Google Cloud Next '24 | Ron Mills | Definity & Anand Nimkar | Deloitte

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Ron Mills

VP of APIs, Data Platforms & Infrastructure

Definity

Anand Nimkar

Generative AI Practice Leader

Deloitte

Definity seeks to streamline call center operations with generative AI

Generative artificial intelligence continues to capture interest and was a major highlight at last week’s Google Cloud Next event. It’s influencing a wide range of industries, including in the contact center.At Definity Financial Corp., the technology is making a big impact. It involves working with clients to do gen AI-based implementations, many of them on Google, according to Ron Mills (pictured, left), vice president of API, data platforms and infrastructure, and cloud at Definity.“Being able to manage the scaling or the volatility in call demands is a big thing for us,” Mills said

play_circle_outline Definity: A Comprehensive Overview of the Canadian-based Insurance Company and Introduction to Gen AI at Deloitte

play_circle_outline Revolutionizing Business Processes and Enhancing Customer Experiences through AI and Gen AI in Call Centers

play_circle_outline Trends and challenges in the adoption of Generative AI in various industries

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Ron Mills | Definity & Anand Nimkar | Deloitte

Ron Mills

VP of APIs, Data Platforms & Infrastructure Definity

Anand Nimkar

Generative AI Practice Leader Deloitte

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>> 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 The Cube.

>> Yes, du jour. Do we do everything? I think at this point, yes.

>> 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 an nun 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.

>> Savannah: I can imagine. So Ron, just in case folks are not familiar, give us a little background on Definity.

>> Yeah, so Definity is a Canadian based PT insurance company. We offer traditional lines, digital, pet insurance, commercial insurance, so wide spectrum of products.

>> Savannah: 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.

>> Yeah. 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, you know, we need to leverage AI to either re-engineer processes or, you know, whether it's process efficiency or maybe generating new revenue through marketing or other channels. So, you know, it's an exciting space. We're learning more about the tech every day, and it's evolving, you know, 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, yeah.

>> Well, we're really excited to have you on 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 are companies using this technology to improve the workflows for their employees, but also improve the experiences for their customers. So Definity 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 are what were the long poles 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 a 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 would say two, three years now. Yeah.

>> 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, you know, really brings that relationship to fruition and we're able to take up new concepts like CCAI Yeah. 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.

>> Yeah.

>> 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.

>> Savannah: Well, you want it to feel face to face. You want it to feel that personable. I don't think there's anything wrong with that. And I'm curious, you see a lot of different customers and across verticals, I can imagine you're a very popular person these days. Yeah, absolutely. 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, they're focused on knowledge retrieval or, you know, removing information disparity in our organization. They want employees to have access to information instantly relevant to their context so that they can just move on with whatever tasks they're doing and actually produce more. At the end of the day in the call center, that shows up in a very interesting way. You know, agents, when they're on a call with a customer, they're often, you know, navigating multiple applications. The most I've ever seen in one flow was like over 30 applications that an agent had to do to execute an interaction, right? 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, you know, we're seeing customers experiment with that and also leveraging information retrieval and knowledge retrieval throughout that journey.

>> Rebecca: 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, you know, it was about a year and a half when Chat GPT was unleashed into the world, to here we are today, where companies really are just go going from, oh wow, here's this new bright, shiny toy to 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, you know, 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 due do improvement of utilization of talent, or, you know, other 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, you know, focused 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, the keynote interacting with humans, you know, in a collaboration, you know, so request coming in, going through a collaboration or orchestration of that. And so over the next few years, and you know, I think we're going to see a lot of new capabilities, new entrants into existing longstanding industries where there's incumbents, right? Just trying to, you know, 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 a consultant is sort of the name of the game. But, I mean, there is 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, 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?

>> I think 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 the leading organization and in the 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.

>> Oh, 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'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, you know, now that we're putting in, we're creating applications now that are non-deterministic in their outputs, right? So the mechanisms you used to test for that and evaluate these applications have completely changed, right? In the past where you would otherwise invest in manual testing efforts or automated testing and with 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, you know, they can slow things down, right? So they are bottlenecks and you can invest in them, you know, by empowering them with tools, with guidance, you know, and, you know, 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, you know, investing in governance and while at the same time promoting use cases that could have a material impact on the business. Yeah.

>> Rebecca: So you have been working together for a few years now, I'm curious 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 a 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, 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, you know, 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 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, you know, feel a sense of purpose and actually helping our clients achieve these visions are, you know, 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 front line to technology adoption. And so, and obviously you are, and you consider yourselves leaders. Are you noticing any trends? And I mean, I'm even curious from a Canada to North American perspective where some folks are either afraid or falling behind and 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.

