How AI Will Reshape Medical Research and Healthcare Delivery with Giovanni Piedimonte, MD

Summary

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Podcast Summary: "How AI Will Reshape Medical Research and Healthcare Delivery"

Becker’s Healthcare Podcast — February 7, 2026
Guest: Dr. Giovanni Piedimonte, Professor, Tulane University
Host: Chris Sosa

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Episode Overview

This episode dives deep into how artificial intelligence (AI)—especially agentic and generative AI—will transform the healthcare industry, particularly in medical research and healthcare delivery. Dr. Giovanni Piedimonte, an experienced physician-scientist and AI task force chair at Tulane University, shares insights on the accelerating changes AI will bring, its risks, the challenges of workforce disruptions, and what the future could look like as healthcare increasingly partners with machines.

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Key Discussion Points & Insights

Dr. Piedimonte’s Background and AI Involvement

• Career Overview ([01:18])
  • Over 30 years in respiratory medicine and research, with significant NIH funding.
  • Administrative experience as division chief, department chair, president at Cleveland Clinic Children’s Hospital, and VP for Research at Tulane.
  • Current sabbatical has allowed deeper exploration into AI, quantum computing, and advanced technology’s impact on healthcare.

Evolution and Findings of Tulane’s AI Task Force

• Task Force Collaboration ([03:15])
  • Engaged with interdisciplinary experts beyond healthcare.
  • Produced a blueprint outlining opportunities and risks of AI in research.
• Key Impacts of AI in Research
  • Predicted near-total automation of grant management and administrative tasks.
  • AI to reduce repetitive work, lower costs, and improve data verification, especially regarding plagiarism and data fabrication.
    • “Virtually every single component of what today is the administration, management of grants... is going to become virtually independent from human input.” ([03:40])
• AI in Data Analysis
  • Using AI to analyze epidemiology and population health data, surfacing insights undetectable by humans.
  • Potential for many experiments to be digitally simulated, greatly accelerating drug and treatment development.
• Predictions for New Technologies
  • Robotic surgery will make dramatic advances ([05:41]).
  • The professional landscape for doctors and lawyers will shift considerably—collaborating with, rather than just using, computers and robots ([06:30]).

Major Risks and Ethical Concerns of AI

• Categorized Risks ([07:20])
  • Intellectual property and confidentiality: Genomic and health data could be difficult to keep secure.
    • “These technologies are going to make almost impossible to keep data confidential, safe and so forth.” ([07:47])
  • Bias and inequality: Data sets may reinforce existing inequalities.
  • Cost and energy use: AI development is expensive and highly energy-intensive.
  • Ecosystem volatility: Tech cycles are accelerating from years to months, creating obsolescence and cost challenges.
  • Hallucinations and reliability: AI mistakes could have severe consequences, especially in critical applications.
    • “You put a lot of vital functions ... in the [hands] of artificial intelligence. When you have an hallucination that can cost a lot…in terms of human lives.” ([14:09])
• The Coming Wave: Agentic & Embodied AI
  • Agentic AI (autonomous systems) and embodied AI (robotics) will be far more disruptive than current generative AI, reducing human control over processes.
  • Dr. Piedimonte predicts 2026-2027 will be historic for AI’s maturation and impact ([13:57]).

Trust, “Skill Downregulation,” and Workforce Implications

• Trusting AI & Human Skill Loss ([16:33])
  • Dr. Piedimonte fears AI’s biggest risk is not mistakes, but humans losing core skills because machines do everything:
    • “I think that we risk to have generations of people who are going to forget how to read, how to think, ... to calculate, ... to strategize.” ([17:26])
• Job Displacement and Societal Disruption ([19:35])
  • AI will automate many repetitive and administrative healthcare tasks, eliminating jobs across all levels—including areas previously thought untouchable, like clinical procedures.
    • “It's going to kill a lot of jobs.” ([19:57])
  • There’s no practical way for organizations to resist these changes as AI brings dramatic cost and efficiency improvements.
  • Societal responses such as reduced work weeks and basic universal income are being discussed internationally to address unemployment.

