Building Human Confidence in the Age of AI

Leslie (Moderator): When we talk about AI, there's such a different perspective on it—you're either using it all the time, or you might be on the exact opposite end of the spectrum and you're like, "Oh, gosh. No. I don't wanna do this." And so recently, I was at a dinner with some other policy folks, and the conversation starter was—and I'm gonna pose it to my fellow panelists—is: what is your favorite use in your daily life of an AI solution? So, giving you my example of what I said to them: I don't know how many of you have young children or grandchildren.

Leslie (Moderator): As Janine shared, I have an eight-year-old, and Elf on the Shelf, of course, dominates December for a lot of families. And so I turned to ChatGPT to help me outline what—Pepe is our elf—what kind of silly things Pepe would be up to during the month of December, and the daily notes that she would leave for our family. So that was my much-appreciated application, because my creative juices were really struggling once we got into those later days in December. So, JT, tell us: what's your favorite use?

JT (Panelist): So I am going to be doing a kayaking trip around Lake Tahoe. So one of my uses is more about my workout—the training schedule, the weather, the equipment, and all that good stuff. So it has put everything together for me. I have videos for different techniques and all that kind of stuff. So it's more at a personal level, but it's gonna help me with, hopefully, achieving a goal.
Leslie (Moderator): Awesome. Doctor G?

Dr. G (Panelist): Well, first of all, Leslie, thank you so much for having me. How is everyone feeling at Voyages 2026 after the ice cream? I know that was Glenn. I know he picked vanilla. I'm really sad that we missed the ice cream.

Dr. G (Panelist): I hope that part of the panel is that we get to get some after. Is there any left, Glenn? Is there any left?

Glenn (Off-mic/Audience): Melted by the time we get out of this one.

Dr. G (Panelist): All right. Well, speaking of food, I have to say that I use AI all the time as my personal assistant, my personal chef, and also sometimes to be the bad cop in parenting—to say no to my teenage daughter who often wants to do things that are ridiculous. And so I have her just—you know—and my AI technology knows me. So I say, "Sonia, why don't you put that in and see what they think about you going unchaperoned where there is all kinds of public folks and alcohol?" And, you know, she says, "They said no."

Dr. G (Panelist): I said, "You know, that made it easy for me." Right?

Leslie (Moderator): I love that. And so, to kind of get us kicked off on some of the other content we wanna cover today—and I'll use another—I'm sorry, I tell a lot of stories, and they generally involve my son. Happy to show you pictures. He just turned eight on Saturday.

Leslie (Moderator): But as—you know—I'm in DC, and we had the snow that has caused woes for many of us. So my mother-in-law finally made it in from Florida, and she said, "Oh, Leslie, you know, I'd love to hear what you're speaking on at this conference." And I said, "Oh, I'm moderating a session on applications for AI and HR and benefits." And my son, who is actually not very excitable, just, like, stopped and went, "Mom, you know about AI?" And I was like, "Yeah."

Leslie (Moderator): Enough. He's like, "Do you know, like, AI intelligence? Are you gonna, like, talk about models? Do you, like, make AI?" And I was like, "I'm not prepared for any of these questions that you've just asked me, but I'm really excited that you're excited about it."

Leslie (Moderator): And I think that speaks to kind of the environment that we find ourselves in. And so I'm gonna start with Doctor G. As Janine outlined, she's an expert in building trust—especially in the healthcare space and as it intersects with technology. And so, you know, as evidenced by my eight-year-old, there's a lot of excitement in our industry, in our community, in our organizations, in our households for AI. But with AI excitement comes some level of anxiety. So as we're thinking about bringing AI to our organizations and more broadly, how would you advise us to think about how we build trust as we introduce more AI into our organizations?

Leslie (Moderator): And then what are some of those tells that you would recommend we look for to indicate that it is trusted—we've reached that point?

Dr. G (Panelist): Sure. So I think it was Spider-Man that said it best, right? "With great power comes great responsibility." And in that spirit, the question we really need to be asking ourselves about AI—and everything we really do in healthcare—is not about our technology strategy, not "what is our AI strategy," but, in fact: what is our trust strategy, right?

Dr. G (Panelist): How are we winning the trust of our employees? How are we winning and gaining trust in institutions that deliver health and drive outcomes? And I like to break these down as the three A's. I like acronyms. I find them much easier to remember.

Dr. G (Panelist): So, number one: is the technology accurate, right? Does it back up into evidence-based medicine? Is there a medical board involved in the information that you are producing and making available to your employees? So that's the first A.

