 Good afternoon, nerd fam, and welcome back to Las Vegas, Nevada. We're midway through day one of Google Cloud Next here. My name's Savannah Peterson, joined by my brilliant co-host, Rebecca Knight. Rebecca, how are you doing this afternoon? I am very good, Savannah. Gen AI is the topic du jour. We cannot get enough of it here on theCUBE. Du jour, du week, do everything I think at this point. Yes. It's true, it's true. And one of the most salient places that Gen AI is having a lot of benefits is in the call center. And that's what leads us to talk to our next guest. I know, very excited to have Anand and Ron here with us to talk about Gen AI. We've got two Canadians in the house. How's the show going for you so far? Yeah, it's great. We're loving the weather. Yeah. I can imagine. So, Ron, just in case folks are not familiar, give us a little background on DFINITY. Yeah, so DFINITY is a Canadian based P&C insurance company. We offer traditional lines, digital, pet insurance, commercial insurance. So wide spectrum of products. That's awesome. And you have a very unique title as chief architect of Gen AI at Deloitte. I'm curious actually, just before we dig in, how long have you had that? How long has that role existed at Deloitte? Let's start there. It's been about a year actually. Yes, so fresh. And tell us what your day to day is like. So I work with clients to do Gen AI based implementations. Many of them on Google. And we're looking at solving very challenging business problems. So it's a problem where we need to leverage AI to either re-engineer processes, or whether it's process efficiency or maybe generating new revenue through marketing or other channels. So it's an exciting space. We're learning more about the tech every day. And it's evolving. Just the announcements today in the keynote. Like I'm learning a lot about what's coming and we're really excited about it too, so. We're really excited to have you on it because we love customer stories here because there's so much talk about the technology, the TCUs, the PCUs. But we want to know really how our company's using this technology to improve the workflows for their employees, but also improve the experiences for their customers. So DFINITY went live with the Contact Center at the end of 2023. Can you give, why don't you start from the beginning about what was the impetus for this project? Yeah, well I think you touched on it, right? How do we improve the customer experience? How do we improve the employee experience? Leveraging some of the new technology that's in market. So some of the things we looked at, what were the long pulls in those experiences or in that journey? And a lot of it having to do with call wrap up, having to do with authentication, right? So what are things that are taking a lot of time from an agent's perspective, but not adding a lot of value? And then working with partners like Deloitte, starting to build out what that solution could look like and how we can drive more efficiencies. How long have you two been working together? I don't know, is it two to three years now? Yeah, yeah. And what's the advantage for you as a customer working with Deloitte? Yeah, I think for us, we want to go fast, we want to go far, but we know to do that, we can't do it alone, right? And so partnering with folks like Deloitte, folks like Google really brings that relationship to fruition and we're able to take up new concepts like CCAI and some of the cool things we saw in the keynote today. So yeah, I think it's really about leveraging that expertise that's in market, but also then bringing it home with our team as well. So going back to the impetus for the project, what were the pain points that you were seeing, both for the agents and also for the customers? Yeah, I think Call Center has call variability. We've all been on, we've all dealt with it. So being able to manage the scaling or the volatility in call demands is a big thing for us, right? So how can we drive more efficiency away from the call agent, right? So when you actually want to reach someone, you want to have that person-to-person conversation, not be waiting in the queue because someone's doing authentication or because the agent's trying to wrap up the call, right? So we tried to take out some of those low-value interactions so we can have more high-value face-to-face, but person-to-person interactions. Well, you wanted to feel face-to-face. Yeah, absolutely. You wanted to feel that person-to-person. So I don't think there's anything wrong with that. Anand, I'm curious, you see a lot of different customers and across verticals. I can imagine you're a very popular person these days within the organization. You're having a bit of a moment, if you will. What are some of the trends that you're seeing in general? Is everyone kind of in a similar place across verticals? Are there some categories and spaces that you're seeing run ahead perhaps because of their agility or maybe even smaller size? Yeah, so I see a lot of opportunity, many of our clients, especially in financial services, are focused on knowledge retrieval or removing information disparity in our organization. They want employees to have access to information, they're instantly relevant to their context so that they can just move on with whatever task they're doing and actually produce more at the end of the day. In the