David Saltzman: 0:00

If the leap from horses to automobiles reshaped an entire century, what will AI do to our industry? We'll find out on this episode of Shift Shapers.

Announcer: 0:13

Change either energizes or paralyzes. The choice is yours. This is the Shift Shapers Podcast, bringing the employee benefits industry interviews with individuals and companies who are shaping the industry shifts. And now, here's your host, David Saltzman.

David Saltzman: 0:33

And to help us answer that question, we've invited my old friend Julian Lago, who is co-founder and CEO at Benepower. Hey Julian, how are you doing today?

Julian Lago: 0:42

Hey, David, great to be with you today.

David Saltzman: 0:44

My pleasure, my pleasure. So you often use that very same horse to automobile analogy. Why is that moment in history the best parallel for what's happening with AI today?

Julian Lago: 0:55

You know, David, it it's sometimes it's visual. I remember seeing uh an image years back of um, I think it was Avenue of the Americas in New York, and there were two vehicles and several horse and carriages there, and then they go less than five years forward, and it's the reverse. There's basically one to two horse and carriages, and they're all automobiles trying to figure out how to maneuver. And it had always struck me that in such a short window, technology, which was back in the day, in fact, it wasn't the auto industry, right? It was the horseless carriage industry somehow evolved and how many people got displaced and so many things had happened. So that that's been one of those things that are discussed at a lot of business schools, but the image of that was always uh interesting, that it was just a five-year window, and so dramatically the change occurred.

David Saltzman: 1:46

You know, I when you talk about change though, I mean, AI is not really real replacing humans, but it's kind of amplifying them, isn't it?

Julian Lago: 1:55

Yeah, it's an interesting dynamic. I talked to my my engineers, and we're all using AI, right? It's the it's the hot topic. But machine learning, um, I've got an engineer on our team that was with a pretty sizable organization for seven, eight years, and he laughs. He says, Yeah, everybody's talking AI like it's it's a new candy, new wrapper, it's a brand new name. But it's been around, machine learning has been around. I think we've been exploring and seeing it in movies and how it's going to take over, you know, and be careful for that robot that takes over the universe. The reality is that almost without exception, through the history of human mankind, technology makes um uh presence, whether it's the wheel, whether it's the you know, automobile industry, whether it's electricity turning on, in this case, AI, the next progression of the digital experience. And human in the loop is not something that's gonna go away. You need those components. So will there be reshifting? Will people be doing different types of jobs? Will some of the day-to-day functions or responsibilities they have go away? But that means it frees them up to do other things. And and that's the exciting part. You know, we basically uh do new things or have access to new information.

David Saltzman: 3:03

So let's let's focus this in on our our our industry and and daily, day-to-day benefits work. What would a true human AI partnership kind of look like?

Julian Lago: 3:14

Well, it it you know, if you think about the process of this, you know, we're we're in the sales business in some ways, where we're bringing a product to the marketplace, a better solution. There's shopping, there's quoting. Um I almost a best way to look at what the future is going to be is to look backwards, right? There's been uh you shared with me a great book one time. We talked about the the gentleman turning on the lanterns, right? And um in the streets. Think about what it was to order a simple proposal. In the back, I used to remember to fill out a proposal request form, you submit it, and it would take a day or two for that to just be back in your inbox to go present it to a client. So what was the expectation? You met with the client, you did a fact finder, you found out what their issues were, and you let them know three to four days, I will have some proposals back. So let's schedule something for next week. That process is happening in minutes today, right? Because we can go in and put in a request for proposal, the system might digest it, it identifies it, and literally within minutes you could be doing that real time. So that movement allowed us to do more. We can we can do multiple quotes within a day, whereas we were floating and we're moving physically to go deliver that presentation, etc. So our efficiencies increase. It's basically a scaling capability. We're able to scale our business faster and more efficiently. Move that into open enrollment, move that into customer service, which AI plays a significant role in. Move that to the education component. We're dealing with the complexity. The complexity of healthcare has not gone away because technology is here. So there's still a complexity of it. It's not a subject that we deal with every single day. When we get ill, it's it's it's first of all, it's important. It's something we need to resolve, and many times it's touching our family or our lifestyle. So it's a very escalated level of importance. And you want to bring all the solutions to the table. So, in that, um, that is where some of the technology, we're going to want to maximize it and be as efficient as we can. So, efficiency and those components play a big role. And I think every aspect of that, all the way through the renewal cycle and ongoing, but mostly that customer service experience and that education, I think AI is going to be a huge differentiator.

