1 00:00:00,160 --> 00:00:02,560 Everyone. This is Jacob Emerson with the Becker's 2 00:00:02,560 --> 00:00:03,859 Health IT podcast. 3 00:00:04,240 --> 00:00:06,879 Thrilled today to be joined by CVS Health's 4 00:00:06,879 --> 00:00:10,099 vice president of enterprise customer experience and insights. 5 00:00:10,320 --> 00:00:12,160 Sri, thank you so much for taking the 6 00:00:12,160 --> 00:00:13,759 time to be with me on the podcast 7 00:00:13,759 --> 00:00:16,394 today. Pat, thanks, Jacob. Appreciate the time. Excited 8 00:00:16,394 --> 00:00:18,795 to be here with you. Likewise. And before 9 00:00:18,795 --> 00:00:20,394 we dive into everything we wanna talk with 10 00:00:20,394 --> 00:00:22,954 you about, some interesting new tech that CVS 11 00:00:22,954 --> 00:00:24,634 has been rolling out, can you first tell 12 00:00:24,634 --> 00:00:26,574 our audience a little bit more about yourself, 13 00:00:26,870 --> 00:00:28,710 your background in health care, and a little 14 00:00:28,710 --> 00:00:30,890 bit about your role at CVS today? 15 00:00:31,350 --> 00:00:31,910 Yeah. So, 16 00:00:32,549 --> 00:00:35,350 as you mentioned, I lead, customer experience and 17 00:00:35,350 --> 00:00:37,590 insights for CVS Health. I I started my 18 00:00:37,590 --> 00:00:39,130 career actually as an economist. 19 00:00:39,975 --> 00:00:40,475 So, 20 00:00:40,935 --> 00:00:43,515 looking more at, you know, markets and evaluating 21 00:00:43,655 --> 00:00:46,234 them for competitive dynamics and 22 00:00:46,615 --> 00:00:49,174 defending mergers and and acquisitions to department of 23 00:00:49,174 --> 00:00:49,674 justice. 24 00:00:50,215 --> 00:00:51,655 And, you know, that's where I kinda first 25 00:00:51,655 --> 00:00:53,149 got exposed to health care. I used to 26 00:00:53,149 --> 00:00:55,869 look at things like hospital mergers and and, 27 00:00:55,869 --> 00:00:57,949 you know, medical device mergers, and I got 28 00:00:57,949 --> 00:01:00,189 really fascinated by health care. And then my 29 00:01:00,189 --> 00:01:01,710 career kinda took a a bit of a 30 00:01:01,710 --> 00:01:04,129 winding path. I worked at, you know, GE, 31 00:01:04,590 --> 00:01:05,810 including GE Healthcare, 32 00:01:06,454 --> 00:01:08,314 Did spend some time at Wells Fargo, 33 00:01:08,615 --> 00:01:10,215 you know, in the banking industry, so got 34 00:01:10,215 --> 00:01:11,734 a little bit more exposure to the to 35 00:01:11,734 --> 00:01:13,194 the regulated banking industry 36 00:01:13,655 --> 00:01:16,295 before joining here, at CVS Health. And my 37 00:01:16,295 --> 00:01:17,674 role at CVS Health 38 00:01:18,295 --> 00:01:20,715 is I look at all of the consumer 39 00:01:20,775 --> 00:01:23,769 feedback we get, whether that's through surveys 40 00:01:24,229 --> 00:01:24,729 or, 41 00:01:25,189 --> 00:01:27,849 social media data, digital session data, 42 00:01:28,229 --> 00:01:30,549 call transcripts, whatever we can get our hands 43 00:01:30,549 --> 00:01:31,049 on 44 00:01:31,670 --> 00:01:32,409 to understand, 45 00:01:32,869 --> 00:01:35,525 what are some of the patient client, you 46 00:01:35,525 --> 00:01:38,405 know, member pain points that we have across 47 00:01:38,405 --> 00:01:40,584 our entire enterprise, so retail at 48 00:01:41,444 --> 00:01:42,984 health care delivery, Caremark. 49 00:01:43,685 --> 00:01:45,844 And how do we improve the experiences for 50 00:01:45,844 --> 00:01:48,084 those stakeholders and make sure that we're delivering 51 00:01:48,084 --> 00:01:49,305 best in class experiences 52 00:01:50,120 --> 00:01:51,719 so that those people can get the health 53 00:01:51,719 --> 00:01:52,700 care they need. 54 00:01:53,000 --> 00:01:54,680 When I when I kinda give my team 55 00:01:54,680 --> 00:01:56,359 a tagline, I say our job is to 56 00:01:56,359 --> 00:01:58,520 learn from the past, improve the present, and 57 00:01:58,520 --> 00:01:59,500 predict the future, 58 00:01:59,799 --> 00:02:02,200 particularly with respect for our members who we 59 00:02:02,200 --> 00:02:04,219 serve as the internal advocate for 60 00:02:04,645 --> 00:02:07,204 across all of our our internal teams, whether 61 00:02:07,204 --> 00:02:09,944 that's in technology or the business or elsewhere. 62 00:02:10,724 --> 00:02:12,965 Understood. So your background is more in the 63 00:02:12,965 --> 00:02:15,685 business and finance sector. Now you're here at 64 00:02:15,685 --> 00:02:16,185 CVS, 65 00:02:17,125 --> 00:02:19,305 modeling what patients and and customers 66 00:02:19,604 --> 00:02:21,439 are doing. And and you're here with us 67 00:02:21,439 --> 00:02:23,219 today, Shree, to talk a little bit about, 68 00:02:24,400 --> 00:02:26,879 something really interesting that we I I haven't 69 00:02:26,879 --> 00:02:28,799 necessarily heard a lot from other health care 70 00:02:28,799 --> 00:02:30,340 organizations, at least publicly. 71 00:02:31,439 --> 00:02:33,599 CVS, since late last year, has been rolling 72 00:02:33,599 --> 00:02:36,245 out Agentic AI twin simulations. 73 00:02:37,344 --> 00:02:39,585 So talk to our audience about what that 74 00:02:39,585 --> 00:02:41,125 is. When you talk about 75 00:02:41,504 --> 00:02:42,485 agentic twins, 76 00:02:43,025 --> 00:02:44,865 what does that actually mean, and and what 77 00:02:44,865 --> 00:02:46,485 does that actually look like in practice 78 00:02:46,865 --> 00:02:48,245 for CVS specifically? 79 00:02:48,980 --> 00:02:50,580 Yeah. And I bet on this podcast, you 80 00:02:50,580 --> 00:02:51,780 talked to a lot of leaders who talk 81 00:02:51,780 --> 00:02:53,780 about being consumer centric. Right? And I think 82 00:02:53,780 --> 00:02:54,840 that's something that 83 00:02:55,219 --> 00:02:57,300 everyone says. You probably see it in every 84 00:02:57,300 --> 00:02:58,520 single 10 k 85 00:02:58,900 --> 00:03:00,360 out there, every CEO, 86 00:03:00,819 --> 00:03:03,264 dialogue. I I think what's hard is being 87 00:03:03,264 --> 00:03:05,905 consumer centric is really difficult. Getting the voice 88 00:03:05,905 --> 00:03:08,145 of that customer into all of the aspects 89 00:03:08,145 --> 00:03:09,125 of what you do 90 00:03:09,425 --> 00:03:11,185 is challenging because it's hard to get to 91 00:03:11,185 --> 00:03:12,784 customers. It's hard to talk to them. It's 92 00:03:12,784 --> 00:03:15,185 hard for you to test things with them 93 00:03:15,185 --> 00:03:16,724 or and learn from them. 94 00:03:17,129 --> 00:03:18,650 You're limited in terms of how you can 95 00:03:18,650 --> 00:03:20,729 outreach these folks. You know, you can leverage 96 00:03:20,729 --> 00:03:22,270 surveys or maybe the scale. 