WEBVTT X-TIMESTAMP-MAP=LOCAL:00:00:00.000,MPEGTS:0 00:06.600 --> 00:07.800 >> Good afternoon, nerd fam, 00:07.800 --> 00:10.110 and welcome back to Las Vegas, Nevada. 00:10.110 --> 00:13.110 We're midway through day one of Google Cloud Next here. 00:13.110 --> 00:14.760 My name's Savannah Peterson, joined 00:14.760 --> 00:17.460 by my brilliant co-host, Rebecca Knight. 00:17.460 --> 00:19.170 Rebecca, how are you doing this afternoon? 00:19.170 --> 00:23.610 >> I am very good, Savannah. Gen AI is the topic du jour. 00:23.610 --> 00:25.857 We cannot get enough of it here on The Cube. 00:25.857 --> 00:27.652 >> Yes, du jour. Do we do everything? 00:27.652 --> 00:29.260 I think at this point, yes. 00:29.260 --> 00:32.640 >> It's true. And one of the most salient places that Gen AI 00:32.640 --> 00:35.820 is having a lot of benefits, is in the call center. 00:35.820 --> 00:38.010 And that's what leads us to talk to our next guest. 00:38.010 --> 00:40.260 >> I know. Very excited to have an nun 00:40.260 --> 00:43.260 and Ron here with us to talk about Gen AI. 00:43.260 --> 00:44.610 We've got two Canadians in the house. 00:44.610 --> 00:46.273 How's the show going for you so far? 00:46.273 --> 00:48.103 >> Yeah, it's great. We're loving the weather. 00:48.103 --> 00:50.850 >> Savannah: I can imagine. 00:50.850 --> 00:54.889 So Ron, just in case folks are not familiar, 00:54.889 --> 00:57.150 give us a little background on Definity. 00:57.150 --> 00:59.250 >> Yeah, so Definity is a Canadian based 00:59.250 --> 01:00.520 PT insurance company. 01:00.520 --> 01:05.220 We offer traditional lines, digital, pet insurance, 01:05.220 --> 01:08.910 commercial insurance, so wide spectrum of products. 01:08.910 --> 01:11.700 >> Savannah: That's awesome. And you have a very unique 01:11.700 --> 01:15.033 title as Chief Architect of Gen AI at Deloitte. 01:16.650 --> 01:18.330 I'm curious, actually, just before we dig in, 01:18.330 --> 01:19.650 how long have you had that, how long has 01:19.650 --> 01:22.380 that role existed at Deloitte? Let's start there. 01:22.380 --> 01:23.820 >> It's been about a year, actually. 01:23.820 --> 01:27.510 >> Yeah. So fresh and, tell us what your day to day is like. 01:27.510 --> 01:30.930 >> So I work with clients to do Gen AI based implementations, 01:30.930 --> 01:32.250 many of them on Google. 01:32.250 --> 01:34.200 And we're looking at solving very 01:34.200 --> 01:35.730 challenging business problems. 01:35.730 --> 01:38.550 So it's a problem where, you know, we need to leverage AI 01:38.550 --> 01:40.333 to either re-engineer processes 01:40.333 --> 01:43.830 or, you know, whether it's process efficiency 01:43.830 --> 01:46.020 or maybe generating new revenue 01:46.020 --> 01:47.070 through marketing or other channels. 01:47.070 --> 01:49.350 So, you know, it's an exciting space. 01:49.350 --> 01:51.960 We're learning more about the tech every day, 01:51.960 --> 01:53.670 and it's evolving, you know, 01:53.670 --> 01:55.800 just the announcements today in the keynote, like, 01:55.800 --> 01:57.300 I'm learning a lot about what's coming 01:57.300 --> 01:59.490 and we're really excited about it too, so, yeah. 01:59.490 --> 02:01.050 >> Well, we're really excited to have you on 02:01.050 --> 02:02.790 because we love customer stories here 02:02.790 --> 02:05.880 because there's so much talk about the technology, the TCUs, 02:05.880 --> 02:07.650 the PCUs, but we want to know really, 02:07.650 --> 02:10.199 how are companies using this technology 02:10.199 --> 02:12.990 to improve the workflows for their employees, 02:12.990 --> 02:15.690 but also improve the experiences for their customers. 02:15.690 --> 02:19.920 So Definity went live with the contact center at the end 02:19.920 --> 02:21.240 of 2023. 02:21.240 --> 02:23.940 Can you give, why don't you start from the beginning about 02:23.940 --> 02:26.940 what was the impetus for this project? 02:26.940 --> 02:29.207 >> Yeah, well, I think you touched on it, right? 02:29.207 --> 02:30.060 How do we improve the customer experience? 02:30.060 --> 02:33.090 How do we improve the employee experience leveraging some 02:33.090 --> 02:35.160 of the new technology that's in market? 02:35.160 --> 02:36.420 So some of the things we looked at are 02:36.420 --> 02:38.880 what were the long poles in those experiences 02:38.880 --> 02:41.100 or in that journey, and a lot of it having to do 02:41.100 --> 02:44.220 with call wrap up, having to do with authentication, right? 