Dr. G (Panelist): Second A: is there accountability, right? At the end of the day, this is one tool in a bigger system, in a bigger function of the HR division. And so who's accountable when something goes wrong? Who's accountable when things are not accurate? Right? Who's accountable when an employee has a bad experience? So that's very important—having the human in the loop and employees knowing that someone is accountable, not the technology acting autonomously and alone.

Dr. G (Panelist): And then, lastly—probably my favorite—is actionability, right? How is this driving an outcome? How is it driving an action for an employee to make good healthcare decisions? Information's great, but how are we actually getting to next best step and next best action? Are we making an appointment? Are we getting that mammogram? What is really the outcome that we're trying to drive?

Dr. G (Panelist): And when you look at metrics of how you're measuring that trust, I think it's all the things you're all already looking at, which is conversion rates. Are employees staying with it? Are they dissatisfied? What's their feedback? Right? These are metrics you're already measuring. So I know we get really, really caught up in the AI piece, but I think we have to zoom out and say: what are our trust metrics and what is our trust strategy—and then how is AI one tool that gets us to a successful trust strategy?

Leslie (Moderator): And I'm gonna stick with you, Doctor G, because as we're talking about healthcare is changing—that's really been the crux of our conversation today—and in this increasingly digital world where healthcare may be coming in a lot of different forms, you know, potentially trusted, potentially easily accessible but maybe not so trusted. So how is misinformation changing how we think about human trust? And for our HR and benefits leaders who are here with us, what should they understand about that dynamic of where that trust intersection comes into play?

Dr. G (Panelist): Sure. So I think everyone in this room appreciates and understands that we're living in an era where mis- and disinformation are traveling faster and faster than the facts, right? And it's becoming really hard to tell fact from fiction. And the reality is, because of AI, this information is not just traveling fast, but it's really believable, right?

Dr. G (Panelist): And there's a high level of confidence with a lot of these technologies that make you think it's accurate just because it sounds good, right? And I call this "stranger danger" when I'm talking to my fourteen-year-old daughter, right? Just because he sounds like he knows what he's talking about doesn't mean that he does, right?

Dr. G (Panelist): And so we have to remember that with our employees who are very desperate for information, but actually very thirsty for trusted information, right? If everyone's an expert, no one's an expert. And so that accuracy piece is really critical in educating our employees to understand that confidence doesn't necessarily mean accuracy. So how are you looking at sources? Where are you looking for guidelines? Where is there a medical expert in the loop to help you make your own personalized decisions? Because whether it's Google, whether it's AI, generalized opinions don't always work when we talk about individualized, personalized medicine.

Leslie (Moderator): Thank you. And so, thank you for setting the stage of kind of where the intersection of health information, AI, trust, and transparency kind of intersect. And so I'm gonna shift to JT. But for those of you that may not know, last year Transcarent released the results of a survey on AI sentiments from more than thirteen hundred senior HR leaders at U.S. self-insured employers—and the findings, I don't think, would be surprising. If I asked for a show of hands, I'm just gonna kind of assume you're all gonna agree, but I think, you know, ninety-eight percent of respondents were familiar with AI. I think more than ninety percent were excited about the possibilities that AI brings. And seventy-seven percent of folks said we're already applying various productivity tools like ChatGPT to our daily lives.

Leslie (Moderator): So I think that's probably very accurate. You all can disagree with me—throw some tomatoes or something—if that's wrong. But then I think as we look at what does the future hold, there were also findings of the report that about fifty-seven percent of folks lacked internal expertise, or sixty percent were worried about data privacy and security. Forty percent were worried about budget and resource constraints.

Leslie (Moderator): With the positive—kind of as we look to the next chapter—there's an awareness of: we have to go in eyes wide open. And even just this week—in case folks either caught it or didn't—there was a piece that caught my eye in Employee Benefits News that said that AI is forcing benefits teams to be more technical and more analytical, and they're really being looked at as a source of truth and expertise for their organizations—and kind of being the nexus to bring organizations together on their AI strategy. So, JT, with kind of that level-setting of what we found based off of our own data and what we're seeing in the trade press: from an HR lens, what do CHROs and benefit leaders need to know in terms of building confidence in AI within their organizations?
JT (Panelist): Okay. So that's a lot there. In order to build trust—you have your trust models—and I have the four C's of trust, which is communication, confidence, consistency, and compassion. So that's something that, as CHROs, we need to think about when we're deploying any change in the organization.