Reskilling: Challenges and Realities

• Reskilling Older Workers ([27:57])
  • Plans to retrain entire segments of displaced workers are widely discussed but are often unrealistic for established professionals.
    • “It's not easy to get a 50 year old ... and basically convert [them] into a Google engineer.” ([28:09])
  • Large-scale transitions will be difficult for those used to older systems—or, as Dr. Piedimonte notes, even adapting to technologies like electronic medical records was a barrier for many.

The Human Element and Ethical Imperative

• Retaining Human Centrality ([29:36])
  • AI and digital tools should remain in service to human well-being—not the reverse.
    • “To put the humans at the service of the machines is going to be a major strategic error.” ([29:49])
  • The importance of keeping patients and staff central in healthcare decisions.

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Notable Quotes & Memorable Moments

• On AI’s Automation of Research Tasks:
  “I predict that virtually every single component of ... administration [and] management of grants ... is going to become virtually independent from human input.” — Dr. Piedimonte ([03:40])

• On Data Security:
  “These technologies are going to make almost impossible to keep data confidential, safe and so forth.” — Dr. Piedimonte ([07:47])

• On Inequality:
  “Some people see in AI a democratic force... that is not necessarily going to happen.” — Dr. Piedimonte ([08:14])

• On the Risks of accelerated AI adoption:
  “The more we rely on artificial intelligence, the more we are at risk of the so called hallucinations.” — Dr. Piedimonte ([13:42])

• On Human Skills Atrophying:
  “I think that we risk to have generations of people who are going to forget how to read, how to think... because all those things can be done very quickly and very easily by this tool.” — Dr. Piedimonte ([17:26])

• On Workforce Disruption:
  “There are very few things that robots, artificial intelligence are not going to be able to do… you project these trends forward... we have a significant problem.” — Dr. Piedimonte ([23:07])

• On the Importance of Keeping Humans Central:
  “We have to continue… to put human being at the center, because artificial intelligence…[is] going to be helpful and useful only for as much as gonna make people happier.” — Dr. Piedimonte ([29:38])

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Future Directions and Dr. Piedimonte’s Next Moves

• Dr. Piedimonte plans to continue clinical care and research, with particular interest in the interface between agentic AI, quantum computing, and hybrid cloud systems ([30:42]).
• Predicts the “real competition” will be around hybrid data clouds enabling AI collaboration—not just the AI algorithms themselves.
• Warns that healthcare and society must prepare for a “perfect storm” of unprecedented changes in culture, work, and organization as AI technologies achieve maturity and scale.

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Key Timestamps for Reference

• 01:18 — Dr. Piedimonte’s background and research focus
• 03:15—15:35 — Insights from Tulane’s AI task force (opportunities and risks)
• 16:33—19:30 — Trust in AI, hallucinations, and human skill loss
• 19:35—26:36 — Workforce disruption, job losses, and the impossibility of resisting AI’s adoption
• 27:07—29:57 — Reskilling, older workers, and keeping humans at the center of technology
• 30:42—32:55 — Dr. Piedimonte’s future research and predictions for AI’s next era

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Conclusion

This conversation with Dr. Giovanni Piedimonte offers an unvarnished, deeply informed look at how AI is both exciting and threatening for healthcare. The episode stands out for balancing optimism about AI’s potential in research and delivery with warnings about social, ethical, and human consequences. Listeners are left with a sense of urgency to look beyond the hype and ensure technology serves, rather than supplants, humanity.

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Transcript

[A]

Every year, Becker's annual meeting brings healthcare leaders together to unpack the most pressing issues facing the industry. And every year, those conversations shift in profound and unexpected ways. This April, more than 3,500 healthcare executives will return to Chicago for Becker's 16th annual meeting. 795 elite speakers will offer new lessons, new case studies, and predictions about what comes next. Join us April 13th through the 16th. For the agenda and event details, visit Beckershospitalview.com and click on the events tab in the upper right.

[B]

Welcome to the Becker's Healthcare Podcast. I'm Chris Sosa, your host. I'm very happy today to be joined by Dr. Giovanni Piedmonte. He's a professor of pediatrics, biochemistry and molecular biology, and a researcher at Tulane University. He also trained his task force on the use of AI in research, which is our topic for our discussion today. Dr. Bielimonte, thank you for joining us today.

[C]

Thank you for inviting me, Chris. I really appreciate.