97 00:03:22,810 --> 00:03:24,270 You know, you have to do pilots. 98 00:03:24,969 --> 00:03:25,469 And 99 00:03:25,849 --> 00:03:28,969 it's being consumer centric is challenging. You have 100 00:03:28,969 --> 00:03:30,189 that challenge simultaneously 101 00:03:30,729 --> 00:03:31,229 with 102 00:03:31,605 --> 00:03:33,605 the advent of AI and all the advancements 103 00:03:33,605 --> 00:03:34,745 you're having in AI. 104 00:03:35,444 --> 00:03:38,245 And what we realized in in working with 105 00:03:38,245 --> 00:03:41,044 these, you know, company from Stanford founded by 106 00:03:41,044 --> 00:03:43,125 a bunch of PhDs and computer science from 107 00:03:43,125 --> 00:03:43,625 Stanford 108 00:03:44,004 --> 00:03:45,705 is that we can actually build 109 00:03:47,000 --> 00:03:50,060 agentic twins of our customers or or patients 110 00:03:50,120 --> 00:03:50,860 or clients 111 00:03:51,560 --> 00:03:52,620 where we can actually 112 00:03:52,919 --> 00:03:54,699 build the way they make decisions. 113 00:03:55,479 --> 00:03:56,760 So not just what they did in the 114 00:03:56,760 --> 00:03:58,760 past, but how do they actually make decisions? 115 00:03:58,760 --> 00:03:59,740 How do they actually, 116 00:04:00,745 --> 00:04:03,144 handle trade offs? What are the behaviors that 117 00:04:03,144 --> 00:04:05,485 they they would exhibit in a given situation? 118 00:04:06,664 --> 00:04:09,004 And then we can generalize that to new 119 00:04:09,064 --> 00:04:12,025 scenarios and new situations. So if you do 120 00:04:12,025 --> 00:04:14,664 that at scale, and in our case, something 121 00:04:14,664 --> 00:04:15,805 like a 100,000 122 00:04:16,399 --> 00:04:16,899 plus 123 00:04:17,439 --> 00:04:18,500 Agenctic Twins, 124 00:04:19,199 --> 00:04:21,279 you will have a set of customers with 125 00:04:21,279 --> 00:04:22,419 you all the time 126 00:04:22,720 --> 00:04:25,279 that are, you know, effectively amplifying the consumer 127 00:04:25,279 --> 00:04:25,779 voice. 128 00:04:26,240 --> 00:04:28,339 So they are with you from when you 129 00:04:28,995 --> 00:04:31,074 develop the product, when you wanna test the 130 00:04:31,074 --> 00:04:33,975 outcome, if you wanna test some operational change. 131 00:04:34,595 --> 00:04:38,134 And they it creates that real consumer centricity 132 00:04:38,355 --> 00:04:38,855 because 133 00:04:39,314 --> 00:04:41,795 that representation of the consumer, how they think, 134 00:04:41,795 --> 00:04:43,980 how they behave is with you throughout the 135 00:04:43,980 --> 00:04:44,959 entire process. 136 00:04:45,579 --> 00:04:47,899 So, you know, it's the way we've gone 137 00:04:47,899 --> 00:04:49,740 about doing that is we ingest a lot 138 00:04:49,740 --> 00:04:52,560 of different information. Of course, all consumer consented, 139 00:04:53,180 --> 00:04:55,100 but we take things like a a short 140 00:04:55,100 --> 00:04:57,279 behavioral interview, behavioral signals, 141 00:04:58,545 --> 00:05:00,705 spend data, things like that where we can 142 00:05:00,705 --> 00:05:01,685 build a twin 143 00:05:02,305 --> 00:05:04,705 of each individual consumer. And, again, you do 144 00:05:04,705 --> 00:05:05,525 that at scale 145 00:05:06,305 --> 00:05:08,785 where you actually have their thought process with 146 00:05:08,785 --> 00:05:11,365 you, and this agentic twin of the customer 147 00:05:12,389 --> 00:05:14,889 lives on and is always on, 148 00:05:15,589 --> 00:05:18,389 for you to investigate and challenge new concepts, 149 00:05:18,389 --> 00:05:20,629 new ideas, and to actually even perform dress 150 00:05:20,629 --> 00:05:22,629 rehearsals of new things you're trying to launch 151 00:05:22,629 --> 00:05:25,529 out. And it's really helped our decision making 152 00:05:26,154 --> 00:05:28,475 our understanding of the consumer throughout the whole 153 00:05:28,475 --> 00:05:29,694 product life cycle, 154 00:05:30,154 --> 00:05:31,915 and and really just it's brought them to 155 00:05:31,915 --> 00:05:33,194 life in a way that I don't think 156 00:05:33,194 --> 00:05:34,654 was possible in the past. 157 00:05:35,035 --> 00:05:37,514 And now, we really we really do. It's 158 00:05:37,514 --> 00:05:39,035 kinda putting your money where your mouth is 159 00:05:39,035 --> 00:05:39,935 in terms of centricity. 160 00:05:40,909 --> 00:05:42,829 You're having these customers with you across the 161 00:05:42,829 --> 00:05:43,649 entire journey. 162 00:05:44,430 --> 00:05:46,829 Wow. I mean, this is fascinating. You you 163 00:05:46,829 --> 00:05:48,289 literally copy and pasted 164 00:05:48,829 --> 00:05:50,750 your customer base, and and now you can 165 00:05:50,750 --> 00:05:52,909 see how they interact with all your different 166 00:05:52,909 --> 00:05:53,409 businesses. 167 00:05:54,269 --> 00:05:54,769 So 168 00:05:56,055 --> 00:05:58,535 back backing up here, Sri, why did CVS 169 00:05:58,535 --> 00:06:00,535 wanna go down this route? How why do 170 00:06:00,535 --> 00:06:02,394 you wanna leverage this kind of technology? 171 00:06:02,855 --> 00:06:05,435 And what does it actually do problem wise 172 00:06:05,814 --> 00:06:07,834 for your patients and for your customers? 173 00:06:08,295 --> 00:06:10,454 How does it solve issues for them on 174 00:06:10,454 --> 00:06:11,035 the ground? 175 00:06:11,470 --> 00:06:13,069 Yeah. So I think the reason you would 176 00:06:13,069 --> 00:06:15,149 wanna we wanted to undertake this is we 177 00:06:15,149 --> 00:06:18,110 really do take consumer centricity seriously. I mean, 178 00:06:18,110 --> 00:06:20,210 we wanna build products and services 179 00:06:20,830 --> 00:06:23,470 that help people access health care in an 180 00:06:23,470 --> 00:06:24,449 effective way 181 00:06:25,004 --> 00:06:27,245 and really solve the big challenges with The 182 00:06:27,245 --> 00:06:29,824 US health care system around, you know, simplicity, 183 00:06:30,685 --> 00:06:32,365 you know, ease of access, all those things 184 00:06:32,365 --> 00:06:34,785 that you hear about constantly from from patients. 