David Saltzman: 5:27

Well, I mean, we're not we're not only seeing it in those areas, we're also seeing it in things like compliance monitoring, um, broadly enrollment support. So if it's already reshaping core processes, like which of these areas do you think will be see the biggest transformation with AI in the next 12 to 24 months and why?

Julian Lago: 5:45

Well, I think if you think about the ability to take information and turn it into a digital component, um, that bit of information um at our fingertips becomes invaluable. For the most part, other than with our pains and aches and our ID card, we didn't walk into the doctor's office with much more information. Today we're empowered. We literally have all of our doctors, all of our networks. We can do a lot of due diligence early on. I hate to use the terminology, but you Google your uh your medical procedure, at least you have some idea what's gonna happen at that doctor's office. We can walk in much more empowered. That wasn't the case years back. At best, you talk to a family friend or someone of trust and you say, What's this experience gonna be like? And they gave you a vague indication of that. We're much more empowered. Data is also allowing us to take our previous illnesses, our previous comorbility issues. If you have borderline diabetes, that impacts what you're being treated for, what medications you're on. So information, in essence, is gonna be significantly easier to come by. Um, where to go, how to seek the top physicians, how to get the best level of care, most importantly at the lowest price or most cost-effective price.

David Saltzman: 7:00

Well, we've talked about advisors a little bit and employees a little bit. What's this look like at the employer side of the equation? If if you're an advisor and you're you're working with a a C-suite person or an HR person, what does this look like? How is AI helping them?

Julian Lago: 7:16

Uh I think it's the ultimate game changer. The average consultant we work with is looking to differentiate themselves at that employer level. Employers are looking at this. Um, over the past year, we've all heard that we're moving the conversation from the HR to the C-suite, right? Where it's a financial decision, there's much more information, and there's tools to do predictive analytics, and that's wonderful. But what if we can actually take a deeper dive into how their health plan and the way that it's been built is actually equaling or serving the population that it's intended to serve. Just because you build it this way, I can build a car with a convertible, but you know, if if if the person riding it wears a toupee, they're not going to open the convertible top, right? Because the hair's gonna blow off. I'm using the crazy example. But if if we're building plans in such a way that it doesn't accompany the population that is trying to serve, it's not a great solution. If you're putting in solutions that people don't know about and aren't aware how to use it, virtual health care, people still perceive that as telemedicine. And it's so evolved over just the last several years. Think about what COVID did with allowing physicians to practice medicine digitally. That's a transformation both from their billing to their methodology and the way they can communicate and all the HIPAA compliance that goes along with it. We have in some ways though that's an outcome of what we've experienced through COVID. So today it's no longer telemedicine, it's virtual care. That can extend to primary care, even specialists, certainly counseling and treatments, is you know, medical devices, home care, all of that can be touched now with the digital component.

David Saltzman: 9:03

Do you think that all that stuff that kind of got quote unquote forced on us during COVID has opened the door for a more ready acceptance of some of the things that are coming down the pike?