call center, this shows up in a very interesting way. Agents, when they're on a call with a customer, they're often navigating multiple applications. The most I've ever seen in one flow was over 30 applications that an agent had to do to execute an interaction. So if you can remove some of that through automation, through generative AI, moving from the front office into the back office, doing some of that straight through processing with generative AI, we're seeing customers experiment with that and also leveraging information retrieval and knowledge retrieval throughout that journey. And where are they in this phase? Because I mean, one of the things that has really come through, at least in the keynote, is that we've gone from, it was about a year and a half when ChatGBT was unleashed into the world to here we are today where companies really are just going from, oh wow, here's this new bright, shiny toy too, let's really integrate this into our systems. Where do you think companies are in their journey? Yeah, so I'd say the past year, or at least in 2023, there was a focus on POCs. A lot of companies were like, here's this new hammer and what are all the possible things we can do with it? And this year the focus is really about moving from POCs into production. A lot of companies are looking at low value, high volume processes and looking to re-engineer them from the ground up with generative AI and they're building business cases usually based on either cost savings you do, improvement of utilization of talent, or maybe new capabilities that they want to enable, new products that they want to enable with this technology. So there's a huge push around impactful, focus deployments of generative AI that then you can build as a foundation upon which you can scale. And ultimately I think the future operating model for an organization is one where you have AI agents like we saw today at the keynote interacting with humans in a kind of collaboration. So a request coming in, going through a collaboration of orchestration of that. And so over the next few years, I think we're going to see a lot of new capabilities, new entrance into existing long-standing industries where there's incumbents, just trying to come to market with new processes. Yeah. What are some of the challenges there? I mean you just described that as a very smooth process which given that you're consultant is sort of the name of the game. But I mean, there's obviously, there's best practices and there's a great way to do this. What's your advice to folks? I mean, and actually, Ron, I'll turn this to you first. To companies who are embarking on this journey, we're all still in kind of the sandbox stage. How do they get to that at scale moment of realization like you've achieved? Yeah, I think maybe if we take a step back for us, it was even what preceded this, right? And so we had just gone through our data transformation journey which allowed us to be ready for this. So the timing was great, we had just moved to cloud, moved our data platforms to cloud, made the data available for these types of programs. Then I think it's really about finding your right risk tolerance, right? What's your organizational risk appetite? Do you want to do something that's internal facing, that's lower risk? Do you want to do something similar to maybe what we did which was, again, not directly interacting with the customer from that sense of kind of respond and response? Yeah, I think that's key, right? Just figure out where your comfort zone is and then the opportunity, like I said, for us is really driving out that talk time, right? The call time, how can we reduce that and reduce the pain points that come along with longer talk times? How does your team feel? How has your team responded to that adjustment? Are people, do you feel like morale is up? So I think people are excited for sure. Like you said, this is the talk of the town, right? So it's excited to be operating in this space. We tend to think of ourselves as a leading organization in a digital space, so absolutely. So it brings that empowerment to the team that we're not reading about, but we're actually doing it as well. No, it's, we've been talking about it on the show, 2024, the year of making AI real. Not just this hype stage that we're obviously peaking in right now, big time. On your side, what would be your, what's your advice to folks? Or what are the risks you would like to see them avoid so they can achieve success and apply your solutions faster? Yeah, so with Generative AI, now that we're putting in, we're creating applications now that are non-deterministic in their outputs, right? So the mechanisms you use to test for that and evaluate these applications have completely changed, right? In the past where you would otherwise investing manual testing efforts or automated testing in a fixed, what's fixed determinism, now you're looking at non-deterministic outputs and you're using Generative AI to test Generative AI. Like the game is completely different. So I think investing in tooling, putting in the right foundation, breaking down data silos so you have relevant data that you can use for evaluation is important. And then beyond that, I think the control functions in any organizations, particularly in financial institutions, they can slow things down, right? So they are bottlenecks and you can