185 00:06:35,485 --> 00:06:37,725 And I think where we we're we're landing 186 00:06:37,725 --> 00:06:39,245 is we have the ability to get to 187 00:06:39,245 --> 00:06:42,040 these folks via traditional methods, whether that's panel 188 00:06:42,040 --> 00:06:43,339 research or surveys 189 00:06:43,800 --> 00:06:45,800 or even to a degree looking at operational 190 00:06:45,800 --> 00:06:48,040 data. But each one of those things had 191 00:06:48,040 --> 00:06:49,819 challenges. Right? Either it was 192 00:06:50,279 --> 00:06:52,680 speed, you know, or fidelity or any of 193 00:06:52,680 --> 00:06:53,740 those things that 194 00:06:54,175 --> 00:06:56,014 that challenge you in terms of getting to 195 00:06:56,014 --> 00:06:57,775 that group. So when we heard about this 196 00:06:57,775 --> 00:07:00,175 methodology and this approach, it was really exciting 197 00:07:00,175 --> 00:07:00,675 because 198 00:07:01,455 --> 00:07:03,694 it would it would really unlock what we've 199 00:07:03,694 --> 00:07:05,375 been trying to do, which is get the 200 00:07:05,375 --> 00:07:05,875 patient 201 00:07:06,539 --> 00:07:08,860 front and center on the way we build 202 00:07:08,860 --> 00:07:10,779 things. And I think if you if you 203 00:07:10,779 --> 00:07:12,939 look at what we've seen so far, the 204 00:07:12,939 --> 00:07:14,860 four main things we've gotten out of these 205 00:07:14,860 --> 00:07:15,360 twins, 206 00:07:15,899 --> 00:07:17,419 just in terms of the value of how 207 00:07:17,419 --> 00:07:19,439 we build, is one speed. 208 00:07:19,975 --> 00:07:22,295 You go from weeks to months to generate 209 00:07:22,295 --> 00:07:23,574 insights. So if you have to go get 210 00:07:23,574 --> 00:07:26,555 a panel and test something, whether that's messaging 211 00:07:26,694 --> 00:07:28,235 or some product or service, 212 00:07:28,694 --> 00:07:30,295 it takes time. You gotta go find those 213 00:07:30,295 --> 00:07:32,775 patients. You have to go interview them. You 214 00:07:32,775 --> 00:07:34,615 know, you have to you have to distill 215 00:07:34,615 --> 00:07:35,355 those insights. 216 00:07:35,699 --> 00:07:37,800 Now we're talking about fifteen to thirty minutes. 217 00:07:38,019 --> 00:07:39,860 And, you know, I'll tell you honestly, Jacob, 218 00:07:39,860 --> 00:07:41,300 the first handful of times we did this, 219 00:07:41,300 --> 00:07:42,979 I was stunned. Like, things that would take 220 00:07:42,979 --> 00:07:45,300 us eight weeks, we were doing in fifteen 221 00:07:45,300 --> 00:07:46,199 to twenty minutes. 222 00:07:47,139 --> 00:07:48,680 The second is fidelity. 223 00:07:49,574 --> 00:07:51,254 You know, you you can only test so 224 00:07:51,254 --> 00:07:53,014 many things with a human being. Right? There's 225 00:07:53,014 --> 00:07:53,914 only so many 226 00:07:54,294 --> 00:07:55,735 scenarios you can put in front of them 227 00:07:55,735 --> 00:07:58,214 before their brain sort of breaks. They'll get 228 00:07:58,214 --> 00:08:00,634 fatigue. You know, the signal quality reduces. 229 00:08:01,574 --> 00:08:03,860 They're not able to answer. With these AI 230 00:08:03,860 --> 00:08:04,360 representations, 231 00:08:04,740 --> 00:08:07,240 you can test thousands of real world scenarios, 232 00:08:07,300 --> 00:08:09,639 and you're not extrapolating out what they're gonna 233 00:08:09,779 --> 00:08:11,639 what they're gonna do in a given situation. 234 00:08:12,180 --> 00:08:14,600 You can present them with tons and thousands 235 00:08:14,819 --> 00:08:16,439 of different scenarios or situations 236 00:08:16,899 --> 00:08:19,134 and see how they'll actually behave. And that 237 00:08:19,134 --> 00:08:21,055 actually also solves a big problem in research 238 00:08:21,055 --> 00:08:22,914 where you have what's called stated intent. 239 00:08:23,214 --> 00:08:25,454 So what someone tells you and what they'll 240 00:08:25,454 --> 00:08:28,574 actually do. And here with this scenario testing, 241 00:08:28,574 --> 00:08:30,574 just because you've generalized how someone makes a 242 00:08:30,574 --> 00:08:32,034 decision or how they think, 243 00:08:32,360 --> 00:08:35,100 you can actually get to the actual behavior 244 00:08:35,560 --> 00:08:38,040 and even understand that gap between stated intent 245 00:08:38,040 --> 00:08:38,940 and actual behavior. 246 00:08:39,399 --> 00:08:41,480 The scale here, you have all these folks 247 00:08:41,480 --> 00:08:41,980 on 248 00:08:42,440 --> 00:08:43,800 all the time, so you don't have to 249 00:08:43,800 --> 00:08:45,259 generalize the small pilots. 250 00:08:45,720 --> 00:08:46,940 You know, you have thousands, 251 00:08:47,375 --> 00:08:49,294 tens of thousands, and so some cases for 252 00:08:49,294 --> 00:08:52,095 the populations we looked at, agentic twins available 253 00:08:52,095 --> 00:08:54,735 to us at all times. So that scale 254 00:08:54,735 --> 00:08:56,674 of the consumer voice is is tremendous 255 00:08:57,294 --> 00:08:59,475 and now available to us to access, 256 00:08:59,929 --> 00:09:01,690 you know, as we go forward. And then 257 00:09:01,690 --> 00:09:04,089 the final component is the reach. Like, these 258 00:09:04,089 --> 00:09:05,230 hard to reach populations 259 00:09:06,329 --> 00:09:07,549 that we often have, 260 00:09:07,929 --> 00:09:10,649 you know, whether that's particular disease states or 261 00:09:10,649 --> 00:09:13,129 conditions where it's just difficult to find those 262 00:09:13,129 --> 00:09:14,909 people or that can be really costly. 263 00:09:15,455 --> 00:09:17,215 Now we only have to really find them 264 00:09:17,215 --> 00:09:19,615 once because then we can create this twin 265 00:09:19,615 --> 00:09:21,215 of that person, and then they'll be with 266 00:09:21,215 --> 00:09:22,975 us the whole time. And it goes back 267 00:09:22,975 --> 00:09:23,715 to, I think, 268 00:09:24,174 --> 00:09:26,254 amplifying that consumer voice with that hard to 269 00:09:26,254 --> 00:09:28,195 reach population particularly because 270 00:09:28,575 --> 00:09:30,514 that's a group that's, you know, often 271 00:09:31,360 --> 00:09:33,759 marginalized because we can't get to that group, 272 00:09:34,080 --> 00:09:35,540 to understand what they're experiencing. 