Julian Lago: 9:15

Yeah, I think in some ways, unfortunately, um we're creatures of habit. If it's not broken, we're not gonna go out of our way to fix it. If you talk to the average person pre-COVID, if they had a chance to speak a doctor face to face as it get to on the phone and a Zoom, they'd probably prefer it. Um, think of the days where we all had expense accounts, right? And everybody's, if they're gonna have a meeting, let's go make it a meeting, I'll fly into town, take you to dinner, and so on and so forth. Today, that becomes a 30-minute Zoom call. We're here doing a podcast, and I'm not sitting in front of you, we're using technology to do this. Um, much more efficient. Um, in fact, I can do three other things throughout the day. Whereas if I was traveling for that one-on-one meeting, physicians are in that medical practice is in the same way. Think about what we complain about having very limited time with our physicians. Physicians have to see more patients to receive similar reimbursements, and their time is limited. In this case, here we can be much more efficient because a lot of the data is there. Doctors are no longer worried about making sure they jot down all the notes. They sit there, turn on their phone, and the AI agent hears the entire conversation and is ready to create and fill in the ERM and also plan for your that x-ray, read it, reduce the medication, you know, lay out your surgery, and if it's done properly, all that comes in and becomes part of your day-to-day calendar and scheduling without a lot of thought on either part. That's where we're headed with some of this great technology.

David Saltzman: 10:41

So, you know, a lot of the physician relationships, vastly the majority of physician relationships now are corporate owned. They're owned by hospital systems and such. Do you see an accelerator being the hospital systems themselves bringing more AI to bear so that their doctors can see more patients in a more in a more time-effective way?

Julian Lago: 11:00

That's a really interesting question, David. It actually has two sides to that coin. I think we why were doctors being purchased by practices? Because they themselves, as a small regional practice, was not able to keep up with all the technology and all the changes that were happening. Um, if they got you know placed on an HMO, they got the volume of patients, but that also means they have to take care of billing. And think about about a third of their entire staff is is there just to collect the receivables. When they join an ASO model, they join a large practice, some of those efficiencies come into play. Today, physicians are migrating and reverting back to direct primary care, which allows them to move in a cash-paying model. Um, they're actually top surgeons like the Oklahoma Surgical Center. They're doing bundled surgical procedures on a direct cash, very transparent. So I'm seeing the ability for that doctor or that provider that still wants to have that direct patient interaction and practice and be in control of his practice, where technology is freeing them up. It's just the same idea that you know you can now run your own practice and do something for any type of business with technology as opposed to having you leverage people and power and position and power. So nowadays I think it's going to have a positive impact. We may see more and more individual physicians practicing because they don't have to move into those large practices to leverage technology or data or information.

David Saltzman: 12:32

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Julian Lago: 14:02

Yeah, I think fundamentally, if we understand a basic computer has a hard drive, Dave, and has storage of information, um AI is the ability for an agentic process for agents to go and do what's called RAG, they retrieve, augment, and bring that information out of the system. If we're thinking about an insurance, the the who, what, where is covered is written into an insurance policy. That's our governing document. And if you think about asking a question to just Google, which is like going to you know the library and opening up encyclopedia, it's gonna it's just gonna search out information. What AI is able to do is go in and retrieve specifically information as it pertains to a subject. And that agentic process allows multiple agents to work simultaneously. Let me let me go into a little deeper. Um, if I ask a simple question, um, what's my deductible or what's remaining of my deductible? There's several things. Number one, I've got to go to the plan document, find out what the original deductible was. You have a $2,500 deductible, $5,000 per family. It's covered at 80-20 from that. We all kind of follow that. It has a maximum lifetime X. But we would also need to send an agent in there to go read how much of my deductible have I accumulated, right? And we would need to go find out open EOBs that are pending against that. Um, so the question, the simple fundamental question, is perfect for the way AI is built, which is agentic. Multiple sources of information get brought back, and then through a rag system, it retrieves it, augments that, and responds back to the question at hand. And that process is a perfect process for the way AI functions. So that's why I believe we're seeing such a conversation and such um adoption, early adoption to AI, unlike other technologies, David, that um may have circled around the insurance space, but weren't adopted as as briefly. I think it's very logical for our process to go. I could talk about a claim judication process in the similar way. It has multiple moving parts. You have to pre-authorize, you have to identify and see, and then you pay the claim and adjudicate the claim and then communicate it back to the member. Um, even on pre-cert, the member has to ask a question and a go cert. So there's multiple ways for AI to really streamline that process. And at the enterprise level, I think that's the most exciting. You know, TPAs, insurance companies, and certainly brokers that are managing larger books of business. Um, this is not something they're doing tomorrow. This is something they did yesterday already and are actively putting in place today. So if you haven't done it, you're already almost behind the eight-ball.

