1 00:00:00,040 --> 00:00:03,920 Welcome to Episode 800 of CXO Talk. 2 00:00:04,360 --> 00:00:08,360 We're speaking with Mozhgan Lafev, the Executive Vice 3 00:00:08,360 --> 00:00:13,280 President and Chief Technology and Operations Officer of 4 00:00:13,280 --> 00:00:17,560 Travelers Insurance. We're talking about digital 5 00:00:17,560 --> 00:00:20,240 transformation and customer experience. 6 00:00:20,520 --> 00:00:25,400 My guest cohost is Q Harrison Terry, the Chief Growth Officer 7 00:00:25,400 --> 00:00:29,750 at the Mark Cuban Companies. My role, as you said heading up 8 00:00:29,750 --> 00:00:34,070 technology and operations is really leading our technology, 9 00:00:34,070 --> 00:00:36,630 our data and analytics, cybersecurity. 10 00:00:36,790 --> 00:00:39,230 And then on the business operations side, it includes 11 00:00:39,230 --> 00:00:42,790 everything from business resiliency to customer service, 12 00:00:42,790 --> 00:00:46,190 premium audit billing and you know a whole bunch of things 13 00:00:46,190 --> 00:00:53,300 that are about customer service role is very much involved with 14 00:00:53,300 --> 00:00:57,740 digital transformation and with customer experience. 15 00:00:58,860 --> 00:01:03,060 Do you want to give us a little bit of overview about that? 16 00:01:03,060 --> 00:01:06,980 You have a very unusual title. It's really two functions that 17 00:01:06,980 --> 00:01:10,300 aren't necessarily inherently always together, but I think 18 00:01:10,300 --> 00:01:14,660 they're very connected because through the customer operations 19 00:01:14,660 --> 00:01:18,090 and service. A lens I, you know I and my 20 00:01:18,090 --> 00:01:20,850 organization, we have the opportunity to truly see the 21 00:01:20,850 --> 00:01:24,010 interaction with the customers, which is really what it's all 22 00:01:24,010 --> 00:01:27,370 about. And when we think of digital 23 00:01:27,370 --> 00:01:29,930 transformation, we don't necessarily use those terms. 24 00:01:29,930 --> 00:01:33,890 We talk about our transformation as our transform agenda and it's 25 00:01:33,890 --> 00:01:35,490 our innovation and transform agenda. 26 00:01:35,490 --> 00:01:40,490 But really what it encompasses is the making sure that we are 27 00:01:40,690 --> 00:01:44,010 serving our customers the way they want, the lighting them 28 00:01:44,010 --> 00:01:47,120 every step of the way. Serving them how they want and 29 00:01:47,120 --> 00:01:49,160 through any channel that they want. 30 00:01:49,160 --> 00:01:52,960 So it's all about the customer experience and this is not 31 00:01:52,960 --> 00:01:55,200 something that has always been the case in the insurance 32 00:01:55,200 --> 00:01:56,920 industry. I'd say it's probably something 33 00:01:56,920 --> 00:02:00,320 that's started with the advent of the consumerization of IT, of 34 00:02:00,320 --> 00:02:02,600 course. And you know we've seen it in in 35 00:02:02,600 --> 00:02:05,320 every industry and it's happening as we speak in ours as 36 00:02:05,320 --> 00:02:07,360 well. Did you give an example of how 37 00:02:07,360 --> 00:02:10,360 you envisioned like the tech that you're working on today, 38 00:02:10,360 --> 00:02:13,280 transforming and enhancing some of those customer experiences 39 00:02:13,840 --> 00:02:16,800 that are existing and soon to be coming? 40 00:02:17,510 --> 00:02:20,550 Some of what we've done over the last few years is truly 41 00:02:20,550 --> 00:02:24,230 enhancing our the mobile experience where from your 42 00:02:24,230 --> 00:02:27,710 mobile phone you can pull up your policy, you can get a 43 00:02:27,990 --> 00:02:30,790 certificate of insurance, you can pay your bill. 44 00:02:31,110 --> 00:02:34,470 And then if you have, you know if if you're unfortunate and do 45 00:02:34,470 --> 00:02:37,150 actually have an accident and want to file, file a claim. 46 00:02:37,390 --> 00:02:39,550 There's a whole slew of capabilities that you can 47 00:02:39,550 --> 00:02:41,190 actually perform on your mobile phone. 48 00:02:41,510 --> 00:02:43,950 And these weren't things that we had before and actually. 49 00:02:44,480 --> 00:02:48,960 The rating we had several years ago on on the iOS was 2.7 and 50 00:02:48,960 --> 00:02:52,280 today it stands at, you know, over 4 1/2. 51 00:02:52,280 --> 00:02:54,040 So you're managing the expectation, right. 52 00:02:54,040 --> 00:02:58,000 So it's like the customers expect X because that's the 53 00:02:58,000 --> 00:03:00,520 world we live in and that's where the the technological 54 00:03:00,520 --> 00:03:04,200 innovations have existed. When you have a legacy brand 55 00:03:04,200 --> 00:03:07,640 like Travelers where you're you're known for doing what you 56 00:03:07,640 --> 00:03:10,720 do, you're you're making sure that you're not too far behind, 57 00:03:10,720 --> 00:03:12,760 but you're right where you need to be and it's a seamless 58 00:03:12,760 --> 00:03:14,610 experience. Absolutely. 59 00:03:14,610 --> 00:03:16,690 I mean, I couldn't have said it better myself. 60 00:03:16,690 --> 00:03:19,290 You know, we're all about really delivering at our promise, which 61 00:03:19,290 --> 00:03:22,370 is to take care of our customers at their most difficult times. 62 00:03:22,370 --> 00:03:26,010 And that is absolutely our core. That's what we're known for and 63 00:03:26,010 --> 00:03:27,730 that's what everybody loves us for. 64 00:03:27,970 --> 00:03:31,370 So we want to make sure that we're leveraging technology to 65 00:03:31,370 --> 00:03:34,130 deliver that promise as effectively and in the most 66 00:03:34,130 --> 00:03:37,370 modern way possible. And as you said, exactly the way 67 00:03:37,370 --> 00:03:41,420 our customers expect it. You mentioned that your rating 68 00:03:41,420 --> 00:03:45,100 in the App Store went from pretty low to very high. 69 00:03:45,940 --> 00:03:52,140 There must be a cultural, organizational dimension behind 70 00:03:52,140 --> 00:03:55,940 that because I don't think it's a matter of, oh, well, now we 71 00:03:55,940 --> 00:03:58,460 have better technology. Well, you had good technology 72 00:03:58,460 --> 00:04:02,220 before as well. So can you elaborate on that 73 00:04:02,220 --> 00:04:04,990 aspect of it? For me, I always say that the 74 00:04:04,990 --> 00:04:08,230 toughest thing about technology and technology initiatives isn't 75 00:04:08,230 --> 00:04:10,790 necessarily the actual technology itself, it's the 76 00:04:10,790 --> 00:04:14,350 adoption, it's the change management, it's people being 77 00:04:14,350 --> 00:04:16,430 open to that. And and I agree that like the 78 00:04:16,430 --> 00:04:20,350 mindset, the culture and how an organization is, is probably one 79 00:04:20,350 --> 00:04:24,150 of the core elements of how that works and really your talent, 80 00:04:24,150 --> 00:04:26,480 that's that's. Core to making all of this 81 00:04:26,480 --> 00:04:29,960 transformation. So you know we set out as as I 82 00:04:29,960 --> 00:04:32,440 joined the organization, we set out on making sure that we 83 00:04:32,440 --> 00:04:36,120 established first of all our strategic priorities where we 84 00:04:36,120 --> 00:04:39,400 said you know we are going to continue to invest in our 85 00:04:39,400 --> 00:04:41,640 people. So investing in our people. 86 00:04:41,640 --> 00:04:43,960 Secondly it was about evolving the way we work. 87 00:04:43,960 --> 00:04:46,560 I mean we were working in a very traditional way that I T 88 00:04:46,560 --> 00:04:49,560 organizations work with their business where you know things 89 00:04:49,560 --> 00:04:53,320 are thrown over the wall and and you go off and you work for. 90 00:04:53,780 --> 00:04:56,140 You know months or or at least that's how it used to be months 91 00:04:56,140 --> 00:04:58,500 or a year or two and then come back and say here I've, I've 92 00:04:58,500 --> 00:05:01,140 built you the solution. And so it was truly moving us 93 00:05:01,140 --> 00:05:04,700 away from that ensuring that you know we started always with what 94 00:05:04,700 --> 00:05:06,380 what's the business problem we're solving. 95 00:05:06,380 --> 00:05:08,940 You know what what's the expectation of the customer, the 96 00:05:08,940 --> 00:05:12,500 stakeholder. And so we definitely drove kind 97 00:05:12,500 --> 00:05:15,780 of an agile transformation and Dr. drove a kind of product 98 00:05:15,780 --> 00:05:18,600 mindset. Into the organization and you 99 00:05:18,600 --> 00:05:21,640 know started also simplifying and modernizing everything. 