02:44.220 --> 02:45.840 So what are things that are taking a lot 02:45.840 --> 02:47.790 of time from a agent's perspective, 02:47.790 --> 02:49.471 but not adding a lot of value, 02:49.471 --> 02:51.784 and then working with partners like Deloitte, 02:51.784 --> 02:54.240 starting to build out what that solution could look like 02:54.240 --> 02:56.310 and how we can drive more efficiencies. 02:56.310 --> 02:58.620 >> How long have you two been working together? 02:58.620 --> 02:59.910 >> I would say two, three years now. Yeah. 02:59.910 --> 03:01.260 >> Yeah. Yeah. 03:01.260 --> 03:02.700 >> And what's the advantage for you 03:02.700 --> 03:05.250 as a customer working with Deloitte? 03:05.250 --> 03:07.680 >> Yeah, I think for us, we want to go fast. 03:07.680 --> 03:09.120 We want to go far, but we know to do 03:09.120 --> 03:10.950 that we can't do it alone, right? 03:10.950 --> 03:12.840 And so partnering with folks like Deloitte, 03:12.840 --> 03:15.720 folks like Google, you know, really brings that relationship 03:15.720 --> 03:17.700 to fruition and we're able to 03:17.700 --> 03:20.100 take up new concepts like CCAI Yeah. 03:20.100 --> 03:22.080 And some of the cool things we saw in the keynote today. 03:22.080 --> 03:24.750 So yeah, I think it's really about leveraging that expertise 03:24.750 --> 03:26.610 that's in market, but also then bringing it 03:26.610 --> 03:28.140 home with our team as well. 03:28.140 --> 03:28.973 >> Yeah. 03:28.973 --> 03:31.380 >> So going back to the impetus for the project, 03:31.380 --> 03:33.840 what were the pain points that you were seeing? 03:33.840 --> 03:36.390 Both for the agents and also for the customers. 03:36.390 --> 03:39.326 >> Yeah. I think call center has call variability. 03:39.326 --> 03:40.710 >> We've all been on, we've all dealt with it. 03:40.710 --> 03:42.750 >> So being able to manage the scaling 03:42.750 --> 03:45.780 or the volatility in call demands is a big thing for us, 03:45.780 --> 03:49.110 right? So how can we drive more efficiency away 03:49.110 --> 03:50.310 from the call agent, right? 03:50.310 --> 03:52.260 So when you actually want to reach someone, you want to have 03:52.260 --> 03:54.390 that person to person conversation, 03:54.390 --> 03:55.830 not be waiting in the queue 03:55.830 --> 03:57.750 because someone's doing authentication or 03:57.750 --> 04:00.090 because the agent's trying to wrap up the call, right? 04:00.090 --> 04:03.300 So we tried to take out some of those low value interactions 04:03.300 --> 04:05.910 so we can have more high value, face to face, 04:05.910 --> 04:08.400 but person to person interactions. 04:08.400 --> 04:10.770 >> Savannah: Well, you want it to feel face to face. 04:10.770 --> 04:12.570 You want it to feel that personable. 04:14.096 --> 04:15.000 I don't think there's anything wrong with that. 04:15.000 --> 04:18.240 And I'm curious, you see a lot of different customers 04:18.240 --> 04:19.529 and across verticals, 04:19.529 --> 04:22.500 I can imagine you're a very popular person these days. 04:22.500 --> 04:23.940 Yeah, absolutely. Within the organization, 04:23.940 --> 04:26.190 you're having a bit of a moment, if you will. 04:27.258 --> 04:31.560 What are some of the trends that you're seeing in general? 04:31.560 --> 04:34.800 Is everyone kind of in a similar place across verticals? 04:34.800 --> 04:36.690 Are there some categories 04:36.690 --> 04:39.060 and spaces that you're seeing run ahead, perhaps 04:39.060 --> 04:43.227 because of their agility or maybe even smaller size? 04:43.227 --> 04:45.713 >> Yeah. So I see a lot of opportunity, 04:45.713 --> 04:48.840 many of our clients, especially in financial services, 04:48.840 --> 04:50.370 they're focused on knowledge retrieval 04:50.370 --> 04:52.770 or, you know, removing information disparity 04:52.770 --> 04:54.150 in our organization. 04:54.150 --> 04:55.320 They want employees to have access 04:55.320 --> 04:58.231 to information instantly relevant to their context so 04:58.231 --> 05:00.990 that they can just move on with whatever tasks they're doing 05:00.990 --> 05:02.070 and actually produce more. 05:02.070 --> 05:03.720 At the end of the day in the call center, 05:03.720 --> 05:06.180 that shows up in a very interesting way. 05:06.180 --> 05:08.623 You know, agents, when they're on a call 05:08.623 --> 05:10.260 with a customer, they're often, you know, 05:10.260 --> 05:11.910 navigating multiple applications. 