David Saltzman: 16:43

Well, speaking of behind the eight-ball, I mean, there are there are models of AI that folks aren't even aware of. There's one that's called emotion AI. And it's it's really, to me, it's kind of one of the most fascinating parts. Is it true that it can even detect the tone or mood that you're in and then ask if you're okay?

Julian Lago: 16:59

Yeah, I mean, that it's amazing the amount. Again, remember all those little agents that I kind of talked about that are out there, they're listening and they're hearing, and um they're being they're programmed to understand human emotions. Um, they're programmed to understand the severity of your voice, the tone of your voice. Um, they're there to understand if you're struggling with a native language, if you have Spanish as your more preferred language, it will know intuitively to ask if you prefer to speak in another language. Um, so those components are all there. Um, and a lot happens behind the scene, David. This is where all the programming is occurring for these types of agents and and bringing them together. One that it listens properly to what is the true question, where does it have to go seek the information, and and and really in an augmentation, how do we address the communication at hand with this person? Um, are we speaking to that person, you know, in the right tone, in the right methodology? So all that is is part of what large language capability does. Unlike a chat, right? A chat, you just plug it in, you type it in, and it's going to respond. It's not listening to the tone of your voice.

David Saltzman: 18:07

Is now you you talk about something called hyper-personalization. Is that kind of where that's going? You you mentioned when when I've heard you talk about it, you talk about it kind of as the holy grail. What does that look like when you combine natural language modeling and emotional intelligence?

Julian Lago: 18:21

Well, you get very, very close to a human interaction, right? Um, think about when we wrote a letter to someone and you put a big exclamation point, or you're on the phone and you pause and you let silence be part of that conversation. You can interpret two different methodology, two different messages there. And um, you know, think about how powerful dad was when he you asked him a question, he turned to you, he looked at you, but didn't say anything. Right? That that echoes. And AI has that capability to bring that type of personalization into conversations, empathy. You know, um sometimes it's it's bringing a sense of urgency to a situation. A mom who's on the phone driving home and and and can't find the ID card and she's on the way to a doctor's office, that's an emergency for her. She's gonna arrive at that emergency room, she wants her child seen, and she knows they're gonna ask her for the ID card. Doesn't seem like a 911 fire emergency, but in that person's case, so AI should respond adequately. Ma'am, focus on your driving. Let me go ahead and look inside your text. We'll be emailing you the ID card. It'll be there when you arrive at the doctor's office. Empathy, efficiency, capabilities that are there.

David Saltzman: 19:34

Now, every technology, it doesn't matter what it is, every and every technological leap comes with caveats. What do you see as the biggest risks or roadblocks, whether it's privacy, integration, et cetera, that organizations should be preparing for now?

Julian Lago: 19:48

Well, the interesting part is that legislatively we catch up to technology. We don't predict technology. HIPAA was written, you know, with a certain amount of you know, ideas of what it would play out. We're we're crossing into some of these spaces, David, that we just don't have. Um, you know, it's almost like a need for self-governing to some extent. And thank goodness that um, you know, we run through processes and procedures that allow us to make sure that we have the integrity of the individual medical records, all of their privacy. Um, so that there's a cautionary tale that's there because it's it's happened in the past. Um, we really don't know to what extent the legislative component has to adapt or the technology has to adapt. But I know that there's states like California. Um, I was just on a conference and they're already looking at legislating some of the things that AI could basically um hallucinate or impersonate a physician and give information that is required by law to be a licensed practitioner. Can it be done? Yes. Should it be done? No, it's illegal, right? You don't want to impersonate a doctor. So California's already started to address, so we're gonna start seeing some of these functions happen throughout AI and throughout our industry. Um and we just have to be aware of what those what those components are.