100 00:05:21,880 --> 00:05:25,640 But we very much focused on our culture and our teams pulled 101 00:05:25,640 --> 00:05:29,360 together and established our cultural beliefs where you know 102 00:05:29,360 --> 00:05:31,520 it was first and foremost customer first. 103 00:05:32,200 --> 00:05:35,520 The second one was make sure that we are prioritizing. 104 00:05:35,520 --> 00:05:38,600 And then I think probably the third cultural belief that made 105 00:05:38,720 --> 00:05:41,120 all the difference in the world was our test and learn. 106 00:05:41,520 --> 00:05:44,040 Because prior to that, you know, everybody believed that. 107 00:05:44,040 --> 00:05:46,560 You know what, whenever we're doing something, we had to just. 108 00:05:46,950 --> 00:05:50,110 Strive for it to be perfect and and you know regardless of what 109 00:05:50,110 --> 00:05:52,310 goes wrong, don't change your path. 110 00:05:52,310 --> 00:05:55,910 And I think in today's world you actually have to be as flexible 111 00:05:55,910 --> 00:05:58,870 as possible. Recognize when something's not 112 00:05:58,870 --> 00:06:02,630 working and pick up from there. Learn from it and and pivot. 113 00:06:03,030 --> 00:06:07,270 And and so that was really probably what gave our people 114 00:06:07,550 --> 00:06:11,110 kind of the the freedom to to think more openly to be to 115 00:06:11,110 --> 00:06:14,550 understand how innovation works. And and so it was absolutely a 116 00:06:14,550 --> 00:06:17,430 kind of a cultural transformation as much as 117 00:06:17,470 --> 00:06:21,870 everything else. What was the underlying driver 118 00:06:22,470 --> 00:06:26,070 that made you want to undertake, I mean you're an enormous 119 00:06:26,070 --> 00:06:28,230 company. You have what, about 30,000 120 00:06:28,550 --> 00:06:31,750 employees and almost $40 billion in revenue. 121 00:06:32,270 --> 00:06:35,030 So why? Why did you do this? 122 00:06:35,470 --> 00:06:39,070 As I go back to my roots of having been born in in in Iran, 123 00:06:39,750 --> 00:06:42,030 you know, several, many, many years ago I should say. 124 00:06:42,550 --> 00:06:46,670 And then, you know, being there when we had a revolution, our 125 00:06:46,670 --> 00:06:48,710 government was changed. And so really, I would say 126 00:06:48,830 --> 00:06:51,150 probably the future of women completely went. 127 00:06:51,870 --> 00:06:54,310 Down the tube, so to speak. And I knew that as a woman I 128 00:06:54,310 --> 00:06:57,430 really wouldn't have the opportunity to bring my 129 00:06:57,430 --> 00:06:59,590 ambitions which which were big always. 130 00:06:59,590 --> 00:07:01,630 And I don't don't really know what the source of that was. 131 00:07:01,630 --> 00:07:04,790 But I was always pushing myself. And so as I graduated high 132 00:07:04,790 --> 00:07:08,110 school, I worked for a year, you know, saved some money because 133 00:07:08,110 --> 00:07:11,310 my parents couldn't really afford to let send me anywhere 134 00:07:11,310 --> 00:07:15,190 and was lucky enough to get a student visa to come to the US 135 00:07:15,190 --> 00:07:17,590 and. You know, I guess the rest is 136 00:07:17,590 --> 00:07:19,790 history. On that challenge, I wanna ask a 137 00:07:19,790 --> 00:07:22,310 question and this is this is gonna get into a bit of your 138 00:07:22,310 --> 00:07:26,750 background, but I'm gonna transition us to one of the 139 00:07:26,750 --> 00:07:29,110 things that just like when I saw your title, the thing that 140 00:07:29,110 --> 00:07:31,070 screamed to me was okay, you're our travelers. 141 00:07:31,590 --> 00:07:35,790 Everyone knows it's a big data company insurance is all about. 142 00:07:37,000 --> 00:07:39,440 I just it's it's a data play on all sides, right? 143 00:07:39,440 --> 00:07:43,600 Like I give them my data I get a quote I pay the quote premium. 144 00:07:43,640 --> 00:07:47,000 You help me out if I get an unfortunate situation, pretty 145 00:07:47,000 --> 00:07:49,120 streamlined and easy to understand business. 146 00:07:49,360 --> 00:07:53,400 One of the things that's changed in our economy today is as 147 00:07:53,400 --> 00:07:58,480 things have become more digital, the data in itself is very, very 148 00:07:58,480 --> 00:08:01,480 valuable and we are living in an economy where. 149 00:08:02,330 --> 00:08:06,930 Basically anyone with your role or your title is basically the 150 00:08:06,930 --> 00:08:10,330 chief scapegoat officer, right? Where if something goes wrong, 151 00:08:11,130 --> 00:08:14,090 if there's ransomware, if the technology doesn't work, that 152 00:08:14,090 --> 00:08:17,570 blame is placed on you. And my question for you is, like 153 00:08:17,610 --> 00:08:20,730 in this world of cybersecurity and ransomware threats and like 154 00:08:21,170 --> 00:08:24,410 just quite frankly burnout, how have you kept going and how are 155 00:08:24,410 --> 00:08:26,890 you managing that with a company of this size? 156 00:08:27,210 --> 00:08:29,720 I've learned that. The company that you joined 157 00:08:29,720 --> 00:08:32,120 their their kind of their mission, who they're about and 158 00:08:32,120 --> 00:08:35,520 their culture is absolutely paramount and important in, you 159 00:08:35,559 --> 00:08:38,440 know, enjoying your job. So I I don't think that our 160 00:08:38,440 --> 00:08:41,840 organization is 1 where anyone ever gets blamed for one thing. 161 00:08:41,840 --> 00:08:44,880 Now I know that you were dramatizing that in the form of, 162 00:08:44,880 --> 00:08:47,440 look, all of these, all of these are. 163 00:08:48,020 --> 00:08:50,940 For risk and you know, huge risk and and really you know 164 00:08:50,940 --> 00:08:52,700 catastrophes happening so to speak. 165 00:08:52,980 --> 00:08:56,780 And you're right like whether it's the cybersecurity role or 166 00:08:56,780 --> 00:08:59,420 if it's the business continuity role, right, which is a business 167 00:08:59,420 --> 00:09:02,620 role. And and anything from you know 168 00:09:02,700 --> 00:09:06,700 the pandemic to to all the resources that we had externally 169 00:09:06,700 --> 00:09:09,140 not just for the technology organization that also for our 170 00:09:09,140 --> 00:09:11,620 claim organization and others making sure that our 171 00:09:11,620 --> 00:09:13,380 relationships with those vendors were right. 172 00:09:13,380 --> 00:09:16,810 Those are all kind of in the. The purview of my organization 173 00:09:16,810 --> 00:09:20,250 but you know I I never I obviously no leader can do 174 00:09:20,250 --> 00:09:24,250 anything on their own and all the credit obviously goes to the 175 00:09:24,250 --> 00:09:27,770 organization that you build and the you know how cohesive that 176 00:09:27,770 --> 00:09:31,770 that group is and truly bringing the best talent on board and 177 00:09:31,770 --> 00:09:34,650 making sure that you're developing them and and you 178 00:09:34,650 --> 00:09:37,290 know. Helping them do what they do 179 00:09:37,290 --> 00:09:39,650 best. And you know we, we are lucky 180 00:09:39,650 --> 00:09:43,050 and I'm lucky to have a phenomenal team of whether it's 181 00:09:43,050 --> 00:09:47,010 our Chief Information Security Officer or you know The Who we 182 00:09:47,010 --> 00:09:48,890 have at the helm of our business resiliency. 183 00:09:48,890 --> 00:09:51,250 These are like some of the top talents and you know they're 184 00:09:51,250 --> 00:09:54,570 empowered to do their jobs effectively and do things go 185 00:09:54,570 --> 00:09:55,770 wrong. Absolutely. 186 00:09:56,050 --> 00:09:58,890 But you know, The thing is. You know if something goes wrong 187 00:09:58,890 --> 00:10:02,450 I take responsibility for it. If you know and and I strive 188 00:10:02,450 --> 00:10:05,610 that if you know if things go right it's it's obviously 189 00:10:05,610 --> 00:10:09,370 they're doing but my job is to make sure that I just remove the 190 00:10:09,890 --> 00:10:12,450 the problems for them and then you know make sure that we 191 00:10:12,450 --> 00:10:16,490 perform the best possible way. And I have yet to feel like, Oh 192 00:10:16,490 --> 00:10:19,330 my God, like this. This is, I'm going to be blamed 193 00:10:19,330 --> 00:10:22,100 for this thing. One thing that you you mentioned 194 00:10:22,100 --> 00:10:25,580 is the Pandemic and just the current landscape of of 195 00:10:25,660 --> 00:10:29,460 cybersecurity issues. Could you share an example of 196 00:10:29,460 --> 00:10:31,420 how you're managing burnout with your team? 197 00:10:31,420 --> 00:10:35,300 Like what I'm seeing on my end is like I've got rock stars A 198 00:10:35,340 --> 00:10:40,740 players and it's 2023 middle of the year and I'm dealing with 199 00:10:40,740 --> 00:10:43,300 like burnout from my A players, people that I would have never 200 00:10:43,300 --> 00:10:46,420 thought or expected to just be in these faces where they're 201 00:10:46,420 --> 00:10:48,740 just not kicking in all their gears and. 202 00:10:49,340 --> 00:10:51,300 They got us, they got us to hear right. 