JT (Panelist): When it comes to giving confidence around AI, it's moving so fast. We're all learning. We're all in this learning curve right now. We don't have to be experts—especially for the CHRO. We have to, though, be able to mobilize our workforce to what the business dynamics are of the time.

JT (Panelist): So when COVID happened, I became the chief medical officer. I had to quickly mobilize the workforce around that. And not officially—just meaning that I had to mobilize the workforce around COVID. Then I had to become the chief remote office and return-to-office—or hybrid office—officer. And now you're the chief AI officer. So we're early adopters of AI in some ways.

JT (Panelist): We have to understand what this is all about—not to be the expert around AI, but how do we mobilize our workforce to adopt, to adjust, to incorporate into how we operate, how we think—our mindset. So building confidence in AI: one, there is building confidence in yourself; then there's building confidence in your function; and then there's building confidence for your workforce.

JT (Panelist): For myself—for any CHRO—we're already out there. We're probably out in the forefront of just trying to understand it all. But take the time, talk to your peers. We're all comparing notes and getting little nuggets from each other. Conferences like this are extremely helpful.

JT (Panelist): When it comes to building trust and confidence with your employees: it is carving out the time for them to feel safe through this adoption. Forcing adoption is something that—I tried it at one company because that's what we thought we needed to do—and that just failed miserably. So you have to create a safe space.
JT (Panelist): There is a lot of AI that is already infused in a lot of the software that you already have in place. And so how do you embrace that and leverage that a bit more, and dip your toes into things that have high friction but are easy to solve? I know that we just recently adopted Glean to be deployed into our organization. We did a pilot. And it was the seeing the pain go away for a whole bunch of people—it became viral of, "We got to do this." "Oh, my God. Everybody's sharing, and this is great." And all of a sudden, the capacity, the energy, the volume—and it was all organic. It happened organically versus us pushing that mandate down.

JT (Panelist): And then I would say that building that confidence in your function: so for my team, it is—it's a seed and grow. Again, carving out the time. It is knowing what tools we have that are at our disposal within the software that we already have. We have tons of BI tools. We have tons of software everywhere that are infused—quote-unquote—with AI.

JT (Panelist): But there is the ability of saying, "Okay, let's deal with workflows. Let's deal with these little small problems. Let's test the things first before we just go out with a big bang and then realize, oops"—you know—and this impacts employees. So we want to make sure that we're doing the testing right.

JT (Panelist): So those are some of the things that we're doing that I would give advice on as to how do you build trust and confidence. And it's okay to make mistakes; it's okay to own that—"Oops, we've learned something." And as Glenn said when he started this: we know that we're gonna learn and we're gonna make some mistakes along the way. It's how you react to it that matters most. And that's where that consistency, that communication, and then that compassion comes into play—as to being forgiving around the learning experience that everyone is going through.

Leslie (Moderator): I can speak firsthand, having seen the excitement around Glean. So there definitely is that immediate payback and level of fulfillment when things work. So, you know, HR has to collaborate with so many—you literally touch every facet of the organization. And as we think about AI and the rollout of AI tools across the organization, you know, you've got HR; you've got legal and compliance; there's security; there's IT; there's—I mean, Glean was great for commercial purposes, right? So far-ranging team that you have to put together. So who's accountable for what? How have you built those partnerships in your various roles as you've rolled out AI and built AI tools?

JT (Panelist): So, in IT, that is like your biggest partner. Your CIO is your biggest partner relative to just understanding all the different applications and the language models that they're gonna be selecting; the security; the data privacy—that's also with our security or IT team sometimes. Those are extremely important.
JT (Panelist): In fact, I just recently hired for my head of operations—HR operations—a CIO, because that's the direction it's going. And I need to have somebody who understands workflows, the tech stack; who is going to not create AI to adopt AI, but to solve our problems of workflows, problem resolutions, accuracy, timeliness, all that kind of stuff.

JT (Panelist): There is our chief legal officer for privacy and for regulation interpretations. There is our CFO for affording all of these things and also cost savings as well—like where can we get efficiencies from either reduction of all these systems that can be simplified, or as it relates to improving the productivity of our workforce and creating more capacity so that we can accelerate our performance.