invest in them by empowering them with tools, with guidance, and making sure that they are ready to support use cases as they come through. And we're seeing clients actually start to do that where they're investing in governance and while at the same time promoting use cases I could have a material impact on the business. Yeah. So you have been working together for a few years now. I'm curious Anand, what do you think about the kinds of partnerships that you're looking for? I mean, are there certain characteristics, are there certain values that you need to share, certain commitment to certain kinds of technologies? I mean, how do you describe what you look for? Because I mean, it's a little, it's a relationship that you need to cultivate. Yeah. So we're focused on driving outsized outcomes for our clients, right? So our clients approach us with challenging business problems and in many cases, and Deloitte does this quite a bit, where we're not just, we're not just paid by the hour, right? We actually engage in the implementation and we sign up to the risks associated to that, right? And so we share in the benefits and the outcomes in these value-based constructs, right? So we're doing that a lot more. And I think what's important to us is that it's an important strategic problem for the industry, for the client themselves, potentially for society, because we also feel a sense of purpose in actually helping our clients achieve these visions or these lofty goals, right? So, yeah. Would you say there's any sectors that are lagging behind right now? I mean, I say this with love, financial services is not always the frontline to technology adoption. And so, and obviously you are, and you consider yourselves leaders, are you noticing any trends? And I mean, I may have been curious from a Canada to North American perspective, where some folks are either afraid or falling behind in some industries that are really out in front. That's, yeah. So I think financial services, surprisingly, at least out of Canada, has been leading the charge on some of this stuff. That's awesome. Why do you think that is? I'm curious just to dig in. I think there's tremendous benefits that can be obtained from the technology and there are already business cases for many existing processes and they're for automation, right? So I think there's an opportunity. Many of them have focused, they've shied away from customer facing use cases and that's understandable because to prove out the technology at scale, they probably wanted internal facing with employees. We're seeing that risk posture and over time, if I look across the world, like globally in Europe, there's some companies that are putting things in front of customers already. So we're seeing that shift. In terms of industries that are lagging, I think like public sector government services, they're a bit slow to procure and that's, you know, but they do understand the value and they do understand the vision for this and I think the scale of implementations can be a lot larger, but there's a lot more risks there because you're dealing with, you know, citizens and different types of regulations, right? So any regulated industry is slower. Consumer, you know, has been at the gate really fast to adopt and other technology companies are infusing it throughout. So there's really no rhyme or reason. I would say every industry is focused on bringing generative AI to their markets and or infusing it in their processes. There's just, you know, different regulatory hurdles along the way that some are navigating, but overall I feel a sense of optimism across the sectors about this, yeah. Well, the positive energy is emanating and as you said, Ron, morale is up and in general agents are really excited about the effect that this is having on their work. So much of what we hear is that there is some resistance to AI in the workforce, a nervousness, a skepticism, a worry about jobs dislocation. What are some of the things that you've learned in talking to your team and talking to your workforce that you maybe could share to get more employees on board or for other industries to hear? Yeah, and I think it's like we touched on, right? We're taking out the low value piece, right? For us we did call summarization, right? So the wrap up part of the conversation isn't the most exciting part of the conversation either for the agent themselves, right? The authentication piece. So again, I think we've taken out the pieces of the job that probably weren't favorites, if you will. And again, they serve the benefit as well from an expense side, right? Allows us to serve more calls where again, we're doing this real interaction versus the precursor to the call. So I think that's been positive for them again. We're taking out some of the pain points in their experience. So again, it's not only about the customer experience but also the employee experience in this case. Right, right. Have your customers noticed? I think they'll notice, I think you shared early on maybe the wait time to calls, right? Yeah, yeah. I think there's a benefit from that side as well. On the wrap up side again, that part's transparent to the customer, right? On the authentication side, again, you would notice that your interaction, interacting obviously with a virtual agent instead of with a human. But again, the questions are there, right? It