203 00:10:51,300 --> 00:10:54,620 They got us through all the crazy stuff that just ensued not 204 00:10:54,620 --> 00:10:56,980 too long ago. And I'm curious like what are 205 00:10:56,980 --> 00:10:59,660 you seeing at Travelers and how are you managing that just 206 00:10:59,660 --> 00:11:02,300 giving your role in position? Yeah, I mean, there are 207 00:11:02,300 --> 00:11:05,300 absolutely times where you know and you feel that there's 208 00:11:05,300 --> 00:11:07,860 burnouts. You've gotta be aware of that. 209 00:11:07,860 --> 00:11:11,140 You gotta make sure that you're rewarding people that you 210 00:11:11,140 --> 00:11:13,540 acknowledge that, that you encourage them to, you know, 211 00:11:13,620 --> 00:11:16,900 take their time off. I always do my best not to. 212 00:11:17,360 --> 00:11:20,640 E-mail any of my team members over the weekend unless it's 213 00:11:20,720 --> 00:11:24,400 absolutely necessary, just just behaviors like that I think will 214 00:11:24,400 --> 00:11:27,040 go a long way. But at the end of the day, I 215 00:11:27,040 --> 00:11:28,800 think the world we live in is, you know, these. 216 00:11:29,280 --> 00:11:32,400 The pace is just going to keep getting faster and faster. 217 00:11:32,400 --> 00:11:36,280 And we just have to become better as individuals, you know, 218 00:11:36,640 --> 00:11:39,600 to manage it, to make sure that we're taking care of ourselves. 219 00:11:39,600 --> 00:11:43,440 Because without that, you know, without being healthy, nothing 220 00:11:43,440 --> 00:11:45,400 will happen. Our CEO, actually. 221 00:11:46,260 --> 00:11:50,140 Introduced his like Top 40 leaders in our organization that 222 00:11:50,140 --> 00:11:54,180 we call our operating committee to you know why it's important 223 00:11:54,180 --> 00:11:55,820 to sleep. It's a book that's based on the 224 00:11:55,820 --> 00:11:59,900 science of sleep and that was the book that he sent to all of 225 00:11:59,900 --> 00:12:03,060 us and encouraged us to provide it also to our team members 226 00:12:03,060 --> 00:12:06,140 because he said, you know, if you don't sleep and you, you, I 227 00:12:06,140 --> 00:12:08,300 mean, I think everybody knows that now, but. 228 00:12:08,770 --> 00:12:11,930 There's just so much science behind it and and I think that 229 00:12:11,930 --> 00:12:15,530 just shows you know the culture of the company and and how much 230 00:12:15,970 --> 00:12:19,450 the organization cares about our people and our talent that we're 231 00:12:19,450 --> 00:12:23,090 very proud of. Please subscribe to our 232 00:12:23,090 --> 00:12:25,930 newsletter. Just go to cxotalk.com and we 233 00:12:25,930 --> 00:12:30,090 will send you our newsletter with upcoming shows, live shows 234 00:12:30,090 --> 00:12:33,650 and you can participate every time and subscribe to our 235 00:12:33,650 --> 00:12:38,360 YouTube channel. We've been talking about data 236 00:12:38,360 --> 00:12:45,280 and transformation. A I is the great driver of 237 00:12:45,280 --> 00:12:49,200 transformation or certainly going to be one of them. 238 00:12:49,840 --> 00:12:53,600 I know you're doing things with a I, can you tell us what you're 239 00:12:53,600 --> 00:12:55,600 doing? But what I'm really interested 240 00:12:55,600 --> 00:13:01,320 in is how do you use those capabilities to drive again to 241 00:13:01,320 --> 00:13:05,090 drive transformation? First and foremost, I'd say we 242 00:13:05,090 --> 00:13:10,530 know that's that there will be no a I strategy or execution at 243 00:13:10,530 --> 00:13:13,810 scale without really having a data strategy understanding that 244 00:13:14,130 --> 00:13:17,610 both the quality and then as as Q pointed out, the volume of 245 00:13:17,610 --> 00:13:20,120 data. Is absolutely critical now for 246 00:13:20,120 --> 00:13:23,760 us, you know this is we've been around for 165 plus years. 247 00:13:23,760 --> 00:13:28,040 So the the amount of data that we have which we of course treat 248 00:13:28,040 --> 00:13:31,840 vary with like the highest respect and ensure the privacy 249 00:13:31,840 --> 00:13:35,200 and security of our customers because that's like the crux of 250 00:13:35,240 --> 00:13:38,600 of the relationship with us. But, but we have that and then 251 00:13:38,600 --> 00:13:41,960 now with the third party sources of data that are that are 252 00:13:41,960 --> 00:13:44,840 available and that are really powerful and I think that's 253 00:13:44,840 --> 00:13:47,440 truly. Our, you know one of the the 254 00:13:47,440 --> 00:13:51,400 deepest parts of our competitive advantage so to speak and and so 255 00:13:51,400 --> 00:13:54,480 everything that we do in terms of whether we're writing a risk 256 00:13:54,480 --> 00:13:59,320 and evaluating that risk to how we price it to you know how much 257 00:13:59,320 --> 00:14:02,360 reserves we we put aside and then all the way to. 258 00:14:02,950 --> 00:14:05,510 The customer experience on what their interactions have been 259 00:14:05,510 --> 00:14:08,590 with us and how to personalize their experience and to ensure 260 00:14:09,030 --> 00:14:12,590 that our customers stay with us and their retention of course is 261 00:14:12,590 --> 00:14:16,910 a is a huge impact as to to our company as as to any company. 262 00:14:17,190 --> 00:14:22,190 So, so we leverage that data and we have done so for many years 263 00:14:22,190 --> 00:14:26,430 to absolutely build models for all of the functions that I 264 00:14:26,430 --> 00:14:29,270 talked about. And then five years ago, we 265 00:14:29,270 --> 00:14:32,270 actually established our AI accelerator, which is very 266 00:14:32,270 --> 00:14:33,910 focused. And machine learning and 267 00:14:33,910 --> 00:14:38,110 automation. And so we've got practices that 268 00:14:38,110 --> 00:14:41,670 are focused on you know with the combination of some of the 269 00:14:41,790 --> 00:14:44,470 geospatial capabilities that we've developed. 270 00:14:44,470 --> 00:14:49,910 So leveraging both vision a, I and and other types of 271 00:14:49,910 --> 00:14:55,030 automation to for example identify the shape of a roof and 272 00:14:55,030 --> 00:14:58,110 to do it as accurately as possible and this really and you 273 00:14:58,110 --> 00:15:00,910 know to to segment the data as as. 274 00:15:01,320 --> 00:15:04,680 Into as small parcels as possible and all of these have 275 00:15:04,680 --> 00:15:06,880 continued to help us to underwriting in a much more 276 00:15:06,880 --> 00:15:09,680 effective way. And you know we've got, we're 277 00:15:09,680 --> 00:15:12,840 known for being one of the best underwriting organizations in 278 00:15:12,840 --> 00:15:15,480 the world of insurance which is really the the core of it. 279 00:15:15,480 --> 00:15:18,360 And then from a customer experience perspective, you know 280 00:15:18,360 --> 00:15:22,920 we've got models that that we built that for example can 281 00:15:22,920 --> 00:15:29,120 identify after a wildfire total damaged homes from images that 282 00:15:29,120 --> 00:15:32,680 we have both pre and post. Catastrophe without having to 283 00:15:32,680 --> 00:15:35,080 send any of our claim folks out there. 284 00:15:35,320 --> 00:15:39,480 So our people are much safer and we have to, we inform our 285 00:15:39,480 --> 00:15:42,120 customers if something like that has happened when they fled 286 00:15:42,120 --> 00:15:44,320 their homes, they really don't even know what's happened. 