273 00:09:35,920 --> 00:09:37,440 So if you if you wrap all that 274 00:09:37,440 --> 00:09:39,700 up, we're getting away from reacting 275 00:09:40,399 --> 00:09:41,460 to small groups 276 00:09:42,080 --> 00:09:45,139 and with long timelines to get their feedback, 277 00:09:45,894 --> 00:09:48,934 to predicting behavior, acting almost in near real 278 00:09:48,934 --> 00:09:51,434 time, and having these consumers with us along 279 00:09:52,134 --> 00:09:53,195 the entire journey, 280 00:09:53,654 --> 00:09:56,054 it's transformative. It's it's changing the way we 281 00:09:56,054 --> 00:09:58,714 deliver care because we're able to understand 282 00:09:59,289 --> 00:10:01,769 what's gonna actually impact our consumers in a 283 00:10:01,769 --> 00:10:04,429 real way while we're building these products 284 00:10:05,049 --> 00:10:07,450 and not having to do things like, you 285 00:10:07,450 --> 00:10:10,110 know, really narrow pilots and constant testing. 286 00:10:10,410 --> 00:10:11,769 We can go out with a lot more 287 00:10:11,769 --> 00:10:13,230 confidence in what we're doing 288 00:10:13,535 --> 00:10:15,134 because we've been able to dress, rehearse it 289 00:10:15,134 --> 00:10:17,154 with, you know, tens of thousands of customers 290 00:10:17,215 --> 00:10:18,975 before we actually hit the market, and and 291 00:10:18,975 --> 00:10:21,475 anyone has to actually experience what we're building. 292 00:10:22,254 --> 00:10:24,174 Absolutely. I mean, listening to you talk about 293 00:10:24,174 --> 00:10:26,674 this is incredible. It it it sounds transformative. 294 00:10:27,215 --> 00:10:30,830 I I I've done marketing initiatives myself in 295 00:10:30,830 --> 00:10:32,669 terms of doing those panels like you said 296 00:10:32,669 --> 00:10:35,070 that take eight weeks and boiling that down 297 00:10:35,070 --> 00:10:37,250 to fifteen minutes is that's incredible. 298 00:10:38,190 --> 00:10:40,350 Not to mention what to hook on the 299 00:10:40,350 --> 00:10:41,889 last part of your answer, the 300 00:10:42,404 --> 00:10:43,845 the equity of it all of being able 301 00:10:43,845 --> 00:10:46,804 to reach your entire customer base and know 302 00:10:46,804 --> 00:10:47,865 how they all respond, 303 00:10:48,404 --> 00:10:50,404 and not having to put everybody into pockets. 304 00:10:50,404 --> 00:10:52,644 It's it's amazing. I I can't imagine what's 305 00:10:52,644 --> 00:10:54,004 gonna be coming from this. And so I 306 00:10:54,004 --> 00:10:56,745 think that's that's the natural follow-up question here, 307 00:10:56,804 --> 00:10:58,970 Sri, is how does this change the way 308 00:10:58,970 --> 00:10:59,629 that CVS 309 00:11:00,410 --> 00:11:03,690 makes decisions compared to those traditional approaches you 310 00:11:03,690 --> 00:11:05,129 just laid out for us even just from 311 00:11:05,129 --> 00:11:07,690 a marketing perspective. But maybe you could expand 312 00:11:07,690 --> 00:11:09,870 a bit on in terms of clinical decisions, 313 00:11:10,570 --> 00:11:13,274 other areas of the pharmacist of the of 314 00:11:13,654 --> 00:11:15,434 the industry that the company reaches. 315 00:11:16,134 --> 00:11:18,214 How does this change the day to day 316 00:11:18,214 --> 00:11:20,315 for CVS and and the business overall? 317 00:11:20,774 --> 00:11:21,815 Yeah. And I I can give you a 318 00:11:21,815 --> 00:11:24,534 couple of just concrete examples of that we've 319 00:11:24,534 --> 00:11:26,629 that we've tried so far, that we've seen 320 00:11:26,629 --> 00:11:28,870 success with. I think one, you know, one 321 00:11:28,870 --> 00:11:30,870 classic one for us in the pharmacy side 322 00:11:30,870 --> 00:11:31,610 is adherence. 323 00:11:32,309 --> 00:11:34,789 That's an area we we've got a tremendous 324 00:11:34,789 --> 00:11:36,629 amount of focus. Obviously, we want people to 325 00:11:36,629 --> 00:11:38,470 be adherent to their medication. We want them 326 00:11:38,470 --> 00:11:39,370 to stay healthy. 327 00:11:39,914 --> 00:11:40,894 Accessing medications 328 00:11:41,355 --> 00:11:42,654 is really important to 329 00:11:42,955 --> 00:11:44,955 us. That can be a a difficult group 330 00:11:44,955 --> 00:11:47,674 to talk to, particularly nonadherent patients. There's a 331 00:11:47,674 --> 00:11:49,595 lot of reasons people don't, you know, adhere 332 00:11:49,595 --> 00:11:51,855 to medication. Some of them related to stigma, 333 00:11:52,394 --> 00:11:52,894 fear. 334 00:11:53,459 --> 00:11:55,299 And you're in a sense, if you're going 335 00:11:55,299 --> 00:11:56,439 to talk to that group, 336 00:11:56,980 --> 00:11:59,620 you're making them relive whatever that was the 337 00:11:59,620 --> 00:12:01,939 challenge that they had. And that can be 338 00:12:01,939 --> 00:12:04,419 really difficult that you it can lead to 339 00:12:04,419 --> 00:12:06,704 false signals. It can lead to, you know, 340 00:12:06,704 --> 00:12:08,784 different types of challenges in terms of getting 341 00:12:08,784 --> 00:12:09,684 to the population, 342 00:12:10,065 --> 00:12:12,625 fatigue, lack of sample, those sorts of things 343 00:12:12,625 --> 00:12:14,644 because they're just a difficult group to reach. 344 00:12:15,184 --> 00:12:16,464 What we were able to do with the 345 00:12:16,464 --> 00:12:18,225 twins is we were able to actually go 346 00:12:18,225 --> 00:12:21,684 through and and investigate in detail adherence issues. 347 00:12:22,990 --> 00:12:24,909 So get because you don't have to face 348 00:12:24,909 --> 00:12:26,829 that and it's you know, you don't have 349 00:12:26,829 --> 00:12:28,209 that same sort of challenge 350 00:12:28,509 --> 00:12:30,850 with the Gentic twins because they're AI representations, 351 00:12:31,629 --> 00:12:33,110 we were able to get way deeper than 352 00:12:33,110 --> 00:12:35,009 I think we could have in a standard 353 00:12:35,149 --> 00:12:37,250 qualitative or even quantitative interview. 354 00:12:37,595 --> 00:12:39,355 What we're we were able to figure out 355 00:12:39,355 --> 00:12:41,115 is a lot of the things about adherence 356 00:12:41,115 --> 00:12:42,795 were the same that you would expect that 357 00:12:42,795 --> 00:12:43,774 we've always seen. 358 00:12:44,475 --> 00:12:45,375 You know, it's, 359 00:12:45,835 --> 00:12:48,394 you know, fear of side effects and fear 360 00:12:48,394 --> 00:12:50,315 of, you know, you know, not being able 361 00:12:50,315 --> 00:12:51,995 to talk to a clinician and all those 362 00:12:51,995 --> 00:12:53,295 things that we've been solving, 363 00:12:53,730 --> 00:12:55,409 over the, you know, course of the past 364 00:12:55,409 --> 00:12:56,070 few years. 