should be a seamless interaction. It should feel like we're talking like this even though it is the bot, right? So yeah, it's been positive on both sides. Again, both on the employee experience side but as well as the customer side. Yeah, that's awesome here. What are some of the trends that you're seeing since I didn't get a chance to ask you in the Canadian AI scene, for example. We're pretty deeply immersed here on the American side. We were just over in Paris and in Barcelona as well. But I can't say we've done a gig in Canada recently. So what's going on? What do you and your friends talk about in the space? Probably all the same things as our North American counterparts and European counterparts. Yeah, I think it depends what domain you're in, right? Again, I think in the Gen AI space, what we're hearing in the peer group and I'm not in touch on this, right? There's a lot of internal POCs, right? How can we help back off as functions? And I think there's two sides there, right? How can we prove that out in a safe and reliable way? And I think there's tons of opportunity to improve in that space as well. So that's what we're talking about again within our peer groups mainly. Yeah, I'd say that, sorry, what was the question again? Well, I was curious about, because I think it's actually, so I live in the Silicon Valley. Conversation in the Silicon Valley is very different than the conversation even in Las Vegas or in Paris or in Barcelona. Yeah, so what's the vibe in Canada? Yeah, I think there's a lot of, so we're based on Toronto, and Toronto Montreal are tech hubs, they're AI centers of the world. We have a lot of talent and there's a lot of work happening in building applications that leverage this technology. I think where Canada is lagging behind is in infrastructure. So in investments in compute, right? So bringing GPU capacity to Canada, recently the Canadian government announced over two billion in spending to do that, to actually bring that capacity to Canada. On the hardware side specifically, on the chipsets, wow, cool, that's awesome. Yeah, this is like last week, the Prime Minister announced it. So I think there is a realization of this and there's a desire to catch up with other nations. From a regulatory perspective, I think Canada was first to have the regulations in place around AI, or at least proposed. I did not know that, that's outstanding. They're still not fully ratified, but I think there has been thinking around the potential for AI to disrupt society and jobs and work in general, and safeguards being contemplated and discussed. So I think what the government is doing and what industry is doing is they're putting in place the right guardrails so that they can foster an exponential growth in the technology and use. As I engage more with clients, I'm seeing a willingness to buy these technologies, has gone through the roof since chat, GBT. Ooh. Yeah, and- So the money is following the hype a little bit. Yeah. I mean, you're Deloitte, so I guess that's probably accurate. Yeah, I guess. I would say that, and again, making sure you have the right use cases and actually generate real value is critical. We spent a lot of time up front building business cases and selecting use cases and refining and measuring before we even decided what to do, right? And that was about a year, I think we had worked together on that. Oh, wow. And then you can start picking off the low-hanging fruit from that, yeah. There, as you said earlier, how do you bring it to realization, right? How do you make it real, right? How do we get off that hype curve, yeah. Yeah, no, it's super exciting. All right, last question for you gentlemen, and you don't have to give me numbers, Ron, I promise. When we have you back on the show for another fabulous customer use case story, what do you hope you can say a year from today or at the next Google Cloud Next whenever it is that you can't quite say yet? Ron, I'll start with you. There with me. Yeah, I think, again, we're looking to chase this wave just like everyone else, right? So I think there's tremendous opportunity there and we're doing the exploration as a non-set across the organization front to back. So we hope we have more stories to tell you in different spaces and maybe share some numbers. Yeah, we'd like, hey, we're here for that data. We love that on the Cube. Anand, what about you? Yeah, so, you know, I'm a geek and I... There's no geeks here. I don't know, you must feel really out of place. This is like my home. So I would say the multimodal models that are coming to market are quite powerful with, you know, a million context-length windows. Like, I think just very novel experiences that we can drive with customers is something that I'm really looking forward to. So beyond just like simple functions or automation, it's like net new capabilities, experiences, products. I hope to be, you know, be back here to share a story about something like that, yeah. Yeah, the future is bright. Anand and Ron, thank you so much for being here with us on the show. This was a fantastic chat. Rebecca, always a pleasure. I thank all of you for tuning in from wherever you are on this beautiful rock. To our fabulous three days of coverage at Google Cloud Next here in Las Vegas, Nevada, my name's Savannah Peterson. You're watching the Cube, the leading source for enterprise tech news.