287 00:15:44,320 --> 00:15:47,200 And you know we call them up, give them the bad news, but also 288 00:15:47,200 --> 00:15:49,480 tell them that we're there to take care of them and start the 289 00:15:49,800 --> 00:15:53,160 the claim process. And for over 90% of our claims 290 00:15:53,160 --> 00:15:56,400 we actually handle them under 30 days, which is really an 291 00:15:56,400 --> 00:16:00,320 industry benchmark. So a I has. 292 00:16:00,750 --> 00:16:05,190 Absolutely being critical and core to to what we do and and 293 00:16:05,310 --> 00:16:09,030 you know we're very focused on it and now with with generative 294 00:16:09,110 --> 00:16:12,350 AI, I mean we've been working on large language models for the 295 00:16:12,350 --> 00:16:17,110 past few years and we've leveraged those in continuing to 296 00:16:17,110 --> 00:16:21,110 improve how submissions come in. So as submissions, you know. 297 00:16:21,780 --> 00:16:24,420 Thousands of them come in. How do you triage those? 298 00:16:24,420 --> 00:16:28,220 How do you leverage these models to actually filter them and make 299 00:16:28,220 --> 00:16:32,500 sure that we're sending the the best ones to our underwriters 300 00:16:32,500 --> 00:16:35,900 and and really reducing that time from when the quote come 301 00:16:36,060 --> 00:16:38,740 from when the submission comes into when we provide the quote 302 00:16:39,060 --> 00:16:42,980 from you know from days to to hours. 303 00:16:43,700 --> 00:16:46,620 And so these are just some of the areas that we're focused on 304 00:16:46,620 --> 00:16:49,660 in terms of leveraging artificial intelligence. 305 00:16:50,200 --> 00:16:53,320 You mentioned AI Accelerator Lab. 306 00:16:53,320 --> 00:16:56,400 Can you tell us just just briefly about that? 307 00:16:56,400 --> 00:16:58,800 And I'm really interested how that's organized. 308 00:16:59,280 --> 00:17:01,520 Sure. How do you organize it and how 309 00:17:01,520 --> 00:17:04,720 does it fit into the broader whole? 310 00:17:04,920 --> 00:17:08,119 But just just briefly. This is one of our teams that 311 00:17:08,119 --> 00:17:13,319 we've established as a center of expertise that goes horizontally 312 00:17:13,319 --> 00:17:15,760 so to speak. And really their their mission 313 00:17:15,760 --> 00:17:18,960 is to first of all make sure that we always have our. 314 00:17:20,010 --> 00:17:22,730 You know, hands on the pulse of what's going on in the industry 315 00:17:22,770 --> 00:17:24,730 as it relates to a I in this case. 316 00:17:25,410 --> 00:17:29,490 And then they're also there to not only you know, make sure 317 00:17:29,490 --> 00:17:31,810 that they themselves have the best skills, but that they are 318 00:17:31,810 --> 00:17:35,770 actually enabling the rest of the organization to to do so as 319 00:17:35,770 --> 00:17:37,890 well. So through establishing you know 320 00:17:37,890 --> 00:17:40,530 becoming being the subject matter experts for the content 321 00:17:40,530 --> 00:17:42,730 that we develop, for our learnings that we have in the 322 00:17:42,730 --> 00:17:47,420 area of a I and. Conducting, you know, conducting 323 00:17:47,420 --> 00:17:52,660 learning classes for that or actually taking in some of some 324 00:17:52,660 --> 00:17:55,620 of our engineers from other areas so that they can become 325 00:17:56,660 --> 00:17:59,540 experts as part of, you know, learning and doing and then 326 00:17:59,540 --> 00:18:01,260 putting them back out in the organization. 327 00:18:01,260 --> 00:18:05,020 So it's really a way for us to advance our R&D, but then also 328 00:18:05,020 --> 00:18:08,620 make sure that we're extending that to other people in the 329 00:18:08,620 --> 00:18:11,490 organization because. Again at the end of the day, I 330 00:18:11,490 --> 00:18:15,010 think every single one of our technologists need to know AI 331 00:18:15,010 --> 00:18:17,250 the same way that you know we say everybody needs to know the 332 00:18:17,250 --> 00:18:20,690 cloud and how how to execute in that environment. 333 00:18:20,970 --> 00:18:24,010 So and and this is part of our data and analytics organization 334 00:18:24,010 --> 00:18:26,170 which is another horizontal and so. 335 00:18:26,880 --> 00:18:29,960 In my organization, I've got like the business unit CI O's 336 00:18:29,960 --> 00:18:33,000 that I think of as verticals who are very aligned to the business 337 00:18:33,000 --> 00:18:35,720 unit, understanding what you know, what the business needs 338 00:18:35,720 --> 00:18:38,600 are, what the business problems are and then we've got a set of 339 00:18:38,880 --> 00:18:43,920 horizontal capabilities that are really foundational and enablers 340 00:18:43,920 --> 00:18:48,080 for the the entire organization. We have a motto at Travelers 341 00:18:48,080 --> 00:18:51,000 which is about, you know, common as possible and unique as 342 00:18:51,000 --> 00:18:54,080 necessary so that we can leverage our scale and really 343 00:18:54,080 --> 00:18:56,540 take advantage of. Building things once and then 344 00:18:56,540 --> 00:18:59,660 making sure others can take advantage of that and and in 345 00:18:59,660 --> 00:19:03,020 order to do that really those those horizontal kind of 346 00:19:03,020 --> 00:19:06,460 platform teams are focused on some of those capabilities. 347 00:19:06,460 --> 00:19:09,100 I mean the obvious one of course is infrastructure which every 348 00:19:09,100 --> 00:19:12,580 company has as a horizontal, but then above that it's our 349 00:19:12,940 --> 00:19:17,260 architecture organization, our digital organization, our 350 00:19:17,780 --> 00:19:19,780 enterprise data and analytics organization. 351 00:19:19,780 --> 00:19:23,440 Again, the these are ones that. Are providing capabilities 352 00:19:23,440 --> 00:19:27,120 horizontally across the board and then building platforms that 353 00:19:27,120 --> 00:19:31,600 are common that can be then leveraged as services throughout 354 00:19:31,600 --> 00:19:34,280 the organization. One of the things that I wanna 355 00:19:34,280 --> 00:19:38,840 talk on as you're mentioning the infrastructure is you don't just 356 00:19:38,840 --> 00:19:42,160 have one iOS app. I think you have several. 357 00:19:42,400 --> 00:19:45,680 And one of them that I think I noticed when I was just doing a 358 00:19:45,680 --> 00:19:48,680 bit of research was the Intelli Drive. 359 00:19:49,040 --> 00:19:52,810 So travelers Intelli Drive. It's very rare someone gets to 360 00:19:52,810 --> 00:19:58,810 sit down like the CTO or someone at this level and ask them what 361 00:19:58,810 --> 00:20:00,370 are you doing with that data, right. 362 00:20:00,370 --> 00:20:03,290 Like cuz I I I mean I my insurance company wants me to 363 00:20:03,290 --> 00:20:06,610 download the same app and they you know I I'm a little 364 00:20:06,610 --> 00:20:09,490 skeptical and I'm not the only person but I'm curious like as a 365 00:20:09,490 --> 00:20:14,690 customer and and from the customer end like why should I 366 00:20:14,690 --> 00:20:18,320 trust you with all of that data. We tell our customers what we do 367 00:20:18,320 --> 00:20:20,640 with the data. We we want that data just 368 00:20:20,640 --> 00:20:24,480 because we'll use it as kind of a a score of like how you drive, 369 00:20:24,840 --> 00:20:26,400 right. And if you're a great driver we 370 00:20:26,400 --> 00:20:29,760 actually give you a break on your price and if you're you 371 00:20:29,760 --> 00:20:32,840 know not such a great driver then your price goes up. 372 00:20:32,840 --> 00:20:35,920 So it's not like we we're very transparent about this because 373 00:20:35,920 --> 00:20:39,640 again we absolutely believe in in you know trust being 374 00:20:39,640 --> 00:20:43,750 important and I would say insurance companies inherently 375 00:20:43,750 --> 00:20:46,910 are not trusted by a people do not trust insurance companies. 376 00:20:46,910 --> 00:20:50,430 But and we believe we are the kind of insurance company that 377 00:20:50,870 --> 00:20:53,510 has proven that you know through what whether it's through what 378 00:20:53,510 --> 00:20:56,630 happens when you have a claim or or you know the fact that we 379 00:20:56,630 --> 00:21:00,510 have never abused the data that we've had for 160 plus years. 380 00:21:00,830 --> 00:21:02,470 What's the baseline on a good driver? 381 00:21:02,470 --> 00:21:04,910 Because a good driver in Texas is a lot different than a good 382 00:21:04,910 --> 00:21:07,350 driver in New Jersey, right? Like, right. 