05:11.910 --> 05:14.880 The most I've ever seen in one flow was like over 05:14.880 --> 05:16.380 30 applications that an agent had 05:16.380 --> 05:18.540 to do to execute an interaction, right? 05:18.540 --> 05:21.570 So if you can remove some of that through automation, 05:21.570 --> 05:23.040 through Generative AI, 05:23.040 --> 05:25.260 moving from the front office into the back office, 05:25.260 --> 05:26.940 doing some of that straight through processing 05:26.940 --> 05:28.710 with Generative AI, you know, 05:28.710 --> 05:30.210 we're seeing customers experiment with that 05:30.210 --> 05:32.130 and also leveraging information retrieval 05:32.130 --> 05:34.350 and knowledge retrieval throughout that journey. 05:34.350 --> 05:36.870 >> Rebecca: And where are they in this phase? 05:36.870 --> 05:38.730 Because, I mean, one of the things that has really come 05:38.730 --> 05:42.360 through, at least in the keynote is that we've gone from, 05:42.360 --> 05:44.790 you know, it was about a year and a half when Chat GPT was 05:44.790 --> 05:47.100 unleashed into the world, to here we are today, 05:47.100 --> 05:50.370 where companies really are just go going from, oh wow, 05:50.370 --> 05:51.810 here's this new bright, shiny toy 05:51.810 --> 05:55.020 to let's really integrate this into our systems. 05:55.020 --> 05:58.590 Where do you think companies are in their journey? 05:58.590 --> 06:00.426 >> Yeah, so I'd say the past year, 06:00.426 --> 06:03.810 or at least in 2023, there was a focus on POCs. 06:03.810 --> 06:06.330 A lot of companies were like, here's this new hammer 06:06.330 --> 06:07.590 and, you know, what are all the 06:07.590 --> 06:09.290 possible things we can do with it? 06:10.290 --> 06:13.650 And this year the focus is really about moving from 06:13.650 --> 06:15.210 POCs into production. 06:15.210 --> 06:17.760 A lot of companies are looking at low value, 06:17.760 --> 06:19.320 high volume processes 06:19.320 --> 06:20.760 and looking to re-engineer them from the 06:20.760 --> 06:22.200 ground up with Generative AI. 06:22.200 --> 06:25.704 And they're building business cases usually based on either 06:25.704 --> 06:29.580 cost savings due do improvement of utilization 06:29.580 --> 06:32.350 of talent, or, you know, other 06:33.390 --> 06:35.640 maybe new capabilities that they want to enable, 06:35.640 --> 06:36.960 new products that they want to enable 06:36.960 --> 06:38.103 with this technology. 06:39.108 --> 06:42.390 So there's a huge push around impactful, you know, 06:42.390 --> 06:45.900 focused deployments of Generative AI that then you can build 06:45.900 --> 06:48.270 as a foundation upon which you can scale. 06:48.270 --> 06:50.820 And ultimately, I think the future operating model 06:50.820 --> 06:53.880 for an organization is one where you have AI agents, 06:53.880 --> 06:56.850 like we saw today, the keynote interacting with humans, 06:56.850 --> 07:00.990 you know, in a collaboration, you know, 07:00.990 --> 07:03.630 so request coming in, going through a collaboration 07:03.630 --> 07:05.474 or orchestration of that. 07:05.474 --> 07:07.710 And so over the next few years, 07:07.710 --> 07:10.010 and you know, I think we're going to see a lot of 07:11.160 --> 07:14.400 new capabilities, new entrants into existing longstanding 07:14.400 --> 07:17.010 industries where there's incumbents, right? 07:17.010 --> 07:20.970 Just trying to, you know, come to market with new processes. 07:20.970 --> 07:22.290 Yeah. 07:22.290 --> 07:23.670 >> What are some of the challenges there? 07:23.670 --> 07:26.070 I mean, you just described that as a very smooth process, 07:26.070 --> 07:27.540 which given that you're a consultant 07:27.540 --> 07:29.637 is sort of the name of the game. 07:29.637 --> 07:32.730 But, I mean, there is obviously there's best practices 07:32.730 --> 07:34.020 and there's a great way to do this. 07:34.020 --> 07:35.130 What's your advice to folks? 07:35.130 --> 07:37.410 I mean, and actually Ron I'll turn this to you first, 07:37.410 --> 07:39.600 to companies who are embarking on this journey, 07:39.600 --> 07:42.120 we're all still in kind of the sandbox stage. 