 Hello. Hey. Let's try that again. Hello. OK, thanks for joining our session. So today, Andrew and I will be talking about conversational AI. So first, I guess it would make sense to introduce ourselves and explain why we are in the position of talking about it. So my name is Ilya. I'm a product lead at Google. And I kind of like doing two things there. So one is, so I joined Google about a year and a half ago when my company was acquired. Company name is API AI. And we renamed it to Dialogflow. So Dialogflow is a platform for building conversational interfaces for Google Assistant and also other platforms. So our users are building like Assistant apps, Facebook bots, Slack bots, and conversational agents for other platforms. And also, I'm in charge for startup ecosystem development with Google Assistant. So basically, working with startups that are building interesting applications for conversational use cases. Andrew? Hi, my name is Andrew McCraith. I'm responsible for corporate development at Converseca. Converseca is the global leader in conversational AI for business. And we face a great problem, which is that we're growing very fast. And my role is to help us make sure that as we grow and expand, we don't get ahead of ourselves and we do it successfully. And one of the biggest challenges as we grow is recognizing that the new segments we get into, whether they're new business functions, new geographies, new cultures and languages, that we understand the nuances of those different opportunities. And that's key to the success of conversational AI is recognizing that not every conversation is the same. And we need to have one solution that can recognize those differences, put that all in context, and still have a very successful conversation. So now that we know what conversational AI is and why we're the experts to speak to you about it, one of the real benefits of conversational AI is that it can take over doing the non-value add very repetitive aspects of a conversation. So 30% of business people spend their time in email. And a large portion of that is doing repetitive tasks like scheduling a meeting, following up with someone. And so conversational AI can help you address those issues and actually make you more productive in your job. So Ilya, on the side that you're involved with, where do you see the benefits of conversational AI? Yeah, I mean, I guess we are kind of like looking at conversational AI from different angles a little bit. So my main focus is from consumers. And the way we think about conversational AI is that, well, there are two things. There is the conversational and AI here. And so there is an AI that helps you manage conversation. So basically understanding user intent, managing dialogue, like generating personalized answers and things like this. And then there is the AI part, which is more of a decision making and deciding when is the best time to start this conversation, let's say, right? So our focus, especially in Dialogflow at Google, is on the interface part, right? So we are basically considering it as an additional interface to existing services. It's not about just building AI from scratch. It's rather, if you have a great service, why not add a conversational interface to it? So speaking of benefits here, it's, so obviously it is the most natural way of communicating with people. Like people are talking to each other for like thousands and thousands of years. And with the growth of the technological services, like number of those and noise around it, it kind of is becoming really necessary to provide people with easy interfaces to get things done and to be informed when they have to be informed, not to check your Twitter and email and Facebook like every other minute. And this is like a huge benefit. So basically we're allowing people to get their life back and focus on important stuff. But I guess the angle may be a little different if it is, we are talking about enterprise use cases. So and like, well, what I hear here and there is that like actually people will start like losing jobs because of the AI. Because like, well, many of the functions could be like replaced. So what's your take on it? And that is a common fear. AI is an automation technology. Automation, it means jobs are going away. And what we found is it's actually quite the opposite. So Salesforce is one of our big partners being a sales automation company. And they were worried about losing licenses because our customers would automate the sales process. And what they found out was of all the companies they surveyed using Converseca, zero had reduced their number of Salesforce licenses. 80% had actually increased their Salesforce licenses. And the reason for that is we were taking away part of the process, but that enabled people to do what people do best, which was to sell in the case of a sales assistant. And not only were we helping them spend their time selling, we were helping them generate even more leads. So they needed even more people to help. So what we're really seeing is a shift. There's maybe net positive jobs, but it's a shift from the cold calling inside sales type work, which is a high churn position. It's not what people do best to the more value add sales executive account selling type roles. And that's what we expect to continue to see happening as we look at conversational AI is all those business conversations that happen, whether they're between companies and their customers, companies and their employees, companies and their suppliers, those conversations will be automated. And that's kind of where conversational AI is going is continuing to enable more and more of those business interactions to be automated. And that's gonna open up all sorts of new ways of doing business, ways of relating with your employees and your suppliers. And also seeing how all those different assistants work together. What are some of the places where you see the future of conversational AI as these ecosystems continue to grow? Well, I think one of the, like there may be multiple paths to the future of conversational AI. Like at the end of the day, obviously, like on consumer side, we will all have assistants that help us. So the question is like, what form will they be? So would it be, you know, like my personal assistant that cares about my needs, that knows me best and tries to anticipate what needs I may have and is able to answer any questions or it could be like brand assistants where you are basically talking to each and every brand separately, for example. Or I mean, my view is like, well, probably it will be like a combination, right? But in general, again, because we are considering conversational UX as just part of, like as an addition to existing services, well, we are adding this layer that knows you, that understands what you want. That is like much more natural. So, and the future is basically like, well, this assistant's becoming like, well, get into a quality level where you basically do not need like, not like, well, you may need other types of interfaces, but for most of your like daily tasks, if you just think of like a real human assistant, they have to be like same capable, right? So, I mean, obviously they, you will not, you know, like draw like some paintings with like a conversational assistant. But for any routine tasks, well, I