383 00:21:07,350 --> 00:21:09,790 Well, I mean I would say it's probably everything from you 384 00:21:09,790 --> 00:21:12,710 know staying within the speed limit to like how many times you 385 00:21:12,710 --> 00:21:16,270 have brought spot a stop or to you know ultimately like how 386 00:21:16,270 --> 00:21:18,790 many accidents you have which clearly you don't need 387 00:21:18,790 --> 00:21:22,550 telematics for that. But it's it's really that it's 388 00:21:22,550 --> 00:21:24,990 just you know and then distracted driving of course, 389 00:21:24,990 --> 00:21:28,110 which is you know one of the biggest causes of of deaths in 390 00:21:28,110 --> 00:21:31,230 this country is something we're very focused on. 391 00:21:31,230 --> 00:21:34,590 And and you know that's that's another thing that we, you know, 392 00:21:34,590 --> 00:21:37,510 we just want to make sure that people are focused on driving 393 00:21:37,510 --> 00:21:41,390 when when they're doing so. So we've got an interesting 394 00:21:41,390 --> 00:21:44,910 question from the audience from Elizabeth Shaw and she's asking 395 00:21:44,910 --> 00:21:48,470 you know how are the stresses on the insurance business model as 396 00:21:48,470 --> 00:21:51,390 it stands, impact like the digital transformation and 397 00:21:51,390 --> 00:21:53,910 customer experience solutions that you're providing. 398 00:21:54,270 --> 00:21:57,470 I would say lucky enough that you know working for a company 399 00:21:57,470 --> 00:22:00,830 where financially we've been extremely successful knock on 400 00:22:00,830 --> 00:22:05,830 wood over the you know past past many years and you know we're 401 00:22:05,830 --> 00:22:10,430 very focused on shareholder value and and return on on 402 00:22:10,710 --> 00:22:14,910 equity and and you know have had like double digit return on 403 00:22:14,910 --> 00:22:18,590 equity is one of the elements of financials that we absolutely 404 00:22:19,110 --> 00:22:21,350 drive towards and have been doing so and if you look at our 405 00:22:21,350 --> 00:22:23,350 stock price you can you know I think it shows. 406 00:22:23,870 --> 00:22:26,390 Having said that, of course we're very aware of what's going 407 00:22:26,390 --> 00:22:28,950 on. But the wonderful thing is that 408 00:22:28,950 --> 00:22:33,110 our leaders also realize that a lot of what's going on only 409 00:22:33,430 --> 00:22:37,030 makes our transformation all that more important. 410 00:22:37,030 --> 00:22:40,670 And you know everything we do of course has to be very, very 411 00:22:40,670 --> 00:22:43,190 focused and and related and connected to the business 412 00:22:43,190 --> 00:22:44,790 outcomes that our business leaders want. 413 00:22:45,150 --> 00:22:49,150 So we have yet to cut, you know cut our budget so to speak. 414 00:22:49,150 --> 00:22:52,230 I mean you know we, we annually spend 1 1/2 billion on 415 00:22:52,230 --> 00:22:56,350 technology and and you know again over half of that is 416 00:22:56,350 --> 00:22:58,590 really investments in new capabilities. 417 00:22:58,590 --> 00:23:01,790 We've driven down the cost of like our run to enable the 418 00:23:01,790 --> 00:23:04,500 investment. So as as of now, you know, we've 419 00:23:04,500 --> 00:23:07,660 been very responsible in, you know how and what we spent and 420 00:23:07,660 --> 00:23:11,100 that there's there's business cases behind it, but at the same 421 00:23:11,100 --> 00:23:16,540 time have not yet asked being asked to kind of stop any of 422 00:23:16,540 --> 00:23:19,060 what we're doing. What we try to do is be a, you 423 00:23:19,060 --> 00:23:22,420 know, prioritize as much as possible because frankly some of 424 00:23:22,420 --> 00:23:24,780 it is when there's so much change, you know, making sure we 425 00:23:24,780 --> 00:23:28,100 can actually perform and and deliver and and then more 426 00:23:28,100 --> 00:23:31,260 importantly absorb all of the change that that we're creating. 427 00:23:31,300 --> 00:23:33,590 That's a great question. Here's another really 428 00:23:33,590 --> 00:23:37,750 interesting one from Arsalan Khan on Twitter. 429 00:23:37,750 --> 00:23:41,630 Arsalan always listens, and I should call him the great 430 00:23:41,630 --> 00:23:44,070 questioner because he always comes up with these really 431 00:23:44,350 --> 00:23:46,790 thoughtful questions and he says this. 432 00:23:47,390 --> 00:23:55,710 IT alone cannot change culture. Should I T intervene if they see 433 00:23:55,710 --> 00:23:58,190 something that is happening that? 434 00:23:59,060 --> 00:24:03,220 Could cause the culture to be negatively affected. 435 00:24:03,420 --> 00:24:07,180 I always tell our team we are the technology organization we 436 00:24:07,180 --> 00:24:12,140 are it and in in our case we are IT and operations but we're also 437 00:24:12,260 --> 00:24:14,780 travelers and we're probably travelers 1st. 438 00:24:15,140 --> 00:24:18,300 And so not everything we do is just you know to make sure that 439 00:24:18,300 --> 00:24:21,660 our piece of the pie is working but but that you know what we're 440 00:24:21,660 --> 00:24:23,980 doing it's the right thing for the company as a whole. 441 00:24:23,980 --> 00:24:26,300 So I would say every single one of us actually, if something's 442 00:24:26,300 --> 00:24:29,920 happening that isn't good for the culture, we should feel 443 00:24:29,920 --> 00:24:32,400 accountable and do feel accountable and responsible to 444 00:24:32,400 --> 00:24:34,760 make sure that we're doing the right thing, whether it's, you 445 00:24:34,760 --> 00:24:37,720 know, letting our manager know or or or reaching out to our HR 446 00:24:37,720 --> 00:24:41,840 organization or actually you know, our CEO Alan Schnitzer 447 00:24:41,840 --> 00:24:44,720 again, he has he everybody has his e-mail. 448 00:24:44,720 --> 00:24:47,960 He puts it up every time, not that he needs to but he puts it 449 00:24:47,960 --> 00:24:50,600 up in every town hall that he has once 1/4. 450 00:24:50,600 --> 00:24:55,060 And he says call me e-mail me and and people do. 451 00:24:55,300 --> 00:24:58,020 People do. So you know and sometimes it's a 452 00:24:58,020 --> 00:25:02,660 valid and sometimes it's not but it's again you know a culture 453 00:25:02,660 --> 00:25:06,980 that allows for that and and so yeah I mean as you know as 454 00:25:06,980 --> 00:25:12,300 whether you're ITHR you know sales or or anything I think 455 00:25:12,300 --> 00:25:14,540 everybody feels that they could do that and you're and you're 456 00:25:14,540 --> 00:25:16,780 right. IT alone absolutely cannot. 457 00:25:17,100 --> 00:25:20,980 And you know we've got a very strong cultural foundation that 458 00:25:21,490 --> 00:25:24,210 that goes across our enterprise as a whole. 459 00:25:24,210 --> 00:25:27,650 So it's only together that we can kind of change the culture 460 00:25:28,050 --> 00:25:31,570 as you're pointing out. What kind of practical advice 461 00:25:31,570 --> 00:25:37,970 can you offer to technology leaders around this culture 462 00:25:37,970 --> 00:25:41,330 issue? You mentioned the importance of 463 00:25:41,450 --> 00:25:46,570 IT folks to understand that yes, they're IT, but more 464 00:25:46,570 --> 00:25:50,330 importantly, they're part of this larger organization. 465 00:25:51,110 --> 00:25:55,350 Frankly, for many IT folks that's a really hard lesson to 466 00:25:55,350 --> 00:25:57,430 get across. Yeah, because we've been in the 467 00:25:57,430 --> 00:26:00,990 background for so long, right. And or you know we've been 468 00:26:00,990 --> 00:26:03,910 focused on, on that back office so to speak. 469 00:26:03,910 --> 00:26:07,070 And in today's world, you know, I mean you guys started the 470 00:26:07,070 --> 00:26:09,830 conversation with customer experience, customer delight 471 00:26:09,830 --> 00:26:12,550 like the work we do impacts that directly. 472 00:26:12,790 --> 00:26:16,770 So I think really making sure that everybody knows why they do 473 00:26:16,770 --> 00:26:20,490 what they do every day. You know, if they're working on 474 00:26:20,490 --> 00:26:22,970 on a project, you know, what's the problem that they're 475 00:26:22,970 --> 00:26:24,810 solving? Who's the customer, who's the 476 00:26:24,810 --> 00:26:28,490 stakeholder and being confident like knowing that they're there 477 00:26:28,490 --> 00:26:30,450 and they're as they're there as equals. 