Mike Peresie Of Mosaic Clinical Technologies On How Artificial Intelligence Can Solve Business Problems
An Interview With Chad Silverstein
“AI is not an answer, it is a tool you can use to help solve problems.”
As a part of this series, we had the pleasure to interview Mike Peresie.
Mike Peresie is the president of Mosaic Clinical Technologies, the technology and AI services division of Radiology Partners. Mike oversees the MosaicOS platform development, product strategy, operations, customer success, regulatory, AI innovation, marketing, go-to-market and strategic growth across Mosaic’s suite of solutions. He brings to Mosaic two decades of experience leading high-growth innovation portfolios and scaling software, network and data businesses.
Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path in AI?
I started my healthcare career in consulting and have worked for health systems, payers, pharmacy benefit managers, and pharmacies — a representative cross section in healthcare. These roles really helped me understand how the system operates and how the fragmentation challenges impact healthcare providers and most importantly patients. As my career evolved, I progressed to leading software businesses that were designed to solve some of those challenges, and AI became an increasingly important tool for software organizations trying to solve fundamental challenges in healthcare.
So, for me, I really started to lean into AI when I saw the potential it had to bridge some of the tremendously difficult and vexing challenges in healthcare — from increasing the efficiency of the system and care giver satisfaction to improving the outcomes we deliver for patients.
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
When generative AI really started taking off in terms of the capabilities of the technology, I quickly learned that it’s super easy to create a compelling “demo.”
But when the demo ends, “real software not available” was way too common. The software didn’t work in real life. An interesting insight was when Gen AI first broke, I knew it was going to change everything, but what I learned was that some companies were out selling it well before their capabilities were ready for prime time.
It’s super easy to pull together a demo that showcases a concept for a generative AI based solution. It’s extremely difficult — especially in the complex and highly regulated healthcare environment — to make that application work and deliver a targeted outcome.
You are a successful leader in the AI space. Which three character traits do you think were most instrumental to your success?
First, curiosity. Technology is evolving so fast that you must be interested in learning about it and how it’s being deployed across various industries. You must stay up to speed on how the capabilities are evolving, how new approaches are being deployed, and how you can potentially leverage AI, not just in your products, but across your business operations.
Second, problem solving. AI is not an answer, it is a tool you can use to help solve problems. I am focused on the problems my customers are trying to solve, and then testing and experimenting with AI as a tool help them achieve the outcomes they are targeting.
With AI, you can iterate and get yourself to a place where you start to find a lot of value. And you can’t be afraid of failing. You have to keep at it and continuously try to improve and solve problems better.
Third, a trait of the best companies in the world is customer centricity. I encourage leaders to think deeply about their customers — understanding their needs, differentiators, strategy, and workflow. A big mistake that happens when trying to deploy AI is not integrating it into the workflow of the organization. To make AI usable, it must fit within the way the user works. And if you don’t design the AI in a customer-centric manner, and that involves empathy and understanding, you will miss what your customer wants to accomplish, and you will fail. If it doesn’t fit, it doesn’t work, but instead it distracts, delays, and slows people down, rather than increasing capabilities and capacity.
Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?
Radiology is in a state of crisis. There is a shortage of radiologists globally. Imaging volumes are growing at a rate that is unsustainable, while the number of radiologists remains stubbornly flat. So, the result is that radiologists are getting burned out, and patients aren’t getting access to care. In fact, in some countries wait times are six to eight weeks to get your imaging study read. That’s a long time to wait, and it’s just not sustainable.
So, the way we’re deploying AI at Radiology Partners and Mosaic Clinical Technologies is across the radiologists’ and practices’ entire workflow. It starts with optimizing scheduling and using AI to help make sure we have the correct number of radiologists on shift for the specific windows when demand is high or low. It is about using AI to assign exams off the work list to a radiologist, get it to the best qualified radiologist, or who is on shift so an emergency order can be turned around quickly. We are also developing AI that can look at the actual image to surface findings that the radiologist might otherwise not identify, and also pinpoint where a finding is on the scan so the rad can verify accuracy. We’re using AI models to allow the radiologist to just speak in natural language, edit a report, and take all those findings that were documented to automatically generate the report. So, truly looking at every stage of the radiologist’s workflow and thinking about how AI can help streamline, enhance clinical capacity, and improve the quality and satisfaction for that radiologist. That is how we are using AI today, and it has been transformational. We’ve seen in some of our rad users that have adopted our platform early on, as much as 50 percent or more clinical capacity improvement, which is remarkable in an industry that is as capacity constrained as radiology.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
One of the biggest misconceptions that you can run across is that AI must be 100 percent accurate to be usable. The reality is that, especially with large language models and Gen AI, the technology isn’t 100 percent accurate. It’s occasionally going to hallucinate. It’s occasionally going to put something in the wrong spot. So, in many instances, especially in a clinical setting, we must have a highly skilled human working alongside the AI.
Another example of where AI is additive to humans is in coding. You can write software code with AI and in the first pass, it may only be 80 percent accurate, but you have a trained coder who can edit AI’s first software draft and get to the final code significantly faster than if they had to write the entire program themselves.
So, I think those who are seeing huge productivity and quality improvements with AI adoption are organizations that are leaning into this “first draft concept” where you can leverage the AI to get it to 90–95 percent accurate. And, it’s my job as the human worker who’s interacting with the technology, to get it 100 percent. The reality is that with AI, I can accomplish my task faster, easier and more accurately when I take the technology’s output and get it to a finished product.
So, it is a misconception that AI works only when it is completely accurate. Rather, AI can be super helpful if it’s only 90 percent accurate and the human can take AI’s first draft and make it 100 percent accurate.