JT (Panelist): There is—let's see who else is in there—there's IT, HR. Well, HR is responsible for the enablement piece, but I think where it really hits the road is the business leader. And the business leader being really clear as to: what are the outcomes they're expecting from the application of AI in their work—in their function. And that level of specificity is really important: that the business leader is saying, "I need these outcomes"—not about utilization rates or adoption rates, but like the real outcomes that they're expecting from their function.
JT (Panelist): So there's a whole bunch of us. And then there's also just a governance over all of this. We also have a committee that oversees a lot of these things as well.

Leslie (Moderator): Yes—our AIGC, which I have the pleasure of sitting on, and it's a really fun group, and we've been busy. And then, you know, you have some learnings—and I thought it was enlightening, as Janine mentioned, that you worked through the acquisition of a company that acquired eight—eleven—AI companies. So, AI, you are not a stranger. So as we're thinking about—based off of those learnings and what we've done at Transcarent and otherwise—what are some of the more common mistakes that hopefully we can all avoid when it comes to bringing AI to an organization?

JT (Panelist): Definitely do not force it. But you have to carve out the time to have the employees feel safe with it. There are different cohorts that are early adopters—kind of like the technology adoption life cycle, Geoffrey Moore, Crossing the Chasm—that you have to apply that to your workforce as well, and make sure that there's different cohorts that have different learning styles, different approaches.

JT (Panelist): Peers are the best way to get the virality and the comfort instead of it coming from HR. They'd rather get the learnings from peers.

JT (Panelist): I would say that the other thing, from the learning perspective, is: on the vendor side, a lot of vendors say there's AI in there—and really, really double-click and ask the right questions around what really is. You know, AI has been around for a while. What's making it more accessible right now is that there is the generative AI aspect of it that makes it more approachable, and the low-code or no-code that has made it more approachable for easier consumption.

JT (Panelist): And so just making sure that you've got good vendors and you understand your contracts as well, because there's a lot of AI usage—there's like a different model now than just SaaS. So those are some of the things that you can get "ahas" and caught up in that can impede successful adoption.

Leslie (Moderator): That's really helpful. So as we look to kind of bring together your two areas of expertise—so, Doctor G, back to you—you have been at the forefront of medical innovation and the digitization of healthcare. Are there lessons in kind of healthcare safety that our HR leaders might learn from, as healthcare has digitized, that might be applicable toward the application of AI to healthcare?

Dr. G (Panelist): You bet. Look, and I think the safety lessons are really that safety has to be foundational. It can't be an afterthought, right? Deploying technology is one thing, but deploying safe technology is what is gonna help you build trust with your employees.

Leslie (Moderator): So, you know, if you could give our audience and our colleagues kind of a "do not do this" list—I think, JT, you sort of touched on it—but maybe, Doctor G, over to you. So if there is a do-not-do as it relates to AI communication for adoption, what might be on that list?

Dr. G (Panelist): Sure. You know, I'm gonna answer that by telling you what you should do, right? So stick with the to-do list. And what's really important is not just when we deploy technologies, but how we communicate it, right? Communication is half the battle in building trust and deploying technology for utilization, adoption—all the things JT talked about.

Dr. G (Panelist): So, number one: communicating with purpose. What are you using AI for, right? What is the problem that your employees can expect that this will solve for them? So being really crisp on why—what is the purpose of the technology, right? To connect you to your benefits, to make sure you get an appointment, to help you save money—what is the outcome? Be very clear on the purpose. So again, these are my three P's. I'm big on acronyms, guys.

Dr. G (Panelist): So: purpose—first P. Second: protection, right? We're talking about healthcare. We're talking about medicine. We're talking about sensitive information. What protections are you communicating? I.e., is this HIPAA protected, right? Where is this information if patients are gonna offer information? How are you protecting them? How are you protecting their data—whether it's data that they're offering or data that they're using? So that's second P.

Dr. G (Panelist): Third one is permission. Maybe I wanna do it; maybe I don't. JT said it, right? You've been to this movie before. Some people are gonna be earlier adopters; some people are gonna wait and see. So am I opting in? Am I opting out? Make me feel that I know the purpose. Make me feel that you're protecting me. And then make me feel in control—that you got my permission to use this technology.

Dr. G (Panelist): Because I'll tell you as a doc, right—patients are not afraid of technology. They're not afraid of using new things. They want to know what it's gonna be used for and they want to know that they're not being surveilled, right? They want to know that you're not gonna use this information against them. And that goes back to what we talked about before, which is trust. So if you can communicate with the three P's—purpose, protection, and being really committed to permission and making consumers feel that they're in control—that's half of how you do this right.