478 00:26:30,450 --> 00:26:33,360 And you know, not not being afraid and thinking well we're 479 00:26:33,360 --> 00:26:36,240 IT, we shouldn't. You know, it's not our job to do 480 00:26:36,240 --> 00:26:38,360 that. And and really I I, I always say 481 00:26:38,360 --> 00:26:41,440 you're a business person 1st and then you've got your skill sets. 482 00:26:41,640 --> 00:26:44,960 You know, the same way a finance person is a finance person, but 483 00:26:45,000 --> 00:26:46,680 you know they're a business person and they've got their 484 00:26:47,160 --> 00:26:49,920 finance skills or someone's got their underwriting skills and so 485 00:26:49,920 --> 00:26:52,400 on and so forth. So it is a change. 486 00:26:52,400 --> 00:26:57,010 It is absolutely a change. But you know, I'd say the 487 00:26:57,010 --> 00:27:00,650 ability to make sure that you're communicating openly that you're 488 00:27:00,650 --> 00:27:04,690 partnering with other, you know other parts of your business 489 00:27:04,690 --> 00:27:07,410 that you're there to help and that you're actively 490 00:27:07,410 --> 00:27:09,290 participating in solving problems. 491 00:27:09,490 --> 00:27:13,010 I think those are the behaviors that over time and we'll we'll 492 00:27:13,010 --> 00:27:15,890 first of all make sure that everybody else agrees with that 493 00:27:15,890 --> 00:27:17,850 perspective and that you act that way. 494 00:27:17,850 --> 00:27:22,160 And and you know continue to make sure that people are aware 495 00:27:22,160 --> 00:27:24,760 of your knowledge of the business and make sure you you 496 00:27:24,760 --> 00:27:28,080 do know you understand your business and you probably are at 497 00:27:28,080 --> 00:27:32,000 the best place in any company to understand many parts of your 498 00:27:32,000 --> 00:27:33,400 business. You know you can. 499 00:27:33,600 --> 00:27:36,360 You can understand everything and like in so many functions, 500 00:27:36,360 --> 00:27:39,120 because every single function has a lot of technology involved 501 00:27:39,120 --> 00:27:41,600 in it these days. I want to bridge off of that, 502 00:27:41,600 --> 00:27:44,200 right. So follow me here. 503 00:27:44,360 --> 00:27:49,340 So in insurance, you know every. I mean underwriting is like it's 504 00:27:49,340 --> 00:27:51,700 your bread and butter, right. That's when you ask yourself, 505 00:27:51,740 --> 00:27:54,100 you know you're going to look at the risk, you're going to 506 00:27:54,100 --> 00:27:57,580 determine if you as travelers, the insurance company will 507 00:27:57,580 --> 00:28:01,620 insure it and then if yes you guys will give a price and and I 508 00:28:02,420 --> 00:28:05,460 said person pays the premium or the policy. 509 00:28:06,740 --> 00:28:11,300 We're in an era where generative a I has turned everyone to this 510 00:28:11,420 --> 00:28:15,110 thing called automation. And a lot of leaders now have on 511 00:28:15,110 --> 00:28:18,750 their death, you know, how can we automate this process or how 512 00:28:18,750 --> 00:28:23,550 can we make, you know, technology support what we're 513 00:28:23,550 --> 00:28:30,350 doing with less people in 20-30. Do you think underwriting exists 514 00:28:30,350 --> 00:28:33,030 as we know it? Because right now that process 515 00:28:33,030 --> 00:28:36,190 doesn't involve quite a few people and there's there's 516 00:28:36,430 --> 00:28:40,020 there's people involved in it. I'll say nothing will exist as 517 00:28:40,020 --> 00:28:44,540 we know it like that underwriting claim even it you 518 00:28:44,540 --> 00:28:47,060 know coding right, like engineering. 519 00:28:47,060 --> 00:28:49,380 So that I'm comfortable saying now what will it look like? 520 00:28:49,380 --> 00:28:52,380 I have no clue like I'll I'll just tell you like what will it 521 00:28:52,380 --> 00:28:54,620 look like, will there be more automation there? 522 00:28:54,860 --> 00:28:57,700 Absolutely. I, I, you know, I think that 523 00:28:57,700 --> 00:29:01,140 again first of all like you know you can have very positive or 524 00:29:01,140 --> 00:29:03,340 very negative views about the whole AI thing. 525 00:29:03,340 --> 00:29:05,940 I think first and foremost it's you know, I truly hope that the 526 00:29:05,940 --> 00:29:08,060 right regulations get put in place. 527 00:29:08,420 --> 00:29:11,100 You know with the help of our governments, I hope that 528 00:29:11,100 --> 00:29:14,380 companies establish you know ethical frameworks through which 529 00:29:14,700 --> 00:29:17,100 they will operate, which we absolutely have done and we call 530 00:29:17,100 --> 00:29:20,620 it our responsible AI framework. And it's very, very connected by 531 00:29:20,620 --> 00:29:23,220 the way to the the way we've done models and modeling and 532 00:29:23,220 --> 00:29:27,020 pricing ensuring that there's you know, no bias or at least as 533 00:29:27,020 --> 00:29:31,680 little as as possible. And so I, you know we're going 534 00:29:31,680 --> 00:29:35,360 to continue these things. Now the way we're approaching AI 535 00:29:35,360 --> 00:29:40,610 and how generative AI can help is really how can it help us get 536 00:29:40,610 --> 00:29:43,890 our underwriters, our claim people to focus on the more 537 00:29:43,890 --> 00:29:48,290 valuable things and and you know, let automation do a lot of 538 00:29:48,290 --> 00:29:50,210 the kind of grunts work for them. 539 00:29:50,530 --> 00:29:53,530 So for example, one of the solutions that we've just 540 00:29:53,890 --> 00:29:58,090 created a pilot for is for our claim professionals. 541 00:29:58,570 --> 00:30:01,890 They have a lot of knowledge that has been curated over time 542 00:30:01,890 --> 00:30:05,970 but it's in you know dozens if not hundreds of documents and 543 00:30:05,970 --> 00:30:09,890 we've created our own kind of GPT capabilities. 544 00:30:09,890 --> 00:30:14,290 We call it claim GPT and and so and it's it's operating pretty 545 00:30:14,290 --> 00:30:17,090 effectively where you you know the claim professional can ask 546 00:30:17,090 --> 00:30:20,010 it questions and our Chief claim Officer was saying that it's 547 00:30:20,010 --> 00:30:22,970 amazing like the level of accuracy it's coming back with. 548 00:30:22,970 --> 00:30:26,690 So I think you know we again we're thinking of it as how it's 549 00:30:26,690 --> 00:30:29,410 an assistant. Now I have no doubt that people 550 00:30:29,410 --> 00:30:32,170 of course are worrying about well will my job become 551 00:30:32,170 --> 00:30:35,170 redundant, but and I'd say probably all of our jobs that 552 00:30:35,630 --> 00:30:38,230 are at some sort of risk, and the white collar jobs probably 553 00:30:38,230 --> 00:30:41,990 more than any other. So if you're a programmer. 554 00:30:41,990 --> 00:30:44,750 If you're a developer. Unclaimed GPT. 555 00:30:44,870 --> 00:30:47,550 Like you've built this. It's already existing. 556 00:30:47,710 --> 00:30:51,390 How are you dealing with drift? The whole concept of like it's 557 00:30:51,390 --> 00:30:54,190 accurate and then the model starts to enlarge in and 558 00:30:54,190 --> 00:30:57,990 elongate and then it starts to drift and it misrepresents the 559 00:30:57,990 --> 00:30:59,970 data. When you build models and you 560 00:30:59,970 --> 00:31:02,810 train them like machine learning models and you train them. 561 00:31:02,810 --> 00:31:06,930 I mean drift is absolutely like, you know, part of it as many 562 00:31:06,930 --> 00:31:09,210 other things like there's a whole slew of things as part of 563 00:31:09,210 --> 00:31:12,730 our machine learning operations which we've got a group very 564 00:31:12,730 --> 00:31:17,330 focused on that to make sure that you know, we're training as 565 00:31:17,450 --> 00:31:19,050 you know, frequently as possible. 566 00:31:19,050 --> 00:31:23,360 Now with the cloud, that's much more feasible than it used to 567 00:31:23,360 --> 00:31:27,360 be. And again, our data scientists 568 00:31:27,360 --> 00:31:29,360 have been building models for a long time. 569 00:31:29,400 --> 00:31:32,720 So there are a lot of practices that we've put in place very 570 00:31:32,720 --> 00:31:38,480 focused on this. How do you ensure that the 571 00:31:38,920 --> 00:31:45,040 models that you're using don't hallucinate, don't bring in data 572 00:31:45,360 --> 00:31:49,160 from the Internet and essentially make stuff up. 573 00:31:49,550 --> 00:31:53,550 We are doing a huge amount of tests and learn in the in the 574 00:31:53,550 --> 00:31:56,310 field of of generative A I and you know we're very aware I mean 575 00:31:56,350 --> 00:31:59,790 actually like the generative side of it is actually based on 576 00:31:59,790 --> 00:32:01,350 the fact that it can hallucinate, right. 