[B]

Wonderful. So, doctor, you've been researching a number of topics for better part of 30 years now. But for those in our audience who may not be intimately familiar with yourself and your organization, could you please introduce yourself and let us know a little bit about that?

[C]

Yeah. I'm a physician scientist, basically, and I've been practicing respiratory medicine clinically for about three decades. And about two decades I've been generously funded for my research in several areas of biology and respiratory diseases by nih. I added also a significant component to administrative duties over time, serving as division chief, first department chair for many years. Then I spent seven years at Cleveland Clinic as president of the Cleveland Clinic Children's Hospital. And most recently I joined Tulane, where for six years I served as vice president for research. Recently I stepped down for that and started my first sabbatical in my career, which I'm thoroughly enjoying. And the sabbatical has given me the opportunity to evolve new areas of research, but also to go deeper into my ongoing interest, as now several years old, for artificial intelligence, quantum computing, and advanced technologies applied to healthcare that, as you know, I'm sure everybody would agree on this, are gonna completely change the landscape of how we think and how we manage and how we healthcare for many, many years.

[B]

You can say that again. Dr. Bielen, there's so much to discuss. And as I mentioned, you chaired Tulane's task force on AI and research, so let's start there. So could you please take us through simply how the task force evolved, which I know could take a lot of time, but that's okay. We got time and just highlight the most significant findings from the last couple years.

[C]