07:42.120 --> 07:43.800 How do they get to that at scale moment 07:43.800 --> 07:45.600 of realization like you've achieved? 07:45.600 --> 07:47.910 >> Yeah, I think maybe if we take a step back, 07:47.910 --> 07:50.850 for us it was even, what, what preceded this, right? 07:50.850 --> 07:52.920 And so we had just gone through our data transformation 07:52.920 --> 07:54.780 journey, which allowed us to be ready for this. 07:54.780 --> 07:55.980 So the timing was great. 07:55.980 --> 07:58.260 We had just moved to Cloud, moved our data platforms 07:58.260 --> 08:00.210 to Cloud, made the data available 08:00.210 --> 08:01.971 for these types of programs. 08:01.971 --> 08:03.690 Then I think it's really about finding your 08:03.690 --> 08:04.950 right risk tolerance, right? 08:04.950 --> 08:07.140 What's your organizational risk appetite? 08:07.140 --> 08:08.460 Do you want to do something that's internal 08:08.460 --> 08:10.110 facing that's lower risk? 08:10.110 --> 08:12.450 Do you want to do something similar to maybe what we did, 08:12.450 --> 08:15.000 which was, again, not directly interacting 08:15.000 --> 08:18.060 with the customer from that sense of kind of respond 08:18.060 --> 08:19.860 and response. 08:19.860 --> 08:20.940 Yeah. I think that's key, right? 08:20.940 --> 08:22.980 Just figure out where your comfort zone is. 08:22.980 --> 08:24.090 And then the opportunity, like I said, 08:24.090 --> 08:27.000 for us is really driving out that talk time, right? 08:27.000 --> 08:28.950 The call time. How can we reduce that 08:28.950 --> 08:30.810 and reduce the pain points that come along 08:30.810 --> 08:32.580 with longer talk times? 08:32.580 --> 08:33.990 >> How does your team feel? 08:33.990 --> 08:36.179 How has your team responded to that adjustment? 08:36.179 --> 08:38.280 Are people, do you feel like morale is up? 08:39.150 --> 08:40.409 >> I think so. I think people are excited for sure. 08:40.409 --> 08:42.179 Like you said, this is the talk of the town, right? 08:42.179 --> 08:44.850 So it's excited to be operating in this space. 08:44.850 --> 08:46.230 We tend to think of ourselves 08:46.230 --> 08:47.340 as the leading organization 08:47.340 --> 08:49.170 and in the digital space, so absolutely. 08:49.170 --> 08:50.970 So it brings that empowerment to the team 08:50.970 --> 08:51.930 that we're not reading about, 08:51.930 --> 08:54.018 but we're actually doing it as well. 08:54.018 --> 08:56.100 >> Oh, we've been talking about it on the show 08:56.100 --> 08:58.230 2024, the year of making AI real. 08:58.230 --> 09:00.172 Not just this hype stage 09:00.172 --> 09:03.840 that we're obviously peaking in right now, big time. 09:03.840 --> 09:08.310 On your side, what's your advice to folks, 09:08.310 --> 09:10.530 or what are the risks you would like to see them avoid 09:10.530 --> 09:13.230 so they can achieve success and apply your solutions faster? 09:13.230 --> 09:16.290 >> Yeah, so with Generative AI, you know, now that 09:16.290 --> 09:18.570 we're putting in, we're creating applications now 09:18.570 --> 09:21.030 that are non-deterministic in their outputs, right? 09:21.030 --> 09:24.120 So the mechanisms you used to test for that 09:24.120 --> 09:25.350 and evaluate these applications have 09:25.350 --> 09:26.400 completely changed, right? 09:26.400 --> 09:27.900 In the past where you would 09:27.900 --> 09:29.580 otherwise invest in manual testing efforts 09:29.580 --> 09:32.790 or automated testing and with fixed determinism, 09:32.790 --> 09:34.710 now you're looking at non-deterministic outputs 09:34.710 --> 09:37.290 and you're using Generative AI to test Generative AI. 09:37.290 --> 09:38.490 Like, the game is completely different. 09:38.490 --> 09:39.840 So I think investing in tooling, 09:39.840 --> 09:42.720 putting in the right foundation, breaking down data silos 09:42.720 --> 09:45.930 so you have relevant data that you can use 09:45.930 --> 09:47.793 for evaluation is important. 09:47.793 --> 09:50.850 And then beyond that, I think the control functions in any 09:50.850 --> 09:52.980 organizations, particularly in financial institutions, 09:52.980 --> 09:54.450 you know, they can slow things down, right? 09:54.450 --> 09:56.310 So they are bottlenecks 09:56.310 --> 09:58.590 and you can invest in them, you know, 09:58.590 --> 10:01.380 by empowering them with tools, with guidance, 10:01.380 --> 10:03.900 you know, and, you know, making sure that they are ready 10:03.900 --> 10:06.755 to support use cases as they come through. 