577 00:32:01,350 --> 00:32:03,670 Like it can create content that wasn't there yet. 578 00:32:03,670 --> 00:32:07,030 Now many times that content can be accurate but many times that 579 00:32:07,030 --> 00:32:11,350 content can be just you know I guess hallucinations that are 580 00:32:11,350 --> 00:32:15,230 completely false. So I think there are definitely 581 00:32:15,230 --> 00:32:19,420 elements that and and you know things that can be changed in 582 00:32:19,420 --> 00:32:21,820 the model to increase or decrease the amount of 583 00:32:22,180 --> 00:32:25,820 hallucination and it's like finding the right, I I guess the 584 00:32:25,820 --> 00:32:29,580 right settings for that. And then what we're doing of 585 00:32:29,580 --> 00:32:32,860 course is you know we are going to leverage our own data to to 586 00:32:32,860 --> 00:32:36,340 train, we're not letting the models like just go out to the 587 00:32:36,340 --> 00:32:40,140 Internet and and find anything. So it's like as we leverage 588 00:32:40,140 --> 00:32:43,980 whether it's the existing large models like the open A I's or 589 00:32:43,980 --> 00:32:50,110 Amazon's bedrock or or others or open source Llms that you know, 590 00:32:50,110 --> 00:32:52,750 we're training them again on on our own data. 591 00:32:52,750 --> 00:32:56,190 And that's the critical part. And the beauty of it is it's got 592 00:32:56,190 --> 00:32:59,990 the capabilities that the LLM had, but but it's actually 593 00:32:59,990 --> 00:33:02,070 leveraging our data that we trust. 594 00:33:02,470 --> 00:33:06,110 We have a project that's going on right now with Harvard 595 00:33:06,110 --> 00:33:11,430 Business School where they're analyzing the 800 episodes of 596 00:33:11,430 --> 00:33:15,790 CXO talk transcripts to look for trends over time, things like 597 00:33:15,790 --> 00:33:19,580 that. And we wanted to put it into a 598 00:33:19,580 --> 00:33:21,660 model. And so we did this. 599 00:33:22,020 --> 00:33:24,620 And the first thing is we started asking the questions and 600 00:33:24,620 --> 00:33:28,260 it started giving us these amazing quotes from CIO's, from 601 00:33:28,260 --> 00:33:29,940 all these different incredible people. 602 00:33:30,300 --> 00:33:34,460 The only thing is, as we started going back to look at it, the 603 00:33:34,460 --> 00:33:37,980 folks never said these things. I think the technology leaders, 604 00:33:37,980 --> 00:33:42,430 at least those I, I talked to frequently, we're very like this 605 00:33:42,430 --> 00:33:44,990 is one of the first times that we're just so high on on this 606 00:33:44,990 --> 00:33:47,750 technology and and is there a hype around it. 607 00:33:47,750 --> 00:33:50,550 I'm sure there's some level of hype, but at the same time now 608 00:33:50,550 --> 00:33:53,030 you've got consumers involved in in the interaction. 609 00:33:53,030 --> 00:33:55,430 It is like one of the first times where consumers are 610 00:33:55,430 --> 00:33:57,430 interacting with this technology. 611 00:33:57,430 --> 00:33:59,750 So it's not going to just go away, let's put it this way. 612 00:33:59,750 --> 00:34:03,370 This is different from like the Metaverse and all those other 613 00:34:03,370 --> 00:34:06,210 things, which by the way I think they have promised and they will 614 00:34:06,210 --> 00:34:08,969 be relevant to whatever industries they are and maybe to 615 00:34:08,969 --> 00:34:11,170 all at some point. Same for blockchain. 616 00:34:11,570 --> 00:34:17,810 But, but this one, we just think this is extremely relevant that 617 00:34:17,810 --> 00:34:20,530 I'd say AI as a whole by the way, you know there's AI and 618 00:34:20,530 --> 00:34:23,449 then now with generative AI kind of like at another level. 619 00:34:23,810 --> 00:34:25,889 When I think of AI and where it's at today. 620 00:34:26,500 --> 00:34:28,900 It's interesting to hear that everyone's dealing with the same 621 00:34:28,900 --> 00:34:30,139 problems. It doesn't matter if you're a 622 00:34:30,139 --> 00:34:33,739 one person team or you know a several hundred person team and 623 00:34:33,739 --> 00:34:35,820 you're working with these models, You're dealing with the 624 00:34:35,820 --> 00:34:39,980 same consequences. But in some cases they're not. 625 00:34:40,540 --> 00:34:41,980 They're not much different than the real world. 626 00:34:41,980 --> 00:34:44,860 The AI now has its own perception or? 627 00:34:45,510 --> 00:34:47,630 Experience that it thinks happen. 628 00:34:47,909 --> 00:34:50,989 And we're like saying, no, that's wrong, but it's not much 629 00:34:50,989 --> 00:34:54,790 different than if like you know someone on this show will hear 630 00:34:54,790 --> 00:34:58,110 something that I said entirely differently than I intended it 631 00:34:58,110 --> 00:35:00,710 or that it was perceived. And just because of that, that's 632 00:35:00,710 --> 00:35:02,990 their perception. It's not that they're wrong, 633 00:35:02,990 --> 00:35:05,630 it's just that's their that's their that's that's how they 634 00:35:05,630 --> 00:35:08,310 view things. And that's it's a very like, it 635 00:35:08,310 --> 00:35:11,230 gets very hypothetical and theoretical and I think that's 636 00:35:11,230 --> 00:35:13,550 why this a I thing makes everyone very queavy. 637 00:35:13,980 --> 00:35:20,380 Let me ask a question from LinkedIn very quickly and this 638 00:35:20,380 --> 00:35:25,740 is from Mike Prest who is a Chief Information Officer at a 639 00:35:25,740 --> 00:35:28,260 private equity investment group. And I'm going to ask you to 640 00:35:28,300 --> 00:35:30,860 answer this really quickly because we're simply going to 641 00:35:30,860 --> 00:35:35,900 run out of time as you build out customer facing applications. 642 00:35:35,900 --> 00:35:39,780 What are your thoughts on the challenges in developing AI 643 00:35:39,780 --> 00:35:42,980 driven? Virtual agents as well as the 644 00:35:42,980 --> 00:35:45,700 potential opportunities to drive innovation and growth. 645 00:35:45,700 --> 00:35:48,740 So the challenges and opportunities of AI virtual 646 00:35:48,740 --> 00:35:52,060 agents and and really quickly please AI virtual agents have 647 00:35:52,060 --> 00:35:55,340 you know we've there been their attempts have been made. 648 00:35:55,340 --> 00:35:59,100 I think kind of like the accuracy of them has not 649 00:35:59,100 --> 00:36:02,260 necessarily always been perfect, but then there are companies who 650 00:36:02,260 --> 00:36:03,460 are leveraging them. Of course. 651 00:36:03,460 --> 00:36:07,380 I think that with generative AI that's going to become really 652 00:36:07,380 --> 00:36:12,360 that's one of the areas that's very promising and that it's 653 00:36:12,360 --> 00:36:16,400 going to be an opportunity for you know more kind of AI driven 654 00:36:16,400 --> 00:36:20,680 virtual agents to be leveraged and to make it to make it better 655 00:36:20,680 --> 00:36:23,000 for the customer. Because you know the customer, 656 00:36:23,320 --> 00:36:26,200 if it's good, the customer doesn't even realize that it's 657 00:36:26,200 --> 00:36:28,920 virtual. I want to ask a couple questions 658 00:36:28,920 --> 00:36:31,160 regarding just your personal story that you shared with us 659 00:36:31,200 --> 00:36:34,480 earlier. One of those is you grew up in 660 00:36:34,480 --> 00:36:39,230 Iran and you. End up through a series of 661 00:36:39,230 --> 00:36:42,510 journeys at this role at one of the largest organizations in the 662 00:36:42,510 --> 00:36:45,070 world. One of the questions I have just 663 00:36:46,670 --> 00:36:50,710 just delineating off that is you know what were the skill sets 664 00:36:50,710 --> 00:36:55,550 that helped you just navigate a world where there's not that 665 00:36:55,550 --> 00:36:59,270 many people of color and there's not that many women especially 666 00:36:59,270 --> 00:37:01,540 in the in the market. I think at the end of the day it 667 00:37:01,860 --> 00:37:04,620 comes down to the basics. I say regardless of what your 668 00:37:04,620 --> 00:37:07,500 role is, communication is like at the core of it. 669 00:37:07,900 --> 00:37:12,540 Like you know the ability to express tell a story to inspire 670 00:37:12,540 --> 00:37:16,700 to you know to to both written and verbal and everything. 