>> Savannah: 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, you know, there's already business cases for many existing processes, and there are for automation, right? So I think there's an opportunity, many of them have focused, you know, they've shied away from customer facing use cases, and that's understandable because to prove how 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, you know, 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 regular industry is slower, consumer, you know, has been out the gate really, 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 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, this, I, 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.

>> Savannah: Have your customers noticed?

>> I think they'll notice, I think you shared early on maybe the wait time to calls, right? So 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 been positive on both sides, again, both on the employee experience side, but as well as the customer side.

>> Yeah, that's awesome to hear. 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 Annan touched on this, right? There's a lot of internal POCs, right? How can we help back office functions? And you know, I think there's two sides to that, 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.

>> Annan: Yeah, I would say that, sorry, what was the question again?

>> Well, I was curious about, 'cause 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?

>> Annan: Yeah, I think there's a lot of, so you know, we're based on Toronto. Toronto and you know, Toronto and Montreal are they're tech hubs. They're AI centers of the world. We have a lot of talent and there's a lot of, you know, 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, you know, bringing GPU capacity to Canada, recently the Canadian government announced, you know, over 2 billion in spending to do that, to actually bring that capacity to Canada.

>> On the hardware side specifically?

>> Annan: On the hardware side.

>> Wow, cool. That's awesome.

>> Yeah. This is like last week. The Prime Minister announced it. So I think, you know, there is a realization of this and there's a desire to catch up with other nations like from a regulatory perspective. I think, you know, Canada was first to have the regulations in place around AI, or at least proposed, and...

>> Savannah: I did not know that. That's outstanding.

>> Like, they're still not fully ratified. But I think, you know, there has been thinking around the potential for AI to disrupt society and jobs and work in general and, you know, safeguards being contemplated and discussed, right? So I think what the government is doing and kind of 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, you know, has gone through the roof since Chat GBT.

>> Savannah: So money is following the hype a little bit. I mean, you're Deloitte, so I guess that's probably accurate.

>> Yeah, I guess I would say that, I would say that, and again, like making sure you have the right use cases and actually generate real value is critical. Like we spend a lot of time upfront 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.

>> Savannah: Oh, wow.

>> Yeah. And then you can start picking off the low hanging fruit from that. Yeah.

>> Ron: 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, that hype curve?

>> Yeah. No, it's super exciting. All right, last question for you gentlemen, and you don't have to gimme 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.

>> Bear 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 an onset 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 love, hey, we're here for that data. We love that on The Cube. Annan, 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, million context length windows. Like, I think just very novel experiences that we can drive with customers is something 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.

>> That'd be great. The future is bright. Annan and Ron, thank you so much for being here with us on the show. This was a fantastic chat. Rebecca, always a pleasure. And 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.

Ron Mills | Definity & Anand Nimkar | Deloitte

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>> 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 The Cube.

>> Yes, du jour. Do we do everything? I think at this point, yes.

>> 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 an nun 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.

>> Savannah: I can imagine. So Ron, just in case folks are not familiar, give us a little background on Definity.

>> Yeah, so Definity is a Canadian based PT insurance company. We offer traditional lines, digital, pet insurance, commercial insurance, so wide spectrum of products.

>> Savannah: 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.

>> Yeah. 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, you know, we need to leverage AI to either re-engineer processes or, you know, whether it's process efficiency or maybe generating new revenue through marketing or other channels. So, you know, it's an exciting space. We're learning more about the tech every day, and it's evolving, you know, 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, yeah.

>> Well, we're really excited to have you on 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 are companies using this technology to improve the workflows for their employees, but also improve the experiences for their customers. So Definity 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 are what were the long poles 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 a 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 would say two, three years now. Yeah.

>> 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, you know, really brings that relationship to fruition and we're able to take up new concepts like CCAI Yeah. 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.

>> Yeah.

>> 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.

>> Savannah: Well, you want it to feel face to face. You want it to feel that personable. I don't think there's anything wrong with that. And I'm curious, you see a lot of different customers and across verticals, I can imagine you're a very popular person these days. Yeah, absolutely. 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, they're focused on knowledge retrieval or, you know, removing information disparity in our organization. They want employees to have access to information instantly relevant to their context so that they can just move on with whatever tasks they're doing and actually produce more. At the end of the day in the call center, that shows up in a very interesting way. You know, agents, when they're on a call with a customer, they're often, you know, navigating multiple applications. The most I've ever seen in one flow was like over 30 applications that an agent had to do to execute an interaction, right? 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, you know, we're seeing customers experiment with that and also leveraging information retrieval and knowledge retrieval throughout that journey.