365 00:12:56,529 --> 00:12:58,289 But a new one's emerged, and it was 366 00:12:58,289 --> 00:12:59,110 really around 367 00:12:59,730 --> 00:13:02,049 the fear of getting a refill, which sounds 368 00:13:02,049 --> 00:13:04,450 really you know, it sounds a little bit 369 00:13:04,450 --> 00:13:06,450 strange. It wasn't what we expected, but we 370 00:13:06,450 --> 00:13:08,154 were able to see, like, you know, a 371 00:13:08,154 --> 00:13:10,315 lot of what we were observing was people 372 00:13:10,315 --> 00:13:12,075 were saying, okay. Now once I start a 373 00:13:12,075 --> 00:13:13,514 medication, how do I make sure I'm always 374 00:13:13,514 --> 00:13:15,514 gonna get it? What happens if I can't 375 00:13:15,514 --> 00:13:16,414 get that medication? 376 00:13:17,274 --> 00:13:18,875 You know, does that is that gonna have 377 00:13:18,875 --> 00:13:20,794 outcomes for me? And all those things that 378 00:13:20,794 --> 00:13:22,394 we were able to see that that were 379 00:13:22,394 --> 00:13:23,375 clear in the data. 380 00:13:23,709 --> 00:13:25,309 And I think what what it pointed to 381 00:13:25,309 --> 00:13:26,669 is that we have a lot of best 382 00:13:26,669 --> 00:13:28,909 in class digital tools we're building and can 383 00:13:28,990 --> 00:13:29,730 have built 384 00:13:30,110 --> 00:13:31,730 that are making accessing medications 385 00:13:32,509 --> 00:13:34,190 much easier. So it gave us a lot 386 00:13:34,190 --> 00:13:35,009 more confidence 387 00:13:35,754 --> 00:13:37,674 in those tools we're building. And in addition, 388 00:13:37,674 --> 00:13:39,434 we're able to actually look at how do 389 00:13:39,434 --> 00:13:41,355 we optimize some of those tools to ensure 390 00:13:41,355 --> 00:13:41,855 that, 391 00:13:42,235 --> 00:13:44,394 you know, we're we are making it as 392 00:13:44,394 --> 00:13:46,014 easy as possible on the refill. 393 00:13:46,394 --> 00:13:48,235 And I I think what it really pointed 394 00:13:48,235 --> 00:13:49,054 out is 395 00:13:49,379 --> 00:13:52,100 this anxiety, and it's patient anxiety that you 396 00:13:52,100 --> 00:13:52,759 were able 397 00:13:53,139 --> 00:13:54,500 that you were able to see in in 398 00:13:54,500 --> 00:13:57,799 the agentic twins around all the process related 399 00:13:57,860 --> 00:13:59,860 to the prescription. So it wasn't just the 400 00:13:59,860 --> 00:14:00,360 medication. 401 00:14:01,059 --> 00:14:02,120 It was the process 402 00:14:02,514 --> 00:14:03,334 and the experience 403 00:14:03,954 --> 00:14:05,714 that led to adherence. And, you know, we 404 00:14:05,714 --> 00:14:06,995 were able to back that up with a 405 00:14:06,995 --> 00:14:08,914 lot of the actual data we were able 406 00:14:08,914 --> 00:14:11,334 to we were collecting from the customers. 407 00:14:11,794 --> 00:14:13,634 When I say actual, I mean, operational data 408 00:14:13,634 --> 00:14:15,174 that we were collecting from the customers. 409 00:14:16,039 --> 00:14:17,879 It it it was a it's a it 410 00:14:17,879 --> 00:14:19,559 was a way for us to unlock something 411 00:14:19,559 --> 00:14:21,319 that we didn't we didn't see in the 412 00:14:21,319 --> 00:14:21,819 past. 413 00:14:22,199 --> 00:14:24,519 And I think what's particularly unique about it 414 00:14:24,519 --> 00:14:26,919 is we're talking about effectively about robots here, 415 00:14:26,919 --> 00:14:29,579 Jacob. We build robots that represent customers, 416 00:14:30,215 --> 00:14:31,195 but they were unlocking 417 00:14:31,575 --> 00:14:33,674 something that's as that's superhuman 418 00:14:34,774 --> 00:14:35,434 and anxiety. 419 00:14:35,975 --> 00:14:37,654 And so we were able to get to 420 00:14:37,654 --> 00:14:39,975 the emotion through these agentic twins, which I 421 00:14:39,975 --> 00:14:41,355 think is a really fascinating 422 00:14:42,134 --> 00:14:43,434 use case for us. 423 00:14:44,159 --> 00:14:45,840 And then just a a quick related one 424 00:14:45,840 --> 00:14:48,080 just because you mentioned marketing. Another one was 425 00:14:48,080 --> 00:14:49,220 related to our PetRx. 426 00:14:50,080 --> 00:14:51,700 I'm gonna just tell a story really quickly. 427 00:14:52,159 --> 00:14:54,080 You know, PetRx is our our you know, 428 00:14:54,080 --> 00:14:56,259 we're looking to to move into pet care, 429 00:14:56,495 --> 00:14:58,034 and we're looking at how do we message 430 00:14:58,095 --> 00:15:00,334 to those to those, pet parents, if you 431 00:15:00,334 --> 00:15:01,695 will. I'm a pet parent. I've got a 432 00:15:01,695 --> 00:15:02,195 dog. 433 00:15:02,735 --> 00:15:04,174 And, you know, there was a lot of 434 00:15:04,174 --> 00:15:06,735 the data we were expecting, like emotional data 435 00:15:06,735 --> 00:15:08,574 that people care a lot about their pets. 436 00:15:08,574 --> 00:15:10,355 They become, like, family members. 437 00:15:10,700 --> 00:15:12,220 One of the more interesting things we saw 438 00:15:12,220 --> 00:15:13,839 from the Agenctic twins was 439 00:15:14,220 --> 00:15:16,779 people were saying, you know, that even giving 440 00:15:16,779 --> 00:15:18,539 medication to a pet was an act of 441 00:15:18,539 --> 00:15:20,639 devotion, not necessarily a chore. 442 00:15:21,019 --> 00:15:23,339 So any messaging appealing to the emotions was 443 00:15:23,339 --> 00:15:24,320 gonna be successful. 444 00:15:24,735 --> 00:15:26,495 But what the the agentic twins allowed us 445 00:15:26,495 --> 00:15:27,714 to do is present scenarios 446 00:15:28,334 --> 00:15:30,495 beyond that. And what we found was it 447 00:15:30,495 --> 00:15:31,394 wasn't enough 448 00:15:32,014 --> 00:15:33,235 to just be 449 00:15:34,095 --> 00:15:36,495 connecting emotionally. You had to show that we 450 00:15:36,495 --> 00:15:39,129 had the capability to actually get the the 451 00:15:39,129 --> 00:15:40,990 scripts from the veterinarians, 452 00:15:41,529 --> 00:15:44,169 have an understanding what those scripts are, how 453 00:15:44,169 --> 00:15:46,649 the side effects work. That was really important 454 00:15:46,649 --> 00:15:48,429 to the pet parents. So 455 00:15:48,809 --> 00:15:50,649 by being able to drill in and get 456 00:15:50,649 --> 00:15:52,644 to the kind of stated versus actual actual 457 00:15:52,644 --> 00:15:54,804 behavior using the twins, we were able to 458 00:15:54,804 --> 00:15:55,304 uncover 459 00:15:56,085 --> 00:15:58,164 that the messaging needed to have both. It 460 00:15:58,164 --> 00:16:00,644 wasn't sufficient to just have messaging and marketing 461 00:16:00,644 --> 00:16:02,884 that was appealing to emotion. We had to 462 00:16:02,884 --> 00:16:05,320 appeal to the tactical side too, because pet 463 00:16:05,320 --> 00:16:08,379 owners are incredibly pragmatic despite this emotional connection 464 00:16:09,000 --> 00:16:10,940 that I think we all observe and see. 465 00:16:11,159 --> 00:16:13,320 So, anyway, those are two kinda quick examples 466 00:16:13,320 --> 00:16:15,659 of where we've we've seen early wins. 467 00:16:16,200 --> 00:16:18,279 And, you know, we're operating this at scale, 468 00:16:18,279 --> 00:16:20,174 so there's more to come, I think, here 469 00:16:20,174 --> 00:16:21,475 as we keep moving forward. 