Leslie (Moderator): I love that. And so I think, to round us out—and I think you both touched on this, but in case there's any finer points—I'll try to leave it a little bit open-ended. So, you know, AI is everywhere. It's in the workplace. It's at home. It's being applied to healthcare in a variety of ways. What are—kind of leave us with—how do we continue to keep the momentum? How do we continue to communicate with our colleagues, with our employees, without triggering fear? So I know when we were talking earlier, you were talking about: if I'm thinking about applying it to benefits, there are some things you consider—and then also as you're applying it kind of to everyday. So, I don't know, JT, if you want to start with any kind of final thoughts there.

JT (Panelist): Sure. So when it comes to benefits: there's our employees that are receiving benefits that have AI infused in its service. And so they're gonna wanna know—just as a consumer of healthcare or of the services that their employer is providing to them—"Is it safe?" What decision-making? Where is the decision-making happening? Who's owning that decision? When is there a human touch that's going to be part of this?

JT (Panelist): So just as a service organization, to our employees who are experiencing what they're expecting from their employer, those are things that we have to orchestrate and program properly and be thoughtful around—be consistent, and also compassionate—and add that human component in.

JT (Panelist): Then there is the employee who is using AI to be productive at work, or infusing AI into our product and our services—getting them excited, being able to learn, feeling safe around that technology—that we have to create that environment for. And it is a one-size-fits-one approach to this. Again, there are all different functions that adopt things in different ways and use the technology in different ways. And there are also just different generations represented that will consume it in different ways.

JT (Panelist): So we have to program our upskilling, reskilling, and infusion of this technology into their day-to-day work in the ways that can work for them. So those would be my two little takeaways. Doctor G?

Dr. G (Panelist): You know, I think the one thing we didn't talk about—which I think is really important to go home with—is transparency, right? And understanding that this is all new, right? Even for us. It's difficult to know who's really an expert when something is new. And so I think being really transparent about that.

Dr. G (Panelist): And like you felt during COVID—I felt like I became the head of HR. I remember knocking on HR's door and saying, "You know, we need to get telemedicine benefits because I'm telling everyone to stay home." So being really transparent—that's one of the things I learned during that crisis—was talking to employees and saying, "Look, it's a dynamic situation. I'm not gonna pretend to be a COVID expert, but today, this is what I know. This is what I think is the best judgment call, and tomorrow's another day," right?

Dr. G (Panelist): And so I think if you employ the same transparency in innovating, that's really critical—along with all the principles and acronyms we talked about, right? But you will be surprised what that does. It really disarms people, and it leaves an appetite and an ability to make mistakes when you say, "Our goal was this; this was our purpose. But then we did this, and then we learned this—and yeah, we kind of screwed it up—but we said that. Remember? We said that we didn't have this quite 100% baked, but that we were gonna try it out there to solve this problem."

Dr. G (Panelist): And I think any of us would be receptive if someone came to us with that mindset. So not pretending to have all the answers if you don't, right? Acknowledging what you don't know is, I think, half of the innovation battle with AI right now.

JT (Panelist): One other thing I would add is that I think, to eliminate some of the fear that employees have around AI: yes, they're experiencing—I know some of our employees are super excited about—"Oh my god, this is freeing up. I'm able to increase velocity. I'm able to spend more time thinking about the client versus thinking about all the transactions"—really to raise their gaze, because we've been on our phones and down and in and looking down and in around all of this transactional work.

JT (Panelist): It is going to help us to be able to automate, to be able to eliminate, reduce—whatever—all those transactional activities from our day-to-day and free us to be able to look up and out; to be able to become humble and human again and bring humanity back into the equation—even though it's done with robots. But that's where I find the excitement: I'm gonna actually have time to think. I'm gonna actually have time to be creative. I'm gonna actually have time to be present instead of always going a mile a minute and transacting. I think this is gonna really help us out.

Leslie (Moderator): So you stole my closing, which is gonna be that one of our Transcarent values is being humble and human. And I think it's really interesting that as we talk through what we need to know about AI and the excitement and the various applications—that, kind of without knowing it, we ended up back at being open and transparent and humble about what we know and what we don't know, and how much is going to continue to change over time—and that it's going to allow us to be more human, to spend more time with each other doing the things that we know the AI can't.

Leslie (Moderator): So anyway, thank you all. Please join me in expressing our appreciation for the great expertise that we heard from these two wonderful women.