>> Rebecca: 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, you know, it was about a year and a half when Chat GPT was unleashed into the world, to here we are today, where companies really are just go going from, oh wow, here's this new bright, shiny toy to 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, you know, 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 due do improvement of utilization of talent, or, you know, other 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, you know, focused 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, the keynote interacting with humans, you know, in a collaboration, you know, so request coming in, going through a collaboration or orchestration of that. And so over the next few years, and you know, I think we're going to see a lot of new capabilities, new entrants into existing longstanding industries where there's incumbents, right? Just trying to, you know, 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 a consultant is sort of the name of the game. But, I mean, there is 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, 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?

>> I think 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 the leading organization and in the 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.

>> Oh, 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'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, you know, now that we're putting in, we're creating applications now that are non-deterministic in their outputs, right? So the mechanisms you used to test for that and evaluate these applications have completely changed, right? In the past where you would otherwise invest in manual testing efforts or automated testing and with 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, you know, they can slow things down, right? So they are bottlenecks and you can invest in them, you know, by empowering them with tools, with guidance, you know, and, you know, 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, you know, investing in governance and while at the same time promoting use cases that could have a material impact on the business. Yeah.

>> Rebecca: So you have been working together for a few years now, I'm curious 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 a 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, 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, you know, 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 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, you know, feel a sense of purpose and actually helping our clients achieve these visions are, you know, 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 front line to technology adoption. And so, and obviously you are, and you consider yourselves leaders. Are you noticing any trends? And I mean, I'm even curious from a Canada to North American perspective where some folks are either afraid or falling behind and 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.

>> Savannah: 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, you know, there's already business cases for many existing processes, and there are for automation, right? So I think there's an opportunity, many of them have focused, you know, they've shied away from customer facing use cases, and that's understandable because to prove how 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, you know, 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 regular industry is slower, consumer, you know, has been out the gate really, 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 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, this, I, 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.

>> Savannah: Have your customers noticed?

>> I think they'll notice, I think you shared early on maybe the wait time to calls, right? So 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 been positive on both sides, again, both on the employee experience side, but as well as the customer side.

>> Yeah, that's awesome to hear. 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 Annan touched on this, right? There's a lot of internal POCs, right? How can we help back office functions? And you know, I think there's two sides to that, 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.

>> Annan: Yeah, I would say that, sorry, what was the question again?

>> Well, I was curious about, 'cause 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?

>> Annan: Yeah, I think there's a lot of, so you know, we're based on Toronto. Toronto and you know, Toronto and Montreal are they're tech hubs. They're AI centers of the world. We have a lot of talent and there's a lot of, you know, 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, you know, bringing GPU capacity to Canada, recently the Canadian government announced, you know, over 2 billion in spending to do that, to actually bring that capacity to Canada.

>> On the hardware side specifically?

>> Annan: On the hardware side.

>> Wow, cool. That's awesome.

>> Yeah. This is like last week. The Prime Minister announced it. So I think, you know, there is a realization of this and there's a desire to catch up with other nations like from a regulatory perspective. I think, you know, Canada was first to have the regulations in place around AI, or at least proposed, and...

>> Savannah: I did not know that. That's outstanding.

>> Like, they're still not fully ratified. But I think, you know, there has been thinking around the potential for AI to disrupt society and jobs and work in general and, you know, safeguards being contemplated and discussed, right? So I think what the government is doing and kind of 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, you know, has gone through the roof since Chat GBT.

>> Savannah: So money is following the hype a little bit. I mean, you're Deloitte, so I guess that's probably accurate.

>> Yeah, I guess I would say that, I would say that, and again, like making sure you have the right use cases and actually generate real value is critical. Like we spend a lot of time upfront 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.

>> Savannah: Oh, wow.

>> Yeah. And then you can start picking off the low hanging fruit from that. Yeah.

>> Ron: 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, that hype curve?

>> Yeah. No, it's super exciting. All right, last question for you gentlemen, and you don't have to gimme 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.

>> Bear 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 an onset 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 love, hey, we're here for that data. We love that on The Cube. Annan, 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, million context length windows. Like, I think just very novel experiences that we can drive with customers is something 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.

>> That'd be great. The future is bright. Annan and Ron, thank you so much for being here with us on the show. This was a fantastic chat. Rebecca, always a pleasure. And 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.