10:06.755 --> 10:09.120 And we're seeing clients actually start to do that, 10:09.120 --> 10:10.950 where they're, you know, investing in governance 10:10.950 --> 10:12.910 and while at the same time 10:14.150 --> 10:16.050 promoting use cases 10:16.050 --> 10:18.150 that could have a material impact on the business. Yeah. 10:18.150 --> 10:19.710 >> Rebecca: So you have been working together 10:19.710 --> 10:21.480 for a few years now, I'm curious 10:21.480 --> 10:24.846 what do you think about the kinds 10:24.846 --> 10:27.300 of partnerships that you're looking for? 10:27.300 --> 10:29.160 I mean, are there certain characteristics? 10:29.160 --> 10:31.440 Are there certain values that you need 10:31.440 --> 10:32.850 to share a certain commitment 10:32.850 --> 10:35.100 to certain kinds of technologies? 10:35.100 --> 10:37.230 I mean, how do you describe what you look for? 10:37.230 --> 10:39.420 Because I mean, it's a little, it's a relationship 10:39.420 --> 10:41.190 that you, that you need to cultivate. 10:41.190 --> 10:42.930 >> Yeah. So we're focused 10:42.930 --> 10:46.980 on driving outsized outcomes for our clients, right? 10:46.980 --> 10:48.540 So our clients approach us 10:48.540 --> 10:50.310 with challenging business problems. 10:50.310 --> 10:52.422 And in many cases, 10:52.422 --> 10:55.233 and Deloitte does this quite a bit, where, you know, 10:57.101 --> 10:58.440 we're not just paid by the hour, right? 10:58.440 --> 11:01.080 We actually engage in the implementation, 11:01.080 --> 11:05.640 and we sign up to the risks associated to that, right? 11:05.640 --> 11:07.710 And so we share the benefits 11:07.710 --> 11:09.900 and the outcomes in these value-based constructs, right? 11:09.900 --> 11:11.398 So we're doing that a lot more. 11:11.398 --> 11:13.320 And I think what's important to us is 11:13.320 --> 11:15.634 that it's an important strategic problem for the industry, 11:15.634 --> 11:19.327 for the client themselves, potentially for society, 11:19.327 --> 11:22.020 because we also, you know, feel a sense of purpose 11:22.020 --> 11:23.640 and actually helping our clients achieve 11:23.640 --> 11:25.980 these visions are, you know, these lofty goals, right? 11:25.980 --> 11:26.813 So yeah. 11:27.664 --> 11:29.190 >> Would you say there's any sectors 11:29.190 --> 11:31.170 that are lagging behind right now? 11:31.170 --> 11:32.460 I mean, I say this with love, 11:32.460 --> 11:34.470 financial services is not always the front line 11:34.470 --> 11:36.090 to technology adoption. 11:36.090 --> 11:38.160 And so, and obviously you are, 11:38.160 --> 11:40.350 and you consider yourselves leaders. 11:40.350 --> 11:41.550 Are you noticing any trends? 11:41.550 --> 11:43.110 And I mean, I'm even curious from a Canada 11:43.110 --> 11:44.572 to North American perspective 11:44.572 --> 11:48.090 where some folks are either afraid or falling behind 11:48.090 --> 11:50.730 and some industries that are really out in front. 11:50.730 --> 11:55.020 >> That's, yeah, so I think financial services, surprisingly, 11:55.020 --> 11:56.910 at least out of Canada, has been leading the 11:56.910 --> 11:58.710 charge on some of this stuff. 11:58.710 --> 11:59.543 >> Savannah: That's awesome. 11:59.543 --> 12:01.620 Why do you think that is? I'm curious, just to dig in. 12:01.620 --> 12:03.210 >> I think there's tremendous benefits 12:03.210 --> 12:04.830 that can be obtained from the technology 12:04.830 --> 12:06.960 and, you know, there's already business cases 12:06.960 --> 12:09.180 for many existing processes, 12:09.180 --> 12:10.350 and there are for automation, right? 12:10.350 --> 12:12.047 So I think there's an opportunity, 12:12.047 --> 12:14.580 many of them have focused, you know, they've shied away from 12:14.580 --> 12:17.100 customer facing use cases, and that's understandable 12:17.100 --> 12:18.840 because to prove how the technology at scale, 12:18.840 --> 12:21.360 they probably wanted internal facing with employees, 12:21.360 --> 12:22.410 we're seeing that risk posture. 12:22.410 --> 12:24.540 And over time, if I look across the world, 12:24.540 --> 12:26.910 like globally in Europe, there's some companies that are, 12:26.910 --> 12:28.470 you know, putting things in front of customers already. 