David Saltzman: 21:16

I know one of the analogies that you talk about a lot when you talk to groups is about the buggy whip makers makers who adapted versus those who disappeared. What does that adapting look like for benefits brokers, for carriers, and for HR teams in this new AI era?

Julian Lago: 21:31

Dave, I I I love that analogy for so many reasons because there's, you know, let's play it out very, very quickly. We have limited time, but it's important that we kind of play it out. You know, all of a sudden I wake up one morning and all my orders for buggy whips are gone, right? And my little shop in town, there's another guy across town. He got the same request that hey, buggy whips are slowing down, our current inventory is probably keep up, so sorry to have you. One person takes it and he says, Oh my God, I'm being displaced, I'm out of business, you know, time to move out of state, whatever, whatever the laws are, or whatever the situation. The other guy looks at it, hmm, you know what? Um, what have I been doing for several years? I've been manipulating leather and building buggy whips. And I was visiting the shop um and they've got leather steering wheels that are there, and I see the seats are going to be made out of cloth, but they would look better in leather. And uh, let me put in a bid and see if I can become the new leather, you know, the upgrader for these Model T Fords. Somewhere along the line that happened, and someone adopted, and guess what? That buggy whip manufacturer had multiple locations, is now doing for all the vehicles that are coming off the assembly line. Their job quadrupled uh 10x and they became extremely successful in that environment. Did they change fundamentally what they were doing? To some extent, but they were still in the box of they were manipulating leather. Um the other guy said, Oh, completely out of business. So a lot has to do with how you perceive this. And if we're confident in what we deliver and we're confident in our capabilities, one of the things we should never have is the ability to stop learning and adapting. And if that's missing in an entrepreneur, you're missing one of the key components of being an entrepreneur. So in my mind, that's an exciting dynamic. You look at it with how do we adapt? How do we bring? And you're not going to have all the answers.

David Saltzman: 23:15

Well, you can't have all the answers because all the technology isn't all rolled out yet. And even the new technology is begatting, to use a biblical term, even newer technology. And so that will continue to evolve. But, you know, I think a lot of brokers are afraid of these changes. But boy, there you'd be hard-pressed to find an uh an occupation that has done more adapting in the last 20 years than brokers. I mean, you and I have been at this a long time. I remember when we had indemnity policies where there was a schedule of what would be paid for each procedure, period, end of story, that was it. And we've gone through changes after changes after changes. So I think most brokers will be in a good place. They just need somebody to kind of help explain it to them and a partner to work with them. That's kind of what you guys are doing, isn't it?

Julian Lago: 24:00

Yeah, I mean, that's exactly it, David. We haven't lost our core competency. We understand how important the role of a consultant and broker is. Um, and they're there as a consultant for these employers. Interpreting how technology is going to make that, you know, providing healthcare for their employees more efficiently and giving better results is is just part of this. There's there's a tremendous number of solutions that are coming into our marketplace. We could break it down, the old doctor-hospital medicine, but in pharmaceutical, there's a tremendous amount of new tools that can function whether you're a diabetic or not. Introducing technology so we can communicate that to Joe the forklift operator in the warehouse and making sure that he can interpret it and use it, that's a key component of the broker's role. And they do that really, really well. So we're providing all the tools and all the technology so they don't have to be the one building it, but they will be empowered to say, we've got it in our, we've got it, you know, in our in our uh, you know, our list of products and services, and we can introduce technology there.

David Saltzman: 24:58

So that's a great place to end our conversation for today. Julian Lago, co-founder and CEO at Benepower. Julian, thanks for a fascinating conversation.

Julian Lago: 25:07

Always, always great to catch up, David. Thank you.

Announcer: 25:11

The Shift Shapers Podcast is a production of Shift Shaper strategies and may not be reproduced or quoted in whole or in part without our express written permission. Copyright 2020, all rights reserved.