine. Ron Ford (MBA '18), chief medical officer at Joe DiMaggio Children's Hospital and a member of the HCMBA advisory board, noted AI's utility in streamlining patient care documentation.
At Joe DiMaggio in Hollywood, Florida, a tool powered by AI implements ambient sound recording technology. Once patients opt in, it transcribes physician-patient interactions, reducing the time spent on electronic health records and allowing clinicians to focus on patient care.
Photo courtesy: Joe DiMaggio Children's Hospital."When you have the artificial intelligence app listening in the ambient environment, it can summarize, and it's smart enough to learn that there are multiple people in the room," said Ford. "It can differentiate the voice of the patient, and the voice of the two parents or grandparent or anyone and it will gather the clinical data and summarize it."
Ford says it's all about spending more face-to-face time with patients and their families – and less time facing a computer and typing in the details.
"It's all about value, and when it comes down to it, we want to create or deploy things that are going to add value to the care that we're providing," said Ford.
Despite its promise, healthcare business leaders should understand AI in healthcare is not without significant risks. A key concern is the potential for errors in predictive models, which can lead to false negatives or incorrect diagnoses.
HCMBA advisory board member Alberto Jacir (MBA '15) is a medical director at South Florida primary care provider CANO Health. He cautions the healthcare industry that over-reliance on AI could jeopardize patient safety and stresses that AI must be seen as a tool rather than a replacement for human judgment.
"At this point it's a tool that always needs a double set of verification and validation."
– Alberto Jacir
"Let's say the patient is talking, and a computer transcribes that they did not have history of cancer when in fact, they had a history of cancer," said Jacir. "At this point it's a tool that always needs a double set of verification and validation."
Legal and ethical considerations also loom large. In the U.S., AI in healthcare remains largely unregulated.
"We don't know the impact it'll have on malpractice liability," said Miriam Weismann, who leads the HCMBA program at FIU Business. "The misuse or misapplication of AI can result in very expensive litigation for physicians, hospitals, etc."
She also noted that the lack of interoperability among electronic medical record systems further complicates AI's implementation. Standardizing data across healthcare organizations could unlock AI's full potential, but requires significant investment and oversight.
Ensuring transparency and building patient confidence will be essential for healthcare organizations as AI becomes more integrated into care.
"AI is here to stay - it's not going anywhere. It's transforming almost all aspects of healthcare, from how we collect and manage data to how it integrates seamlessly into healthcare workflows and complements human expertise rather than replacing it."
– Min Chen
"There's interesting questions around the ethics and what we need to do in terms of consent," said Ford. "AI is, by definition, collecting data, a lot of it, and you know that data could be used in ways that it's not intended."
Financial barriers also present a challenge. Many healthcare institutions face budgetary constraints, particularly in rural areas. While AI could enhance telehealth and other services, organizations must weigh costs against other pressing needs, such as maintaining access to basic care facilities.
AI's role in healthcare is undeniably transformative, but its implementation should be approached strategically. Business leaders in healthcare should focus on areas where AI can deliver immediate value, such as administrative efficiency and data interoperability, experts say.
Education and training for staff will be essential. Providers should understand how to work with AI platforms effectively and integrate them to provide personalized patient care. The success of AI in a medical setting will depend not just on the technology itself, but on the willingness of the industry to embrace and adapt to these tools, experts say.
"AI is here to stay - it's not going anywhere," said Min Chen, associate professor of information systems and business analytics at FIU Business. "It's transforming almost all aspects of healthcare, from how we collect and manage data to how it integrates seamlessly into healthcare workflows and complements human expertise rather than replacing it."
At the same time, it is imperative for healthcare leaders to advocate for policies that ensure ethical, equitable and safe applications of AI, she said.
"I think there are definitely challenges and ethical considerations," said Chen. "When data is biased - like in some clinical trials where African Americans or certain female groups have been underrepresented - the AI models trained on that data can end up making biased predictions."
