1 00:00:02,800 --> 00:00:05,680 Speaker 1: Welcome to the Business of Tech, powered by Two Degrees Business. 2 00:00:05,680 --> 00:00:09,000 Speaker 1: I'm Peter Griffin, coming to you from San Francisco, where 3 00:00:09,000 --> 00:00:12,479 Speaker 1: I've been hanging out with well around fifty thousand other 4 00:00:12,520 --> 00:00:16,040 Speaker 1: people in town for the annual dream Force conference put 5 00:00:16,079 --> 00:00:21,200 Speaker 1: on by software company Salesforce, and it's flamboyant founder Marc Benioff. 6 00:00:21,680 --> 00:00:25,640 Speaker 1: I've always liked getting to dream Force because Benioff, You've 7 00:00:25,640 --> 00:00:28,320 Speaker 1: got to hand it to him, puts on a great show. 8 00:00:28,440 --> 00:00:31,200 Speaker 1: He always gets big names to talk at his conference. 9 00:00:31,760 --> 00:00:37,159 Speaker 1: This year's highlights included Google CEO Sundaipachai, President Trump's aisar 10 00:00:37,400 --> 00:00:40,839 Speaker 1: and member of the PayPal mafia David Sachs, and an 11 00:00:40,920 --> 00:00:45,480 Speaker 1: unexpected one, Pete Bodhage Edge, the former mayor of South Bend, Indiana, 12 00:00:45,520 --> 00:00:50,280 Speaker 1: who ran in the Democratic presidential campaign in twenty nineteen 13 00:00:50,560 --> 00:00:55,640 Speaker 1: before dropping out and serving as President Biden's Transport Secretary. 14 00:00:55,760 --> 00:00:59,560 Speaker 1: Bootage Edge is still tipped as a future potential candidate 15 00:00:59,640 --> 00:01:02,320 Speaker 1: and his talk was really fascinating. I've included a clip 16 00:01:02,360 --> 00:01:04,800 Speaker 1: of it at the end of the podcast. Dream Force 17 00:01:04,920 --> 00:01:08,880 Speaker 1: was dominated once again by artificial intelligence. It's a year 18 00:01:08,959 --> 00:01:12,800 Speaker 1: since Salesforce debuted Agent Force and look Salesforce is a 19 00:01:12,840 --> 00:01:17,960 Speaker 1: tech company that is probably most enthusiastically embraced AI agents. 20 00:01:18,040 --> 00:01:24,040 Speaker 1: These are autonomous software programs that perceive their environment, make decisions, 21 00:01:24,080 --> 00:01:28,960 Speaker 1: and take actions to achieve goals, often with minimal human intervention. 22 00:01:29,400 --> 00:01:33,440 Speaker 1: Agents are particularly useful for automating aspects of customer service 23 00:01:33,440 --> 00:01:37,800 Speaker 1: and support, sales and marketing, which is why Salesforce has 24 00:01:37,840 --> 00:01:41,600 Speaker 1: gone all in on agents. It has twelve thousand Agent 25 00:01:41,720 --> 00:01:45,720 Speaker 1: Force customers after its first year. It's around eight percent 26 00:01:45,800 --> 00:01:49,840 Speaker 1: of the entire Salesforce customer base of companies, which a 27 00:01:49,920 --> 00:01:53,520 Speaker 1: number of analysts pointed out is relatively low uptake, but 28 00:01:53,880 --> 00:01:57,080 Speaker 1: as Benioff countered, it's a heck of a lot more 29 00:01:57,120 --> 00:02:00,640 Speaker 1: than any other tech company is managing at the moment. Still, 30 00:02:00,680 --> 00:02:04,240 Speaker 1: despite the AI boom, some would say bubble that we're in, 31 00:02:04,480 --> 00:02:07,440 Speaker 1: Salesforce has actually seen at share price retreat twenty three 32 00:02:07,480 --> 00:02:10,680 Speaker 1: percent this year. It claims it's using AI to reduce 33 00:02:11,000 --> 00:02:14,440 Speaker 1: one hundred million dollars in costs across the company each year. 34 00:02:14,919 --> 00:02:19,239 Speaker 1: It shared four thousand staff, many in customer support roles 35 00:02:19,280 --> 00:02:22,800 Speaker 1: by shifting to AI agents, and it told the share 36 00:02:22,840 --> 00:02:26,519 Speaker 1: market it expects to return to double digit growth out 37 00:02:26,560 --> 00:02:29,520 Speaker 1: to twenty thirty, when it expects to