Well, you know, was a great experience because I had the opportunity to interact with a lot of brilliant minds and most of them actually with the little to do with healthcare, including engineers, mathematicians and the like. And so open several different angles to read, you know, to read what the opportunities are and what the risks are for this new technology. And we wrote a blueprint that summarizes some of these concepts that emerged and to make a very short summary. There is no doubt that the specific area that we were interested in, which was research, is going to be impacted dramatically in any component by the introduction of artificial intelligence. Already is, I predict, and I'm a little bit radical in this, but I predict that virtually every single component of what today is the administration, management of grants, for example, is going to become virtually independent from human input. And the reason for this is that most are repetitive tasks that the computers will do, already do in some part with, in a fraction of the time, with minimal cost and with incredible reversibility. For example, the preparation of a grant, the assembly of a grant, the submission of a grant, the verification of a grant, Some other functions that already a lot of investigators are dealing with, but are going to become more and more stringent. For example, recently in the last years, we have seen a significant increase in the cases of plagiarism or publication of data that were not either accurate or completely fabricated. And the reason for that increase is quite simple. A lot of the fabrication of data could escape the human eye, but will not escape artificial intelligence and computer eye. And today there are plenty of softwares that allow people to actually verify whether something has been simply built on somebody's imagination or whether it's real data. So there are millions of different aspects that artificial intelligence another one. For example, I do epidemiologic research and population research. And the current study that I'm running is the first one in which we're going to use artificial intelligence algorithms to analyze the data. And already we're seeing a lot of driving phenomena that very unlikely. It's very unlikely we could picked if we were just using our brains. So in an extreme world, basically I would say that a lot of experiments may become obsolete because can be, can be reproduced in digital formats and therefore problems solved in a fraction of the time. And so all those things are great. And I expect a significant acceleration in the development, for example, of new drugs, of new therapeutics. I suspect that one of the areas of immediate progress and substantial progress is going to be robotic surgery, which Already is evolving and so forth is going to be a complete new world. A friend of mine some time ago said that to apply for med school or law school today is stupid because by the time you graduate, the computers are gonna and the robots are gonna do the work of doctors and lawyers is a little bit extreme. But the history of artificial intelligence has shown us that things that it sound stupid, sound impossible, become very possible and very almost simple within years. And so I think that definitely the new doctors and the new lawyers are gonna be collaborating primarily with computers and robots. And the scope and the applications of their work is going to be completely revolutionized. At the same time, it was an excellent opportunity to collaborating with my colleagues to assess what I think needs to be central in our analysis of artificial intelligence and new technologies. And that are the risks that are associated with this technology. And frankly, this is becoming a main focus on my interests. One of the things that we did was we tried to categorize the different types of risks that are associated with the introduction of, for example, Genai. And they specified that at the time we basically were discussing these matters, everybody was concentrating on gen AI. Today most people concentrate on genetic AI. These are totally different universe. And it's going to make most or all of our conclusions irrelevant. Because generative AI is not just an evolution of Genai is a change, a drastic complete change in the way we are going to interact with this technology. But at the time, talking about Genai, we identified the major types of risks as intellectual property risk, for example, and confidentiality breach. These technologies are going to make almost impossible to keep data confidential, safe and so forth. Not with the current technologies. That is going to create a lot of problem for the respect of intellectual property. It's going to create a lot of problem with the attempts to block individuals that are trying to get into critical databases. And that can become very problematic. Because I give you an example, we know very well that there are very large databases already in existence containing genomic data on individuals. And this new technology is going to make almost impossible to keep this safe unless we develop new, very complex strategies to secure those data. Another element is the biased and unbalanced coverage. It is true that some people see in AI a democratic force that is going to put everybody on the same level. That is not necessarily going to happen. There is a very big risk that the GI systems are trained on a large amount of data and the data is not heavily distributed, does not give a fair weight to all the components of society. So that gen AI can actually increase the risk of inequalities. Another element is the, the cost. Artificial intelligence costs a lot of money and it's going to break a lot of banks. It's going to be out of the reach of a lot of people. And one of the most critical area of cost is going to be energy. It's not by serendipity that China's run a very aggressive campaign for many years to increase their ability to have large sources of energy. Because this is an incredibly unprecedented requirement on the power needs that we had before AI. Another one is ecosystem volatility. So in other terms, we were used to change and upgrade systems every certain number of years. Pretty soon we are going to go into the weeks. A lot of technologies are evolving at a speed that is unprecedented and therefore that may create problems because you acquire a certain technology and becomes deja vu within months. That creates again a significant cost problem. And I left for last the one that I think is most concerning in terms that the more we rely on artificial intelligence, the more we are at risk of the so called hallucinations. Artificial intelligence is not perfect. I think it's going to become less and less imperfect over time. But you understand that you put a lot of vital functions of the society and even human beings in the ends of artificial intelligence. You know, when you have an hallucination that can cost a lot, not only in terms of money, but also in terms of human lives. So I think the, the best part of this experience was the understanding of the very delicate balance, very delicate balance existing between the advantages of this technology and the disadvantages of this technology. And again, all these considerations are going to go on a different scale. When agentic AI is going to become more prevalent. And that is going to be. Agentic AI is going to be the introduction and the needed bridge into embodied AI, which means the production robots, those two have a much more disruptive potential on our society and our technologies and our operations than Genai. Gen AI depends on us. Genai depends critically on the input of data on the programming. The human component is still dominant in Genai. In agentic AI, that flips. And that is where I think that is the reason I say that we have not seen not even the beginning of this revolution. When we are going to see the revolution, it's going to be when agentic AI is going to become more sophisticated, more prevalent. And I have reasons to believe that 2026 is going to be an historic year because the 2025 was kind of eventful, seemed like a breaking point, but I think was just an Introduction to what is going to happen in 2026 and 2027 when the technology that has been maturing over time is going to come to full fruition and at that point really the world is going to change in ways that are in great part unpredictable.

[B]

Thank you for laying all that out, Dr. Bielamonte. There's so much that's exciting and scary at the same time and really unavoidable in terms of how AI is going to affect all of us, including health systems and healthcare in general. I do want to ask, I'm curious, so given how much you've been embedded in AI in its research, what would you say your comfort level is with AI in terms of how well do you trust it? You mentioned hallucinations and what do you think has to happen for humans to trust it more than they do now? Does that make sense?

[C]

Yes, it does. It's a great question and I may surprise you, but hallucinations are not the part of AI that scares me the most. The part of AI that scares me the most is the risk of skill reprogramming and skill down regulation in humans. And I give you an example. I'm old enough that when I was in school I became very good at mathematics. I didn't like it at all, but I knew how to do basic calculations at least by hand with no support. And then we start getting the calculators and then the calculators get better and better. I don't know if today I I will be able to run square root analysis or even basic mathematical skills. Why? Because I don't need to. Now if you expand that to all the incredible potential of artificial intelligence and to the knowledge that I don't think there are that many students today that don't rely on artificial intelligence and Gen AI to do their work, I think that we risk to have generations of people who are going to forget how to read, how to think, they're going to forget how to calculate, they're going to forget how to strategize because all those things can be done very quickly and very easily by this tool. And so this is a risk. In fact, I'm in a very tough position because I'm really trying to understand all aspects relevant to my area of interest concerning AI Gen AI and the related technologies. But I try to use it the least I can if it makes any sense to you.

