WEBVTT 00:00:00.000 --> 00:00:02.127 Jeff, Brian, welcome, Brian, to you. 00:00:02.127 --> 00:00:05.630 First, where are companies getting most stuck 00:00:05.630 --> 00:00:08.383 when it comes to the adoption of AI? 00:00:08.383 --> 00:00:11.511 And I suppose the answer to that would be, what can they do about it? 00:00:11.636 --> 00:00:13.722 Yeah, I mean, we're seeing a lot of companies, 00:00:13.722 --> 00:00:17.017 particularly in the telco industry, that they're really being stuck around 00:00:17.017 --> 00:00:18.601 data being a big challenge for them. 00:00:19.144 --> 00:00:22.355 We're seeing them struggle with all the legacy systems that they have to sort of 00:00:22.355 --> 00:00:24.232 integrate and think about what that looks like. 00:00:25.025 --> 00:00:27.444 And then ultimately, they're struggling with their operating 00:00:27.444 --> 00:00:29.112 models, the ROI that they're going to get. 00:00:29.821 --> 00:00:32.615 And so, you know, some of the research that we've done 00:00:32.615 --> 00:00:36.745 shows that the 25% of companies that are actually getting tangible value from it 00:00:36.745 --> 00:00:39.748 are really focusing on getting it out of the front office. 00:00:39.748 --> 00:00:42.000 And that's things like sales, marketing and service, 00:00:42.000 --> 00:00:45.170 which plays nicely into the great partnership that we have with Salesforce. 00:00:45.962 --> 00:00:49.090 Jeff, what does the rise of AI agents mean in 00:00:49.090 --> 00:00:51.342 your view for the future of work? 00:00:51.468 --> 00:00:56.222 Don't think it's any secret that the AI revolution is already underway. 00:00:56.723 --> 00:01:00.018 And to us, that's a $2 trillion market opportunity 00:01:00.018 --> 00:01:04.981 that more than 85% of our CI OS think is going to be more important to their 00:01:04.981 --> 00:01:07.025 business than the Internet was. 00:01:07.692 --> 00:01:11.279 And there's a good reason for it, which is it's all about digital labor. 00:01:11.279 --> 00:01:15.450 And creating digital workers is phenomenally valuable for these companies 00:01:15.450 --> 00:01:19.370 because these digital workers, they know the great information that's 00:01:19.370 --> 00:01:20.997 needed to drive the business. 00:01:21.247 --> 00:01:24.292 They don't take vacations, they don't take coffee breaks, 00:01:24.292 --> 00:01:25.460 they don't even sleep. 00:01:25.460 --> 00:01:28.713 They're working 24/7 to drive value for their companies. 00:01:29.255 --> 00:01:31.299 To allow a digital worker to do that, though, 00:01:31.299 --> 00:01:33.176 you have to have your data house in order. 00:01:33.468 --> 00:01:36.429 And thankfully, we have a product called Data Cloud that 00:01:36.429 --> 00:01:40.642 helps our customers take their structured and unstructured data and bring it into 00:01:40.642 --> 00:01:43.603 the flow of work so that a digital worker can act on it. 00:01:43.895 --> 00:01:46.731 And that digital worker could be autonomous or it could be assisted. 00:01:46.731 --> 00:01:51.069 It could be the Angel on the shoulder of a user, but with that extra insight, 00:01:51.069 --> 00:01:52.946 those users become more powerful. 00:01:52.946 --> 00:01:57.325 Those companies become more powerful because they can solve difficult problems 00:01:57.325 --> 00:01:58.451 in the flow of work. 00:01:58.785 --> 00:02:02.997 And they do that leveraging our agent force application, which makes it really, 00:02:02.997 --> 00:02:07.377 really easy for customers to create these agents and to deploy them in their work. 00:02:07.377 --> 00:02:10.713 And so the combination of that is significantly greater efficiency, 00:02:10.713 --> 00:02:13.591 higher revenues, all the things that companies are trying 00:02:13.591 --> 00:02:16.636 to do everyday, they now can do with this digital. workforce. 00:02:17.178 --> 00:02:21.224 I have to ask your company, you've, you've been at the forefront of tech, 00:02:21.224 --> 00:02:23.059 you AI has been around for years. 00:02:23.059 --> 00:02:28.523 But what what is what is different now that everybody's talking of Nothing else, it seems. 00:02:28.690 --> 00:02:30.817 Well, we've been actually in the AI business 00:02:30.817 --> 00:02:31.943 for more than 10 years. 00:02:32.235 --> 00:02:34.612 And so we've had a lot of technology that does that. 00:02:34.612 --> 00:02:37.824 But the predictive elements that have come up are very, very powerful. 