470 00:16:22,014 --> 00:16:24,254 Oh, absolutely. I I can imagine so. And 471 00:16:24,254 --> 00:16:26,495 for pretty much any company listening in right 472 00:16:26,495 --> 00:16:28,495 now, I would imagine they are taking notes 473 00:16:28,495 --> 00:16:31,054 on how to replicate something like this, Sri, 474 00:16:31,054 --> 00:16:34,169 because the the possibilities seem endless just listening 475 00:16:34,169 --> 00:16:36,350 to even those those two examples you shared, 476 00:16:36,570 --> 00:16:38,090 and I really like how you framed it 477 00:16:38,090 --> 00:16:42,029 of unlocking something that is human. You're you're 478 00:16:42,090 --> 00:16:44,169 unlocking something that the humans on the other 479 00:16:44,169 --> 00:16:46,544 side maybe hadn't been able to before, which 480 00:16:46,544 --> 00:16:47,684 is really fascinating. 481 00:16:48,144 --> 00:16:50,304 It's a really unique AI use case. You 482 00:16:50,304 --> 00:16:52,465 know? It's not it's in a sense, it's, 483 00:16:53,184 --> 00:16:54,384 it's not one of the ones that I 484 00:16:54,384 --> 00:16:55,284 think are traditional, 485 00:16:56,065 --> 00:16:58,865 and it's it's using AI to understand human 486 00:16:58,865 --> 00:16:59,365 behavior, 487 00:16:59,720 --> 00:17:01,259 which, again, sounds a little counterintuitive. 488 00:17:01,960 --> 00:17:03,960 But I think No. It makes sense. Yeah. 489 00:17:03,960 --> 00:17:06,200 Yeah. It's really creating this always on approach 490 00:17:06,200 --> 00:17:09,079 with our customers. Definitely. Definitely. Is there anything 491 00:17:09,079 --> 00:17:11,880 you'd add for for the health care audience 492 00:17:11,880 --> 00:17:14,279 that's listening in terms of the value prop 493 00:17:14,279 --> 00:17:17,115 here for the wider health care system? 494 00:17:17,974 --> 00:17:20,055 Yeah. I think, you know, if you if 495 00:17:20,055 --> 00:17:21,595 I were thinking about more broadly, 496 00:17:22,134 --> 00:17:24,474 a EO, even things like patient experience 497 00:17:24,934 --> 00:17:26,695 and and I'll use the experience tag because 498 00:17:26,695 --> 00:17:28,535 that's that's where I, you know, tend to 499 00:17:28,535 --> 00:17:29,035 focus. 500 00:17:29,910 --> 00:17:30,809 It it's 501 00:17:31,190 --> 00:17:34,090 ability to test messaging. Like, how do we 502 00:17:34,549 --> 00:17:36,549 change in particular in health care is really 503 00:17:36,549 --> 00:17:38,170 painful. That's observed everywhere. 504 00:17:38,789 --> 00:17:41,109 You can see that across multiple populations when 505 00:17:41,109 --> 00:17:42,250 you change people's 506 00:17:42,825 --> 00:17:45,565 medications, when you change formularies, when you change 507 00:17:45,625 --> 00:17:47,484 the way they access care, it's painful. 508 00:17:48,184 --> 00:17:49,704 But what this allows you to do is 509 00:17:49,704 --> 00:17:52,024 test different messaging and different approaches to see 510 00:17:52,024 --> 00:17:54,024 how you how do you smooth that, how 511 00:17:54,024 --> 00:17:55,964 do you make that easier on the patient. 512 00:17:56,184 --> 00:17:58,319 And you're able to do that here in 513 00:17:58,319 --> 00:17:59,940 a controlled, safe environment 514 00:18:00,559 --> 00:18:02,640 that you you are able to see the 515 00:18:02,640 --> 00:18:04,079 results before you actually have to go into 516 00:18:04,079 --> 00:18:05,679 the market and test that. I think that's 517 00:18:05,679 --> 00:18:07,700 a really big unlock for health care. 518 00:18:08,319 --> 00:18:10,339 The the other one, I think, is understanding 519 00:18:10,400 --> 00:18:12,994 journeys. Health care journeys are incredibly complex, 520 00:18:13,615 --> 00:18:15,295 and, you know, it's it can be difficult 521 00:18:15,295 --> 00:18:18,414 to actually get patient feedback along every aspect 522 00:18:18,414 --> 00:18:19,315 of that journey. 523 00:18:19,775 --> 00:18:21,775 But here, you can you can do that, 524 00:18:21,775 --> 00:18:24,035 and you can see how people are experiencing 525 00:18:24,255 --> 00:18:26,674 every aspect of where they engage with you. 526 00:18:27,419 --> 00:18:29,819 And I think understanding quickly where you have 527 00:18:29,819 --> 00:18:31,179 pain points and where you may need to 528 00:18:31,179 --> 00:18:33,099 do some work and may where you're excelling 529 00:18:33,099 --> 00:18:34,879 and maybe where you need to double down. 530 00:18:35,579 --> 00:18:37,519 Health care in particular to me, 531 00:18:38,379 --> 00:18:40,000 this is a way to 532 00:18:40,379 --> 00:18:41,679 test and learn 533 00:18:42,085 --> 00:18:42,585 quickly, 534 00:18:43,765 --> 00:18:44,744 with those audiences. 535 00:18:45,285 --> 00:18:48,164 And I think it's it's a major unlock 536 00:18:48,164 --> 00:18:49,924 because I I think that's where and I 537 00:18:49,924 --> 00:18:51,845 know I keep using the word unlock because 538 00:18:51,845 --> 00:18:53,545 I think in in these populations, 539 00:18:54,440 --> 00:18:56,599 traditionally, it's really difficult to get the feedback, 540 00:18:56,599 --> 00:18:58,940 and they're also really difficult to pilot with. 541 00:18:59,079 --> 00:19:01,160 Because if you're running tests, you're actually running 542 00:19:01,160 --> 00:19:03,420 tests on someone that's experiencing something, 543 00:19:04,200 --> 00:19:06,279 or trying to access care. And that's not 544 00:19:06,279 --> 00:19:08,119 always easy, and that's not always right, and 545 00:19:08,119 --> 00:19:09,259 it's it can be difficult. 546 00:19:09,644 --> 00:19:11,644 Here, you're able to do those tests in 547 00:19:11,644 --> 00:19:13,884 this controlled environment without having to worry about 548 00:19:13,884 --> 00:19:16,125 the patient risk or outcome. It makes it 549 00:19:16,125 --> 00:19:17,644 safer, and it and it makes it more 550 00:19:17,644 --> 00:19:18,144 controlled. 