671 00:37:16,700 --> 00:37:18,940 So I say communication, communication, communication. 672 00:37:18,940 --> 00:37:22,620 And then I say you know, relationships, the ability to to 673 00:37:23,300 --> 00:37:25,700 work with people to have them like you. 674 00:37:26,260 --> 00:37:29,060 You know, if you're trying, if you're leading A-Team, they'll 675 00:37:29,060 --> 00:37:32,500 do a lot more for you if they like you than if they don't. 676 00:37:32,820 --> 00:37:36,940 And then you know, I'd say third is I I think we're always like 677 00:37:36,940 --> 00:37:39,540 many people are, are very hesitant to take risks. 678 00:37:39,540 --> 00:37:42,500 So as I look back to my journey, I would say look when I left 679 00:37:43,380 --> 00:37:46,820 Iran at the age of 19 and I'd, I'd actually got in into medical 680 00:37:46,820 --> 00:37:48,940 school which was always my dream to become a doctor. 681 00:37:48,940 --> 00:37:53,040 Well, I clearly did not become one, but I knew what I wanted 682 00:37:53,040 --> 00:37:56,160 ultimately in terms of like having far more freedom as a 683 00:37:56,160 --> 00:37:59,240 woman than than where I was. And it was a risk. 684 00:37:59,240 --> 00:38:03,120 Like I could have come to the US and you know, not being 685 00:38:03,120 --> 00:38:06,840 successful academically or not have been able to like I don't 686 00:38:06,840 --> 00:38:10,640 know, I guess support myself and so on and so but being resilient 687 00:38:10,640 --> 00:38:13,920 and, you know, taking the risk and the worst case scenario 688 00:38:13,920 --> 00:38:15,640 would be I would have gone back, you know what I mean? 689 00:38:15,640 --> 00:38:18,960 I guess that would have not been a good scenario, but that's how 690 00:38:19,000 --> 00:38:21,800 I think of it. How did you go about building 691 00:38:21,800 --> 00:38:23,880 and developing your executive presence? 692 00:38:24,200 --> 00:38:28,320 I think it happened really through work and practice. 693 00:38:28,720 --> 00:38:31,920 Again, I think the best way to learn is really through doing 694 00:38:31,920 --> 00:38:35,880 and without doing and without failing a few times. 695 00:38:35,920 --> 00:38:38,630 Really. It's like really hard to become 696 00:38:38,630 --> 00:38:40,790 very successful. And so I remember when I was 697 00:38:40,790 --> 00:38:43,910 working like before business schools, I was in my early 20s 698 00:38:43,910 --> 00:38:47,310 and was working at Computer Vision at the time. 699 00:38:47,310 --> 00:38:50,750 And there was going to be a presentation and I and I went to 700 00:38:50,750 --> 00:38:53,950 my boss and I said hey, can I, can I do this now? 701 00:38:53,950 --> 00:38:58,070 You know, people supposedly like, you know, are are afraid 702 00:38:58,070 --> 00:39:00,230 of speaking publicly as they are of dying. 703 00:39:00,230 --> 00:39:03,030 So that's like the second fear that you have dying and then 704 00:39:03,030 --> 00:39:05,150 speaking publicly. So, so it's like putting 705 00:39:05,150 --> 00:39:08,910 yourself out there, you know, working hard, practicing like 706 00:39:08,910 --> 00:39:12,150 you know, practicing because of course but but then doing it and 707 00:39:12,150 --> 00:39:15,030 then doing it enough times where you start to get comfortable and 708 00:39:15,030 --> 00:39:20,330 and you know, be be confident. What advice do you have for 709 00:39:20,330 --> 00:39:25,930 other women who are interested in becoming obviously more 710 00:39:25,930 --> 00:39:31,690 senior in their careers and facing so many challenges of 711 00:39:31,730 --> 00:39:35,410 being a woman in a male dominated career profession? 712 00:39:35,810 --> 00:39:38,410 Be confident, don't be afraid of taking risks. 713 00:39:38,410 --> 00:39:42,570 I I think women might even take that even one step farther where 714 00:39:42,570 --> 00:39:46,010 like a lot of times they think 3-4 years out and say, Oh well, 715 00:39:46,010 --> 00:39:48,440 I'm going to have babies in like 3 years. 716 00:39:48,440 --> 00:39:50,640 So I'm not going to take on this job and it's like okay, Well, 717 00:39:50,640 --> 00:39:53,040 why don't you wait until that happens and then worry about it 718 00:39:53,840 --> 00:39:56,720 Or you know, things like that. Like I, you know, I tell them, 719 00:39:58,120 --> 00:40:00,720 you know, just just again, don't be afraid. 720 00:40:00,800 --> 00:40:03,320 The worst that can happen is it's not going to work out. 721 00:40:03,320 --> 00:40:05,240 You're going to learn something from it and. 722 00:40:05,960 --> 00:40:08,200 I'd say go for it. You know, if you want something, 723 00:40:08,200 --> 00:40:10,880 go for it. No one else is really going to 724 00:40:10,880 --> 00:40:14,360 take care of you. You have to think of yourself, 725 00:40:14,360 --> 00:40:16,720 but then also build relationships and make sure you 726 00:40:16,720 --> 00:40:20,080 have allies which can who can play a huge role in in your 727 00:40:20,080 --> 00:40:22,200 career. And as I look back, I mean I 728 00:40:22,360 --> 00:40:25,040 there have been so many people that were instrumental in 729 00:40:25,040 --> 00:40:27,040 helping me get to where I am today. 730 00:40:27,440 --> 00:40:28,640 You know, when is your book coming out? 731 00:40:28,640 --> 00:40:31,680 You've got such an incredible story and there's so many things 732 00:40:31,680 --> 00:40:32,840 that everyone can learn from you. 733 00:40:32,840 --> 00:40:34,920 Like when is when is that announcement happening? 734 00:40:35,610 --> 00:40:37,490 Thank you too. Well, now you're giving me an 735 00:40:37,490 --> 00:40:41,330 idea. Nothing in the plans yet, but I 736 00:40:41,330 --> 00:40:44,330 really appreciate that. Can we get one more question 737 00:40:44,330 --> 00:40:47,970 squeezed in here very fast from Twitter, Arsalan Khan comes 738 00:40:47,970 --> 00:40:50,130 back. He says something. 739 00:40:50,410 --> 00:40:52,930 This is his assertion. I don't know if I totally agree 740 00:40:52,930 --> 00:40:55,890 with this, but you can decide, he says. 741 00:40:55,970 --> 00:41:00,410 Shareholders want profit, customers want trust. 742 00:41:00,650 --> 00:41:04,090 How do you strike the balance between profit and? 743 00:41:04,580 --> 00:41:05,940 Trust. And I understand what he's 744 00:41:05,940 --> 00:41:07,860 saying. I don't think it's quite that 745 00:41:07,860 --> 00:41:09,020 simple. A dichotomy. 746 00:41:09,020 --> 00:41:10,180 And what do you, what do you think? 747 00:41:10,180 --> 00:41:11,260 Yeah. And I don't think they go 748 00:41:11,260 --> 00:41:14,740 against each other frankly, because what we say is if if 749 00:41:14,740 --> 00:41:17,900 we're not a profitable company, we're not going to be viable to 750 00:41:18,380 --> 00:41:20,940 to deliver the services that we deliver. 751 00:41:21,020 --> 00:41:24,100 But if we do it ethically, if we do it with with trust that we 752 00:41:24,100 --> 00:41:28,100 can create that trust. So we think we can do both and 753 00:41:28,180 --> 00:41:30,740 they absolutely don't go against each other. 754 00:41:31,170 --> 00:41:34,610 Moshkan, thank you so much for being here today with us. 755 00:41:35,130 --> 00:41:37,610 Thank you, Michael. Thank you for having me and both 756 00:41:37,610 --> 00:41:40,970 of you, I mean, and it's been a pleasure, Q and Michael talking 757 00:41:40,970 --> 00:41:43,090 to you. So really appreciate it. 758 00:41:43,330 --> 00:41:46,610 And Q Harrison, Terry, it is great to see you. 759 00:41:47,490 --> 00:41:49,330 It's been a very interesting conversation today. 760 00:41:52,930 --> 00:41:56,210 Everybody thank you for watching, especially those folks 761 00:41:56,210 --> 00:42:00,170 who ask such great questions. You're an amazing audience. 762 00:42:00,620 --> 00:42:05,020 Now before you go, please subscribe to our newsletter. 763 00:42:05,020 --> 00:42:09,140 Just go to cxotalk.com and we will send you our newsletter 764 00:42:09,140 --> 00:42:12,860 with upcoming shows, live shows and you can participate every 765 00:42:12,860 --> 00:42:15,740 time and subscribe to our YouTube channel. 766 00:42:15,740 --> 00:42:19,540 And with that everybody thanks again and have a great day and 767 00:42:19,540 --> 00:42:21,260 we'll see you again. See you again next time.