believe that is, that's definitely like, well, what will be, will be happening. So, what do you think of like the enterprise picture for it? Yeah, so, enterprise is a fastening place because it has a different set of challenges. And the two big ones that stand out are, we're trying to reach out and engage the target. The target hasn't necessarily started that conversation. We're asking the question and that's a different challenge from a technology standpoint. You need to know what's the right question to ask, when's the right time to ask it, and what's the best way to ask it. And that's different for each person you're trying to reach. So, as we continue to get better and better with the technology, we can start to make that a much more personalized assistant. So, right now, most enterprises, they think of having an assistant for each one of their salespeople. And we see the future as we can have an assistant for each one of our customers or for each one of our employees or each one of our suppliers because they each interact and engage in a different way. And that's one of the challenges is how do you build into your system a way to recognize all those different subtleties? So, the way an executive interacts is different maybe than an entry level position. Maybe there's a different dialect in different parts of the country. Maybe someone prefers to engage with a female assistant or a male assistant. Do they want someone who's very stern and aggressive in their style or very laid back and relaxed? And so, all those different nuances and different personalities takes time to build up a data set that can be very precise. And then the other part is to get the most out of an assistant, whether it's for business, consumer, and any application, you need to integrate with systems. The more systems you integrate with, the more valuable data you can bring to the conversation, both to contextualize it, but also to make it beneficial in both directions. A lot of our business conversations, people share information that's really valuable, but we don't have a place to store it today. Being able to integrate with more and more systems will help that become a richer, more valuable experience. And it also accelerates the time to pay back. So as an enterprise, return on investment is very important. And the faster we can deploy, and the easier we can deploy, and the more systems we integrate with, the higher those returns and the faster you get a return. So, on the other side, where are some of the challenges that you see as we try and get to this next generation of conversational AI? Well, I agree on the integration piece. In our world, integration is basically access to all the services. And obviously, one of the roles of speaking assistants, digital assistants, is actually being a gateway to all types of different services. So it's not just about integrating it, it's about mainly orchestrating services, understanding which service to contact for each type of request and user personality. So you may have different preferences in terms of your travel providers, for example. So depending on your personality and depending on the type of request, you may need to connect to different systems, right? So basically, integration is extremely important. In order to get to integration, you actually have to convince brands and services and companies to play this game, to join the ecosystem, which they are doing. But then, the question is always a balance, like chicken and egg issue, where they are much more motivated to build very meaningful experiences if the audience is there and audience is requesting it. But you cannot get this demand from consumers if you do not have enough services connected. And if you do not get really high quality of the responses, right? So it's an interesting balance where you have to set expectations for consumers and you are trying to achieve the coverage and many of the companies that are building conversation interfaces, they have first to just imagine what the conversations will be about. They do not have any data yet as they haven't launched yet. So that is an interesting challenge and something that is to be solved to get to really widespread conversational AI applications but that's also pretty interesting and I guess it kind of helps us, well, we are working hard on bringing it, right? So what do you think of the opportunities there? So what should be done to make it, to get to that future? Yeah, so this room is filled with entrepreneurs, investors supporting entrepreneurs and we all know that where any great challenge lies, that's really an opportunity for someone to take advantage of it and conversational AI is ripe for that. There's a lot of places where innovation still needs to happen. So making the integration problem making that easier is one place. The other place that is very exciting to both of us is as these AIs become more pervasive, they're gonna enable new use cases that we don't have today and recognizing those use cases and the new opportunities is an area where the people who can identify that and take advantage of it will be able to create great amounts of value and I think we're just at the beginning of that. So if we look on the business side, a lot of the penetration has been in sales. It's very easy to talk about if we can help you convert more leads into revenue, pay us to help you do that. But it doesn't just stop there. We can do the same thing engaging employees to make employee experiences better at the company. Working with our suppliers, working with investors. And so at the end of the day, really the opportunity is for everyone here how can I take advantage of conversational AI? So if you're at a startup and you're trying to grow and expand, maybe you don't need to hire 10 or 20 salespeople. You can augment that with an AI-powered sales assistant. Let them do a lot of that pre-sales grunt work. If you're an investor, the most common use for Series B and Series C funds is to scale sales and marketing. So bring this technology to your portfolio. If you're a corporation and you're looking at digital transformation, where are those repetitive processes where you can apply a sales assistant or an AI-powered assistant to help you? What are some of your other thoughts on key takeaways going forward? No, for the startups here, I guess, like today we have this unique opportunity where there is a new ecosystem that is growing the conversational like UX market. Like I mean, we had this with like web in 90s and then like with mobile apps in 2000s. And basically like most of the stakeholders are here already. So the technology companies are investing huge amount of like resources and money in building hardware, providing tools to make it happen. Brands recognize that it is very important as well. So they are coming there. Startups are still not there. So we are still to see some like breakthrough cases like you know, Angry Birds for mobile or like Pokemon Go for AI. So I kind of like want to invite all the startups here to think like how they can like come up with great new experiences for conversational market. If you have any questions immediately following this session, come join us over in the Slush Cafe and we'd be happy to talk to you. As long as you have questions, we'll give you answers. Thank you. Thank you. Thank you.