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
What we’ve discovered in radiology is that the AI is very accurate. But when you put AI and the radiologist together, the quality level increases significantly. It’s logical because the AI isn’t perfect and the human isn’t either, but together they catch each other’s mistakes, and the resulting output is better. In clinical cases, when there is a patient involved, the clinician must be in the loop. Based on what we’ve learned in radiology — that you must have that human-AI interaction to make the AI better — I think the most significant way AI can positively impact businesses today is with significant human interaction. This is why the ability to integrate the AI seamlessly into the human workflow is so critical.
Ok, let’s dive deeper. Based on your experience and research, can you please share “3 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges. If possible, please share examples or stories for each.
1. Build, Modify, and Enhance Software Quickly
First, I think that our ability to build, modify, and enhance software quickly is extremely accelerated through AI. The tools that generate code are very fast and accurate. They allow you to modify your software so much quicker than without AI.
2. Information Security
Second, AI is extremely important in information security. Companies are successfully using AI to protect their data and information against the bad actors out there. Deploying AI in the information security space is — and will continue to be — incredibly important.
3. Quality and Productivity
Third, which is core to Mosaic Clinical Technologies, is quality and productivity. We have seen a tremendous improvement in addressing capacity and access to care issues, as well as identifying findings that may have been missed by a human, but that can be seen through AI. The amount of information that’s contained the image’s pixels is incredible, and we’re just finding that the AI can see things that even humans can’t see a lot of the time. So, it’s improving the quality of care. It’s resulting in better outcomes for patients, but it’s also improving the performance and satisfaction of the radiologists themselves.
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
One of the great things about AI is that it is available for all businesses — from Fortune 10 companies to startups. In fact, a lot of startups are building their entire business model around AI.
We’ve seen huge investment flowing into these startups, and I think that’s fantastic because it is driving a lot of innovation, especially in healthcare to solve complex problems. When I joined Mosaic Clinical Technologies, part of what I was looking for was this ability to build something up, but do so in the context of having a scaled clinical workforce and a large data set, because for AI solutions to be developed effectively, you have to have access to data, and you have to have access to a feedback loop. So, today we have radiologists providing us with feedback on where the AI was right and where it was wrong. From that feedback, we’re able to generate data to feed into our AI models and create a flywheel effect that I think every AI company needs to be successful.
So, if you’re a startup, what you need to do is build out your prototypes and get your early-adopter customers to give you access to users that will generate data you can use as feedback to improve your technology. This allows you to create your own flywheel where you’re getting feedback on your AI that you’re using to enhance the model continuously to solve a business problem. And that’s really the most important point to never lose sight of when improving your model: Is the AI helping solve the problem? If you focus on outcomes, you can drive through AI deployment. That’s the basic formula for success.
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
Just try it. I encourage all my teams to be using AI tools in their day-to-day work, because it will give you a sense of its capabilities. And I’m a big believer in thinking big, starting small, and moving fast. I encourage people to experiment with AI in low-risk environments and remember that as you’re experimenting with the technology, it’s evolving incredible fast.
The worst AI will be is today. It will only be better than it is today. I think approaching it with that mindset is crucial. As you think about deploying AI today, remember that in another six months, it’s only going to be better. It’s going to be able to do even more than it is doing today. It’s going to be even more accurate. I think that’s a good approach to take if your hesitant to dip your toe in the AI waters.
In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?
AI will be central to the business world over the next five to 10 years, and I think that winners and losers will be determined by how much an organization embraces it and weaves AI into their organization. It is quite apparent that we will see huge productivity and quality improvements in everything we do with AI. To continue to succeed, all businesses need to be at the forefront of experimenting with AI and learning how it can improve your business. For all of us in our careers, what will make us successful is our ability to leverage AI. Leveraging the technology will be a huge factor for how people shape their careers over the next 5–10 years.
How do you think the use of AI to solve business problems influences relationships with customers, employees and the broader community?
In the software industry the question I get asked all the time is “how are you using AI?” What I have noticed lately is that customers aren’t just buying your product for what it can do today, they’re making a commitment with you as a partner for the long term. Customers are investing in implementing your solution into their environment. They’re training their employees on how to use your product, and so while they want to know what you can do today, they’re really looking for confidence that you are going to lead the AI evolution in terms of embedding those capabilities into your offering for the long haul. The last thing a customer wants is to be stuck with a vendor that’s behind the curve on AI. I think customers are more attuned to what their vendor partners will be able to do in three years than even what their AI capabilities are today.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. 🙂
If I could start a movement, it would be to evolve global regulatory systems. Currently, we have systems that have worked well regulating healthcare technology products and “narrow AI models” to ensure safety and effectiveness. But as we’ve discussed, AI is changing the world. And as a result, we need to change how we think about evaluating AI solutions for deployment. Healthcare is one of the industries that needs the change AI is bringing. The faster we can start to bring those capabilities to bear on the challenges that exist in the healthcare system to drive better affordability, better physician and clinician experiences, and most importantly, better outcomes for patients, the better it will be for everyone. That’s why it is essential to have the right frameworks in place to make sure these solutions are safe — because AI deployment does carry some risk. So, getting AI tools to market with the full confidence they are safe and effective will require some different ways of thinking about regulatory processes.
How can our readers further follow you online?
You can follow Mosaic Clinical Technologies at https://www.linkedin.com/company/mosaic-clinical/
And you Radiology Partners at https://www.linkedin.com/company/radiology-partners/
You can follow me at https://www.linkedin.com/in/mike-peresie-1161072/
Thank you for sharing these insights!
About The Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
Mike Peresie Of Mosaic Clinical Technologies On How Artificial Intelligence Can Solve Business… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.