12:28.470 --> 12:30.003 So we're seeing that shift. 12:30.900 --> 12:32.250 In terms of industries that are lagging, 12:32.250 --> 12:33.390 I think like public sector, 12:33.390 --> 12:36.330 government services, they're a bit slow to procure, 12:36.330 --> 12:37.980 and that's, you know, 12:37.980 --> 12:40.140 but they do understand the value 12:40.140 --> 12:41.460 and they do understand the vision for this. 12:41.460 --> 12:43.560 And I think the scale 12:43.560 --> 12:44.850 of implementations can be a lot larger, 12:44.850 --> 12:45.960 but there's a lot more risks there 12:45.960 --> 12:48.640 because you're dealing with, you know, citizens 12:49.908 --> 12:51.150 and different types of regulations, right? 12:51.150 --> 12:54.180 So any regular industry is slower, consumer, you know, 12:54.180 --> 12:56.910 has been out the gate really, really fast to adopt. 12:56.910 --> 13:00.213 And other technology companies are infusing it throughout. 13:01.877 --> 13:03.540 So there's really no rhyme or reason, 13:03.540 --> 13:06.480 I would say every industry is focused on bringing 13:06.480 --> 13:08.230 Generative AI to their markets 13:09.120 --> 13:10.650 or infusing it in their processes. 13:10.650 --> 13:13.320 There's just, you know, different regulatory hurdles along 13:13.320 --> 13:14.880 the way that some are navigating. 13:14.880 --> 13:18.810 But overall, I feel a sense of optimism across the sectors 13:18.810 --> 13:19.920 about this. Yeah. 13:19.920 --> 13:22.500 >> Well, this, I, the positive energy is emanating, 13:22.500 --> 13:24.870 and as you said, Ron, morale is up 13:24.870 --> 13:27.810 and in general, agents are really excited about the effect 13:27.810 --> 13:30.360 that this is having on their work. 13:30.360 --> 13:33.720 So much of what we hear is that there is some resistance 13:33.720 --> 13:37.350 to AI in the workforce, a nervousness, a skepticism, 13:37.350 --> 13:39.660 a worry about jobs, dislocation. 13:39.660 --> 13:42.810 What are some of the things that you've learned in talking 13:42.810 --> 13:45.390 to your team and talking to your workforce 13:45.390 --> 13:48.780 that you maybe could share, to get more employees on board 13:48.780 --> 13:51.335 or for other industries to hear. 13:51.335 --> 13:52.770 >> Yeah. And I think it's like we touched on, right? 13:52.770 --> 13:54.930 We're taking out the low value piece, right? 13:54.930 --> 13:56.610 For us, we did call summarization, right? 13:56.610 --> 13:58.020 So the wrap up part of 13:58.020 --> 14:00.780 the conversation isn't the most exciting part 14:00.780 --> 14:02.130 of the conversation either for 14:02.130 --> 14:03.630 the agent themselves, right? 14:03.630 --> 14:04.463 The authentication piece. 14:04.463 --> 14:07.200 So again, I think we've taken out the pieces of the job 14:07.200 --> 14:09.780 that probably weren't favorites, if you will. 14:09.780 --> 14:11.490 And again, they serve the benefit 14:11.490 --> 14:13.550 as well from an expense side, right? 14:13.550 --> 14:16.020 Allows us to serve more calls where again, 14:16.020 --> 14:17.820 we're doing this real interaction versus 14:17.820 --> 14:19.161 the precursor to the call. 14:19.161 --> 14:21.000 So I think that's been positive for them. 14:21.000 --> 14:22.800 Again, we're taking out some of the pain points 14:22.800 --> 14:23.850 in their experience. 14:23.850 --> 14:25.500 So again, it's not only about the customer experience, 14:25.500 --> 14:27.960 but also the employee experience in this case. 14:27.960 --> 14:29.753 >> Savannah: Have your customers noticed? 14:30.620 --> 14:33.150 >> I think they'll notice, I think you shared early on 14:33.150 --> 14:34.800 maybe the wait time to calls, right? 14:34.800 --> 14:36.780 So I think there's a benefit from 14:36.780 --> 14:39.690 that side as well on the wrap up side, again, 14:39.690 --> 14:42.180 that part's transparent to the customer, right? 14:42.180 --> 14:44.100 On the authentication side, again, you would notice 14:44.100 --> 14:46.050 that your interaction interacting obviously 14:46.050 --> 14:47.820 with a virtual agent instead of with a human. 14:47.820 --> 14:50.670 But again, the questions are there, right? 14:50.670 --> 14:52.380 It should be a seamless interaction. 14:52.380 --> 14:54.150 It should feel like we're talking like this, 14:54.150 --> 14:55.320 even though it is the bot, right? 