551 00:19:19,164 --> 00:19:21,085 And I think, you know, the follow on 552 00:19:21,085 --> 00:19:23,105 effect is you're gonna deliver better care, 553 00:19:24,089 --> 00:19:25,950 for those patients and for those stakeholders. 554 00:19:26,809 --> 00:19:28,170 Sure. Let me ask you a a bit 555 00:19:28,170 --> 00:19:29,789 of a prodding question. 556 00:19:30,329 --> 00:19:32,029 Just as this technology 557 00:19:32,490 --> 00:19:34,970 continues to develop, we'll continue to see it 558 00:19:34,970 --> 00:19:36,190 across many companies, 559 00:19:36,490 --> 00:19:37,470 different industries. 560 00:19:38,785 --> 00:19:41,105 How are you thinking about how CVS wants 561 00:19:41,105 --> 00:19:41,605 to 562 00:19:41,984 --> 00:19:43,605 ensure responsible use 563 00:19:44,065 --> 00:19:46,945 of of agentic twins at enterprise scale? You 564 00:19:46,945 --> 00:19:49,345 know, you're able to now test an an 565 00:19:49,345 --> 00:19:50,484 external pressure 566 00:19:50,785 --> 00:19:52,400 on on your customer 567 00:19:52,859 --> 00:19:53,920 base. How do you balance, 568 00:19:55,019 --> 00:19:57,259 some of the potential negatives of that or 569 00:19:57,259 --> 00:19:59,500 or ensure that there's gonna be human judgment, 570 00:19:59,500 --> 00:20:00,000 trust, 571 00:20:00,460 --> 00:20:03,019 good governance of this technology as it begins 572 00:20:03,019 --> 00:20:05,440 to as already has started to influence, 573 00:20:06,255 --> 00:20:07,955 real health care on the ground? 574 00:20:08,494 --> 00:20:10,035 Yeah. It's a really important question. 575 00:20:10,414 --> 00:20:12,575 I I think one, we do. We have 576 00:20:12,575 --> 00:20:14,335 very strong controls around this, and there's a 577 00:20:14,335 --> 00:20:15,795 couple different ways we do it. 578 00:20:16,255 --> 00:20:17,795 We continuously test 579 00:20:18,440 --> 00:20:19,099 these twins, 580 00:20:19,640 --> 00:20:21,980 against not only our own data, 581 00:20:22,440 --> 00:20:23,900 but third party studies 582 00:20:24,279 --> 00:20:26,039 to ensure that we have the highest quality 583 00:20:26,039 --> 00:20:26,539 information. 584 00:20:27,160 --> 00:20:28,839 And, you know, one of the things that 585 00:20:28,839 --> 00:20:30,974 we're doing that these twins do as well, 586 00:20:31,214 --> 00:20:32,815 is they actually live in the world, so 587 00:20:32,815 --> 00:20:34,275 they ingest current events. 588 00:20:34,734 --> 00:20:36,494 You know, if you are a, if you 589 00:20:36,494 --> 00:20:38,734 have a a twin that's a democrat, they'll 590 00:20:38,734 --> 00:20:41,294 read democratic news organizations. If you have one 591 00:20:41,294 --> 00:20:43,714 that's a republican, they'll read republican news organizations. 592 00:20:44,255 --> 00:20:45,934 So you're able to actually keep them up 593 00:20:45,934 --> 00:20:46,674 to speed, 594 00:20:47,039 --> 00:20:49,299 you know, even on current events. But 595 00:20:49,840 --> 00:20:51,759 regardless of that, we're always back testing. We're 596 00:20:51,759 --> 00:20:54,080 always making sure that they're meeting our standards 597 00:20:54,080 --> 00:20:54,820 of of 598 00:20:55,440 --> 00:20:56,580 matching known, 599 00:20:57,600 --> 00:20:58,500 human results, 600 00:20:59,119 --> 00:21:01,274 that we have. The second is, you know, 601 00:21:01,274 --> 00:21:04,095 right now, we have my team of researchers. 602 00:21:04,234 --> 00:21:05,294 I have a team of, 603 00:21:05,755 --> 00:21:06,815 you know, analysts 604 00:21:07,194 --> 00:21:10,794 and market researchers that we have organizationally that 605 00:21:10,794 --> 00:21:12,474 are are the ones who are administering this 606 00:21:12,474 --> 00:21:14,575 test because they represent human behavior. 607 00:21:14,970 --> 00:21:16,890 So you can lead the witness. So if 608 00:21:16,890 --> 00:21:18,970 you don't have someone, you know, at the 609 00:21:18,970 --> 00:21:21,929 controls who's engaging with effectively the way it 610 00:21:21,929 --> 00:21:23,470 works is an agentic chat 611 00:21:23,849 --> 00:21:26,169 and you're not asking the questions appropriately, you 612 00:21:26,169 --> 00:21:28,490 can get results that are misleading. So right 613 00:21:28,490 --> 00:21:29,950 now, it's my team of researchers 614 00:21:30,784 --> 00:21:32,865 that are are looking at that information and 615 00:21:32,865 --> 00:21:35,505 validating it, and making sure it's meeting the 616 00:21:35,505 --> 00:21:37,765 standards that we would have for human studies. 617 00:21:38,065 --> 00:21:39,424 But one of the things I point out 618 00:21:39,424 --> 00:21:40,784 there, though, is not to live in an 619 00:21:40,784 --> 00:21:42,085 echo chamber. On occasion, 620 00:21:42,464 --> 00:21:44,224 the Agenent twins will teach us something new 621 00:21:44,224 --> 00:21:45,940 we didn't know, and we shouldn't just be 622 00:21:45,940 --> 00:21:46,840 sitting there saying, 623 00:21:47,220 --> 00:21:49,299 oh, wait. It it didn't match exactly what 624 00:21:49,299 --> 00:21:50,980 we thought in the past, so, therefore, it's 625 00:21:50,980 --> 00:21:53,220 wrong. What we need to do is investigate 626 00:21:53,220 --> 00:21:54,980 it further. So we make sure we have 627 00:21:54,980 --> 00:21:55,720 that process, 628 00:21:56,980 --> 00:21:57,799 built out. 629 00:21:58,394 --> 00:21:59,674 And then I think the third thing and 630 00:21:59,674 --> 00:22:01,994 probably most importantly, I feel like everyone always 631 00:22:01,994 --> 00:22:03,455 frames AI as replacement. 632 00:22:04,315 --> 00:22:05,914 And as like, what is this gonna replace? 633 00:22:05,914 --> 00:22:07,355 It's always the first question you get when 634 00:22:07,355 --> 00:22:09,674 you're deploying an AI solution. I don't think 635 00:22:09,674 --> 00:22:11,775 this is replacing talking to our customers. 636 00:22:12,390 --> 00:22:14,250 It's augmenting our understanding. 