00:02:38.074 --> 00:02:42.620 And if you get the data equation correct and you have that foundation there, 00:02:42.620 --> 00:02:46.040 now you can leverage those LMS and that other technology, 00:02:46.040 --> 00:02:49.711 especially if a platform like Agentforce makes it that simple. 00:02:49.919 --> 00:02:53.798 And you can have a deeply unified platform like Salesforce has, 00:02:53.798 --> 00:02:57.677 where the application, the data and the agents are all existing 00:02:57.677 --> 00:03:00.680 in the same space that was never before possible. 00:03:00.680 --> 00:03:04.601 So the simplicity of that and the power of that is unlocking a lot of 00:03:04.601 --> 00:03:06.519 opportunities for these customers. 00:03:08.104 --> 00:03:12.025 What's the most interesting real world application of a Gentic AI that you've 00:03:12.025 --> 00:03:13.026 seen at the moment? 00:03:13.193 --> 00:03:17.614 We actually created a voice based agent that can accept incoming customer calls. 00:03:18.156 --> 00:03:20.074 Now, typically you'd see that in AB to C 00:03:20.074 --> 00:03:22.493 environment, but doing it in AB to B environment is 00:03:22.493 --> 00:03:24.829 kind of what makes this unique and differentiated. 00:03:25.288 --> 00:03:28.249 And it was really to solve this challenge around churn management. 00:03:28.541 --> 00:03:32.212 And so this voice agent can actually answer complex questions. 00:03:32.212 --> 00:03:36.090 It can help set differentiating capabilities from its competitors and 00:03:36.090 --> 00:03:40.678 ultimately pass the information off to a human agent if needed to take action with 00:03:40.678 --> 00:03:41.638 the end customer. 00:03:41.638 --> 00:03:44.849 So I think that's pretty cool to see that happening in real life in a complex 00:03:44.849 --> 00:03:45.642 business situation. 00:03:46.392 --> 00:03:48.311 What have you seen that's pretty cool, Jeff? 00:03:48.311 --> 00:03:50.521 Well, we already have thousands of customers 00:03:50.521 --> 00:03:54.108 that are writing agents using Agentforce and using those in the flow work, 00:03:54.108 --> 00:03:55.235 which is pretty amazing. 00:03:55.526 --> 00:03:57.737 And they cover all kinds of different industries. 00:03:57.737 --> 00:04:00.740 So we have companies like 1 New Zealand, FedEx, 00:04:00.740 --> 00:04:05.995 Equinex and Proceda Health that are doing really amazing things with these agents. 00:04:05.995 --> 00:04:08.289 And since we're at a telecommunications conference, 00:04:08.289 --> 00:04:09.749 I'll just give you some examples. 00:04:09.749 --> 00:04:13.461 In the communications business, we have prebuilt agents that leverage 00:04:13.461 --> 00:04:16.256 Communications Cloud, which is our industry specific 00:04:16.256 --> 00:04:20.176 application to do things in on the sales side of the house that are really 00:04:20.176 --> 00:04:23.346 difficult to be done by humans like complex B to B quoting, 00:04:23.346 --> 00:04:27.392 which is the bane of existence for a lot of enterprise sales reps out there. 00:04:27.600 --> 00:04:30.687 But an agent can do it immediately if it's got the right data, 00:04:30.687 --> 00:04:32.563 the right rules and the right pricing. 00:04:32.939 --> 00:04:36.401 And then on the service side, it's also very difficult for service 00:04:36.401 --> 00:04:39.821 agents to resolve, say, billing disputes because they have to put 00:04:39.821 --> 00:04:42.448 the customer on hold and look up some information, 00:04:42.448 --> 00:04:45.743 then look up a policy and then come back and try to resolve it. 00:04:45.743 --> 00:04:48.830 It's painful, but an agent can do that instantly. 00:04:49.080 --> 00:04:52.333 And when they do that, they put a smile on that customer's face. 00:04:52.458 --> 00:04:55.044 And everybody knows that happy customers buy more. 00:04:55.378 --> 00:04:59.007 So in a service context, in a telco, you can actually create a sales 00:04:59.007 --> 00:05:01.384 opportunity by upselling that happy customer. 00:05:01.384 --> 00:05:05.847 So the sales agents and the service agents can also work together behind the 00:05:05.847 --> 00:05:08.474 scenes to increase revenues, decrease costs. 00:05:09.100 --> 00:05:09.475 Fantastic. 00:05:09.851 --> 00:05:11.144 Jeff, Bryan, pleasure. 00:05:11.144 --> 00:05:12.061 Thank you so much. 00:05:12.270 --> 00:05:12.979 Thank you, Georgie.