14:55.320 --> 14:57.870 So yeah, it's been been positive on both sides, again, 14:57.870 --> 14:59.490 both on the employee experience side, 14:59.490 --> 15:01.110 but as well as the customer side. 15:01.110 --> 15:02.760 >> Yeah, that's awesome to hear. 15:02.760 --> 15:03.900 What are some of the trends 15:03.900 --> 15:05.640 that you're seeing since I didn't get a chance 15:05.640 --> 15:09.090 to ask you in the Canadian AI scene, for example, 15:09.090 --> 15:11.160 we're pretty deeply immersed here on the American side. 15:11.160 --> 15:13.410 We were just over in Paris and in Barcelona as well, 15:13.410 --> 15:15.360 but I can't say we've done a gig in Canada recently. 15:15.360 --> 15:16.440 So what's going on? 15:16.440 --> 15:20.460 What do you and your friends talk about in the space? 15:20.460 --> 15:22.620 >> Probably all the same things as our North American 15:22.620 --> 15:24.149 counterparts and European counterparts. 15:24.149 --> 15:26.280 Yeah. I think it depends what domain you're in, right? 15:26.280 --> 15:28.470 Again, I think in the Gen AI space, what we're hearing 15:28.470 --> 15:30.270 in the peer group, and Annan touched on this, right? 15:30.270 --> 15:32.700 There's a lot of internal POCs, right? 15:32.700 --> 15:34.680 How can we help back office functions? 15:34.680 --> 15:36.930 And you know, I think there's two sides to that, right? 15:36.930 --> 15:39.480 How can we prove that out in a safe and reliable way? 15:39.480 --> 15:40.650 And I think there's tons of opportunity 15:40.650 --> 15:42.300 to improve in that space as well. 15:42.300 --> 15:44.040 So that's what we're talking about again, 15:44.040 --> 15:45.540 within our peer groups mainly. 15:47.280 --> 15:48.833 >> Annan: Yeah, I would say that, 15:50.100 --> 15:51.861 sorry, what was the question again? 15:51.861 --> 15:53.160 >> Well, I was curious about, 15:53.160 --> 15:54.540 'cause I think it's actually, 15:54.540 --> 15:56.490 so I live in the Silicon Valley. 15:56.490 --> 15:58.410 Conversation in the Silicon Valley is very 15:58.410 --> 16:00.600 different than the conversation even in Las Vegas 16:00.600 --> 16:02.640 or in Paris or in Barcelona. 16:02.640 --> 16:05.040 Yeah. So, what's the vibe in Canada? 16:05.040 --> 16:06.972 >> Annan: Yeah, I think there's a lot of, 16:06.972 --> 16:08.083 so you know, we're based on Toronto. 16:08.083 --> 16:09.510 Toronto and you know, Toronto and 16:09.510 --> 16:11.040 Montreal are they're tech hubs. 16:11.040 --> 16:12.655 They're AI centers of the world. 16:12.655 --> 16:15.870 We have a lot of talent and there's a lot of, you know, 16:15.870 --> 16:17.700 work happening in building applications 16:17.700 --> 16:19.260 that leverage this technology. 16:19.260 --> 16:22.650 I think where Canada is lagging behind is in infrastructure, 16:22.650 --> 16:25.320 so in investments in compute, right? 16:25.320 --> 16:28.830 So, you know, bringing GPU capacity to Canada, 16:28.830 --> 16:31.110 recently the Canadian government announced, you know, 16:31.110 --> 16:33.930 over 2 billion in spending to do that, to actually bring 16:33.930 --> 16:36.120 that capacity to Canada. 16:36.120 --> 16:37.170 >> On the hardware side specifically? 16:37.170 --> 16:38.003 >> Annan: On the hardware side. 16:38.003 --> 16:39.270 >> Wow, cool. That's awesome. 16:39.270 --> 16:40.320 >> Yeah. This is like last week. 16:40.320 --> 16:42.000 The Prime Minister announced it. 16:42.000 --> 16:45.090 So I think, you know, there is a realization of this 16:45.090 --> 16:48.250 and there's a desire to catch up with other nations 16:50.070 --> 16:51.600 like from a regulatory perspective. 16:51.600 --> 16:53.430 I think, you know, Canada was first 16:53.430 --> 16:55.950 to have the regulations in place around AI, 16:55.950 --> 16:58.590 or at least proposed, and... 16:58.590 --> 17:00.130 >> Savannah: I did not know that. That's outstanding. 17:00.130 --> 17:02.340 >> Like, they're still not fully ratified. 17:02.340 --> 17:05.220 But I think, you know, there has been thinking 17:05.220 --> 17:08.520 around the potential for AI to disrupt society and jobs 17:08.520 --> 17:13.140 and work in general and, you know, safeguards being 17:13.140 --> 17:14.339 contemplated and discussed, right? 