637 00:22:14,710 --> 00:22:16,890 It's amplifying their voice, as I've said. 638 00:22:17,190 --> 00:22:19,190 But, ultimately, we're gonna have to always talk 639 00:22:19,190 --> 00:22:21,190 to our customers because that's important, and that's 640 00:22:21,190 --> 00:22:23,029 what good companies do. You need to listen 641 00:22:23,029 --> 00:22:24,549 to people, and you need to understand what 642 00:22:24,549 --> 00:22:26,505 their friction and their pains are. And then, 643 00:22:26,505 --> 00:22:28,744 also, it's important to do that to potentially 644 00:22:28,744 --> 00:22:31,305 catch emerging issues and things like that. So 645 00:22:31,305 --> 00:22:33,464 I view this as additive to what we're 646 00:22:33,464 --> 00:22:35,404 doing with our human populations. 647 00:22:36,105 --> 00:22:37,865 And I think if you you combine those 648 00:22:37,865 --> 00:22:38,684 three things, 649 00:22:39,279 --> 00:22:41,619 you know, the the the back testing, 650 00:22:42,000 --> 00:22:44,319 the researcher at the wheel, and then always 651 00:22:44,319 --> 00:22:46,500 talking to the human populations as well, 652 00:22:46,960 --> 00:22:48,880 it's a major it's a it's a set 653 00:22:48,880 --> 00:22:50,720 of governance that gives you a lot more 654 00:22:50,720 --> 00:22:52,660 confidence in how the twins are operating. 655 00:22:53,075 --> 00:22:55,335 And it also helps you amplify the impact, 656 00:22:56,194 --> 00:22:57,954 because when you're going out to the various 657 00:22:57,954 --> 00:22:58,454 stakeholders 658 00:22:58,755 --> 00:23:00,595 and you're doing the change management of saying, 659 00:23:00,595 --> 00:23:02,835 hey. Listen to listen to these agentic twins. 660 00:23:02,835 --> 00:23:05,095 They're telling us, you know, what to do. 661 00:23:05,539 --> 00:23:07,380 The people you're working with have more confidence 662 00:23:07,380 --> 00:23:08,899 in you because they know that you're taking 663 00:23:08,899 --> 00:23:09,960 the the care 664 00:23:10,659 --> 00:23:12,099 and you're doing the work to make sure 665 00:23:12,099 --> 00:23:13,159 these things are accurate. 666 00:23:13,700 --> 00:23:15,859 Absolutely. And like you said, Shari, I mean, 667 00:23:15,859 --> 00:23:17,640 this is it sounds like this is unlocking 668 00:23:17,700 --> 00:23:19,940 things that your customers were already feeling and 669 00:23:19,940 --> 00:23:20,440 thinking. 670 00:23:20,984 --> 00:23:23,065 Anyway, this is now just another way for 671 00:23:23,065 --> 00:23:24,825 you to for you to reach to reach 672 00:23:24,825 --> 00:23:26,845 that. So really, really fascinating. 673 00:23:27,625 --> 00:23:30,525 Anything else we're missing here? Any final thoughts 674 00:23:30,664 --> 00:23:32,125 you wanna share with our audience? 675 00:23:33,299 --> 00:23:35,059 Yeah. I think, you know, at at CVS 676 00:23:35,059 --> 00:23:38,179 Health, it's not just that we're experimenting with 677 00:23:38,179 --> 00:23:39,720 this because I think a lot of people 678 00:23:39,859 --> 00:23:41,619 will frame this as it it's it is 679 00:23:41,619 --> 00:23:43,619 new. And I I get it's an emerging 680 00:23:43,619 --> 00:23:45,539 technology, but we were at the forefront here. 681 00:23:45,539 --> 00:23:48,105 And I think it's gone beyond experimentation. 682 00:23:48,724 --> 00:23:50,325 You know, we're we're at this point. We're 683 00:23:50,325 --> 00:23:52,184 at operating at scale. As I mentioned, 684 00:23:52,724 --> 00:23:53,704 a 100,000 685 00:23:54,244 --> 00:23:56,005 twins. You know, my hope is to get 686 00:23:56,005 --> 00:23:57,765 us to 300,000 687 00:23:57,765 --> 00:23:59,684 or more in the in the future, but 688 00:23:59,684 --> 00:24:02,130 we're using this responsibly at that scale to 689 00:24:02,130 --> 00:24:03,349 improve people's lives. 690 00:24:03,809 --> 00:24:06,150 And this is giving our teams unprecedented 691 00:24:06,450 --> 00:24:06,950 clarity 692 00:24:07,490 --> 00:24:08,150 and foresight 693 00:24:08,529 --> 00:24:10,930 into, you know, what's happening in the industry, 694 00:24:10,930 --> 00:24:13,009 what's happening with our consumers, how can we 695 00:24:13,009 --> 00:24:15,269 better serve them, how can we build 696 00:24:15,835 --> 00:24:18,015 better experiences? How can we learn faster, 697 00:24:18,634 --> 00:24:20,095 and design better? 698 00:24:20,875 --> 00:24:23,515 It's it's helping us it's a step change 699 00:24:23,515 --> 00:24:25,195 for us in terms of how we actually 700 00:24:25,195 --> 00:24:25,695 deliver, 701 00:24:26,235 --> 00:24:26,975 health care. 702 00:24:27,434 --> 00:24:29,250 And I think in the end, it's gonna 703 00:24:29,250 --> 00:24:31,730 help us deliver better health and support for 704 00:24:31,730 --> 00:24:32,869 every customer member, 705 00:24:33,809 --> 00:24:35,410 that we serve, and we're gonna do it 706 00:24:35,410 --> 00:24:37,269 with more confidence, empathy, and understanding. 707 00:24:37,650 --> 00:24:39,410 And it's gonna help us achieve our goal 708 00:24:39,410 --> 00:24:41,650 of being the most consumer centric company in 709 00:24:41,650 --> 00:24:42,630 health care. So, 710 00:24:43,164 --> 00:24:45,724 yeah, I I hope everyone listening out there, 711 00:24:45,724 --> 00:24:47,184 particularly those in health care, 712 00:24:48,045 --> 00:24:48,944 understand that 713 00:24:49,325 --> 00:24:50,224 this is a, 714 00:24:50,924 --> 00:24:52,545 this is a a a tool 715 00:24:53,164 --> 00:24:55,825 that I think can really give your customers 716 00:24:55,884 --> 00:24:58,144 an unprecedented voice in the way you operate. 717 00:24:59,140 --> 00:25:01,320 100%. I mean, this does seem to be 718 00:25:01,700 --> 00:25:02,839 the one of the largest 719 00:25:03,220 --> 00:25:05,380 commercial rollouts we've seen of this technology or 720 00:25:05,380 --> 00:25:07,940 that we've been, we've heard about in health 721 00:25:07,940 --> 00:25:10,680 care on our end. So, Sri, really appreciate 722 00:25:10,934 --> 00:25:12,615 you taking the time to chat with us 723 00:25:12,615 --> 00:25:15,255 about this, and then please keep us updated 724 00:25:15,255 --> 00:25:17,095 as as this all evolves. We'd love to 725 00:25:17,095 --> 00:25:19,414 hear more about it. Yeah. Always a pleasure, 726 00:25:19,654 --> 00:25:21,095 talking about this, and it was a pleasure 727 00:25:21,095 --> 00:25:23,174 talking with you. So excited to come back 728 00:25:23,174 --> 00:25:24,375 and tell you all the great things we're 729 00:25:24,375 --> 00:25:25,344 doing in the future. 730 00:25:25,744 --> 00:25:27,024 And to our audience, if you'd like to 731 00:25:27,024 --> 00:25:29,344 listen to more podcasts from Becker's Healthcare, you 732 00:25:29,344 --> 00:25:32,084 can visit beckershospitalreview.com.