[B]

Oh, certainly, certainly.

[C]

Because I want my brain to go keep working and I don't want to be in a situation like the same way I lost my calculation Skill, I think, for example, I don't write. My pentmanship is not the same as it was. I don't need it. I am afraid even that my memory is going to be reduced because that's the nature of Darwinian systems and evolution. So in a world where all those things, all the things that we do, all the expression of our intelligence can be achieved in a much easier way, what is going to be left? That is an enormous concern that I have. Another concern is what this is going to do to our workforce. And there is a little bit of pride in me because at the Becker's conference a couple of years back when everybody was cheering and were partying and were so excited about all the potential of artificial intelligence, I said be careful because it's going to kill a lot of jobs. And I got criticized and several of my colleagues said, you're being over pessimistic. Well, it was very interesting yesterday I follow closely Davos meetings to here the CEO, the largest bank in the in the world I believe, or in the United States for sure, that is Jamie Demon, JP Morgan Chase. And Jamie basically said exactly the same things. Jamie in a nutshell said that if we do not are not very careful with the implementation, the launch, the use of artificial intelligence, particularly in the new generation or artificial intelligence algorithms, we are going to lose an enormous number of jobs. And we have to be proactive in thinking what these people are going to do. For example, in the world of healthcare, as I said before, the opportunities are endless. But when you look at any large healthcare system, there is a certain small number, relatively small number of doctors. All the rest are people that actually do highly repetitive tasks. Even the doctors do highly repetitive tasks. But sometimes, yeah, when you look at for example verification of insurance, check in of the patients, analysis and submission of the claims, all the work we already know can be done much, much faster. Easier buy system that don't get sick and they're very cheap. And another thing that Jamie said yesterday is that unfortunately this is not a process that can be modulated that much. Why? Because let's assume that you're the CEO of a large healthcare system and you decide for your principles that you don't want to get involved in AI and not in the implementation AI in your healthcare system. You're going to be killed on a financial basis because all your competitors are going to leap in front of you and achieve the same performance or much higher performance with much lower cost. So this is not going to stop. There is no possibility of stopping this. So I think One of the most challenging aspect of particular agentic AI is going to be before we launch on very large scale these technologies, we have to start thinking about what to do with people, all the people that are going to lose their jobs. One of the things I noticed there is a lot of attempts, I understand, to reduce the, how can I say, the panic. But I also think we need to be realistic. There are very few things that robots, artificial intelligence are not going to be able to do. One of the most shocking experiences as a physician was I'm a respirologist. For many years I thought that you always needed a physician to do a bronchoscopy, for example, any type of endoscopy. Today there are several systems that do bronchoscopies in a totally robotics way, requiring minimal additional effort from humans. And you know, it's just a matter of time that they're going to be completely independent. And there are already hospitals in Japan where the entire and also in China where the entire staff, nursing staff and physician staff is made of robots is just the beginning. When you project those trends and you realize that the technology is there, we better be at least be ready. Be ready, for example, to a world in which humans probably are not going to work five days, but only three days a week, if that. And one says, well great, I mean the more time for us, yes, but then we have to find the way to pay these people. And already in Europe there are a lot of, there's a lot of discussion about providing basic salaries, you know, from the state. In France, for example, they have a project like that because they already know that a lot of people are not going to have a job. So. And you cannot have the majority of the population without a job because they get very angry. And that is the reason of the revolutions around that occurred around the first Industrial Revolution. But the first Industrial revolution was nothing in comparison to what we are walking to. There were now machines that were able to do the work of hundreds of people. Now we have computers that are going to be able to do the work of tens of thousands of hundreds of thousands of people. And you already see several companies that are laying off big segments of their workforce. They are doing it gradually, but again, you just project this trend forward, realize the speed at which artificial intelligence is growing. When you see the difference between the first version of ChatGPT and the current version of ChatGPT are two completely different worlds, then you realize that we have a significant problem. And I feel a little bit vindicated in a way that the CEO of the largest bank in the United States. Yes, they said exactly the same things and what they did was be careful. We need to time this process otherwise we're going to have a big, big, significant social problem in our hands which is going to be very dangerous from a political level and on a social level.