17:14.339 --> 17:16.290 So I think what the government is doing 17:16.290 --> 17:18.089 and kind of what industry is doing is they're putting in 17:18.089 --> 17:19.829 place the right guardrails so 17:19.829 --> 17:22.020 that they can foster an exponential growth 17:22.020 --> 17:23.433 in the technology and use. 17:24.569 --> 17:26.250 As I engage more with clients, 17:26.250 --> 17:28.590 I'm seeing a willingness to buy these technologies, 17:28.590 --> 17:31.503 you know, has gone through the roof since Chat GBT. 17:33.270 --> 17:36.270 >> Savannah: So money is following the hype a little bit. 17:36.270 --> 17:37.680 I mean, you're Deloitte, so I guess 17:37.680 --> 17:39.000 that's probably accurate. 17:39.000 --> 17:41.280 >> Yeah, I guess I would say that, I would say that, 17:41.280 --> 17:44.850 and again, like making sure you have the right use cases 17:44.850 --> 17:47.430 and actually generate real value is critical. 17:47.430 --> 17:50.010 Like we spend a lot of time upfront building business cases 17:50.010 --> 17:52.739 and selecting use cases and refining and measuring 17:52.739 --> 17:54.780 before we even decided what to do. 17:54.780 --> 17:56.430 Right? And that was about a year, 17:56.430 --> 17:57.960 I think we had worked together on that. 17:57.960 --> 17:58.793 >> Savannah: Oh, wow. 17:58.793 --> 18:02.220 >> Yeah. And then you can start picking off the low hanging 18:02.220 --> 18:04.320 fruit from that. Yeah. 18:04.320 --> 18:05.220 >> Ron: As you said earlier, how do you 18:05.220 --> 18:06.750 bring it to realization, right? 18:06.750 --> 18:07.680 How do you make it real, right? 18:07.680 --> 18:09.827 How do we get off that, that hype curve? 18:09.827 --> 18:11.190 >> Yeah. No, it's super exciting. 18:11.190 --> 18:12.750 All right, last question for you gentlemen, 18:12.750 --> 18:15.000 and you don't have to gimme numbers, Ron, I promise. 18:15.000 --> 18:16.230 When we have you back on the show 18:16.230 --> 18:18.750 for another fabulous customer use case story, 18:18.750 --> 18:20.790 what do you hope you can say a year from today 18:20.790 --> 18:21.900 or at the next Google Cloud Next, 18:21.900 --> 18:24.413 whenever it is that you can't quite say yet? 18:24.413 --> 18:25.246 Ron, I'll start with you. 18:25.246 --> 18:26.455 >> Bear with me. 18:26.455 --> 18:29.160 Yeah. I think again, we're looking 18:29.160 --> 18:31.020 to chase this wave just like everyone else, right? 18:31.020 --> 18:33.120 So I think there's tremendous opportunity there 18:33.120 --> 18:34.920 and we're doing the exploration 18:34.920 --> 18:37.080 as an onset across the organization front to back. 18:37.080 --> 18:38.790 So we hope we have more stories 18:38.790 --> 18:39.945 to tell you in different spaces 18:39.945 --> 18:41.820 and maybe share some numbers. 18:41.820 --> 18:43.860 >> Yeah, we love, hey, we're here for that data. 18:43.860 --> 18:45.450 We love that on The Cube. 18:45.450 --> 18:46.283 Annan, what about you? 18:46.283 --> 18:49.384 >> Yeah, so, you know, I'm a geek and I... 18:49.384 --> 18:50.460 >> There's no geeks here. 18:50.460 --> 18:53.250 I don't know, you must feel really out of place. 18:53.250 --> 18:55.170 >> This is like my home. 18:55.170 --> 18:57.060 So I would say the multimodal models 18:57.060 --> 19:00.600 that are coming to market are quite powerful with, 19:00.600 --> 19:02.460 you know, million context length windows. 19:02.460 --> 19:06.840 Like, I think just very novel experiences 19:06.840 --> 19:08.460 that we can drive with customers is 19:08.460 --> 19:09.570 something I'm really looking forward to. 19:09.570 --> 19:11.760 So beyond just like simple functions 19:11.760 --> 19:16.440 or automation, it's like net new capabilities, experiences, 19:16.440 --> 19:18.870 products, I hope to be, you know, be back here 19:18.870 --> 19:21.090 to share a story about something like that. Yeah. 19:21.090 --> 19:23.340 >> That'd be great. The future is bright. 19:23.340 --> 19:25.590 Annan and Ron, thank you so much for being here with us 19:25.590 --> 19:28.080 on the show. This was a fantastic chat. 19:28.080 --> 19:29.580 Rebecca, always a pleasure. 19:29.580 --> 19:31.710 And thank all of you for tuning in from wherever you are 19:31.710 --> 19:34.170 on this beautiful rock to our fabulous three days 19:34.170 --> 19:36.930 of coverage at Google Cloud Next here in Las Vegas, Nevada. 19:36.930 --> 19:39.210 My name's Savannah Peterson, you're watching The Cube, 19:39.210 --> 19:41.613 the leading source for enterprise tech news.