[B]

Dr. That's all just fascinating. I mean I especially key in on the part where so much of it comes down to how much are we willing to give up in terms of thinking and strategy. Right. It's certainly the human element is very important now and we, to put it out there. I don't expect any of us to have an answer to this question this moment but we have to decide how much of it is worth it. Right. So it's just fascinating and scary and it's, it's again still exciting in a lot of ways.

[C]

But don't, don't forget the element of greed though.

[B]

I wouldn't, it's impossible because again artificial.

[C]

Intelligence is going to have major financial implications. So the risk, which is what Jamie Demon said. Yes, the risk is that basically people go looking, go forward, they're looking exclusively at the bottom line and that is going to be devastating. And then it basically ended with a word of hope saying that humans are still going to be relevant and important. There is no doubt about that. But how many humans are going to be relevant? And he talked also about reskilling.

[B]

Yeah.

[C]

And Chris, I'm afraid that they are taking the issue of reskilling a little bit too lightly because it's not easy to get a 50 year old that has done a certain job all his life or all her life and basically convert it into a Google engineer. There is a certain limit, I mean for the new generations maybe, but what are you going to do with all those people that I don't think I remember One thing that you know, I, I found very interesting. I, I was at the Cleveland Clinic. I participated to the launch of an upgrade of epic. I remember distinctly that a lot of the older physicians just quit because they didn't want to, to deal with the, you know, they were very comfortable with paper charts. Obviously we know that electronic medical record systems are much more efficient, have enormous advantages. But I'm old enough to remember when we didn't have that a lot of people spend most of their career. It was absolutely a cultural shock when trained medical systems were introduced. Among. I think there were a lot of problems when the first ems were implemented. So we have to continue, I think at least make every attempt to put human being at the center, because artificial intelligence, Gen AI and all the derivatives are going to be helpful and useful only for as much as gonna make people happier. And so to put the humans at the service of the machines is going to be a major strategic error.

[B]

That's well said, Dr. Piedmonte. And certainly as it relates to healthcare, you speak to any healthcare leader and they always say that the patients and their staff is front center. And we have every reason to believe that's true. Right. I believe that when they tell me that they wouldn't be in this, this business, this area, this sector otherwise. Right. So that is encouraging, certainly. Lastly, Doctor, I simply want to ask you, you are on sabbatical now, as you mentioned. Well deserved, clearly. But what do you think is next for you? I mean, you have plenty to draw on. So what do you look forward to doing in the next year, five years, whatever time span you see appropriate?

[C]

Well, if I don't retire, which is a possibility, I definitely want to continue my research. I definitely want to continue to do what I've done all my life, which is taking care of patients, which I still enjoy for as long as the robots are going to allow me to. But in terms of this particular field of interest, I am particularly excited about how these technologies are going to talk to each other, how they're going to interact, and particularly at the crossroads between artificial intelligence, particularly agentic AI, quantum computing, that is going to change dramatically. The speed of calculation, therefore, is going to increase enormously, the ability of artificial intelligence to function, and hybrid clouds that basically are going to allow these technologies to talk to each other. And as you know, a lot of hybrid clouds are. So that's where the competition is, in my opinion, is going to be not that much on the quantum side, not that much on the agentic AI, but to have the clouds where most of the data are going to be stored, or all of the data, and they're going to be allowing this cross talking. That is where I think the competition is going to be and that's where we are going to see the most extraordinary manifestation of this technological progress. Again, a lot of excitement, but also the. I think we have to be realistic when this perfect storm is going to hit. I hope that we are prepared because it's not going to be the same world, it's not going to be the same society, it's not going to be the same organization, it's not going to be the same culture, it's not going to be the same way of doing things.

[B]

I hope the very same. Doctor, thank you so much for bringing all your. Your decades worth of knowledge and expertise and insight on AI to our Becker's audience today. As I mentioned before, we love seeing you at conferences. I'm sure we will again. Yeah. Enjoy your sabbatical and thank you again.

[C]

And until next time, thank you very much, Chris.