rack up sixty 38 00:02:29,560 --> 00:02:32,600 Speaker 1: billion dollars in revenue, up from around thirty eight billion 39 00:02:32,840 --> 00:02:35,639 Speaker 1: last year. That growth will largely come on the back 40 00:02:35,720 --> 00:02:39,359 Speaker 1: of businesses taking up AI agents. One thing that only 41 00:02:39,360 --> 00:02:42,799 Speaker 1: got a fleeting demo in the Dreamforce keynote, But one 42 00:02:42,840 --> 00:02:46,200 Speaker 1: of the things that Salesforce is piloting, which is really interesting, 43 00:02:46,400 --> 00:02:49,480 Speaker 1: is Agent Force Voice. It's like calling up a call 44 00:02:49,520 --> 00:02:52,079 Speaker 1: center where you might typically get a human on the 45 00:02:52,160 --> 00:02:57,000 Speaker 1: line or maybe a voice activated menu. Now you'll potentially 46 00:02:57,040 --> 00:03:00,360 Speaker 1: get an AI agent. You can talk to one that 47 00:03:00,400 --> 00:03:03,200 Speaker 1: can understand what you want. It might be changing your 48 00:03:03,240 --> 00:03:07,960 Speaker 1: broadband plan, returning some clothing that doesn't fit, reporting an 49 00:03:08,000 --> 00:03:11,760 Speaker 1: electricity outage, or buying a plane ticket. Given that up 50 00:03:11,760 --> 00:03:15,839 Speaker 1: to eighty percent of interactions with customer service in some 51 00:03:15,880 --> 00:03:19,720 Speaker 1: industries is still coming in via phone lines, that would 52 00:03:19,720 --> 00:03:23,600 Speaker 1: be huge. If it works as envisaged, that's a game changer. 53 00:03:23,800 --> 00:03:26,800 Speaker 1: More about Agent Force Voice coming up in the show. 54 00:03:27,000 --> 00:03:29,440 Speaker 1: At dream Force, I also got around a lot of 55 00:03:29,440 --> 00:03:33,360 Speaker 1: companies that are using agents to automate various processes. PepsiCo 56 00:03:33,520 --> 00:03:36,960 Speaker 1: is using agent Force to let its smaller merchants more 57 00:03:37,000 --> 00:03:40,240 Speaker 1: easily check on the status of their orders just using 58 00:03:40,240 --> 00:03:44,400 Speaker 1: a simple chat based agent. Lululemon, the active where company, 59 00:03:44,440 --> 00:03:47,760 Speaker 1: is offering customers the chance to use an agent to 60 00:03:47,840 --> 00:03:51,320 Speaker 1: customize a wardrobe through an app based experience and then 61 00:03:51,360 --> 00:03:54,720 Speaker 1: go on to purchase what they've been looking at. Pearson's, 62 00:03:54,760 --> 00:03:58,880 Speaker 1: the education provider, is letting students use agents to change 63 00:03:58,920 --> 00:04:03,160 Speaker 1: courses and by textbooks. I saw a really cool agentic 64 00:04:03,200 --> 00:04:07,720 Speaker 1: service from Chicago Medical University to give patients one chat 65 00:04:07,760 --> 00:04:12,720 Speaker 1: based interface to order prescriptions, change appointments, get their medical 66 00:04:12,760 --> 00:04:15,720 Speaker 1: records delivered to them. That would remove a heck of 67 00:04:15,720 --> 00:04:18,279 Speaker 1: a lot of hassle dealing with this sort of gap 68 00:04:18,320 --> 00:04:20,440 Speaker 1: we have between patient portals which we all sort of 69 00:04:20,480 --> 00:04:22,520 Speaker 1: have in New Zealand now, and the mirrid range of 70 00:04:22,560 --> 00:04:26,400 Speaker 1: healthcare professionals who actually deliver frontline services. It can be 71 00:04:26,480 --> 00:04:29,000 Speaker 1: frustrating actually going from one to the other. Good to 72 00:04:29,000 --> 00:04:31,520 Speaker 1: see some New Zealand companies one in Zed, Fisher and 73 00:04:31,520 --> 00:04:36,080 Speaker 1: Pikeland Zero among those being showcased at Dreamforce for Innovative 74 00:04:36,160 --> 00:04:39,280 Speaker 1: Uses of AI agents. So you're hearing the piece from 75 00:04:39,400 --> 00:04:41,320 Speaker 1: Jason Paris, who I caught up on a show floor 76 00:04:41,360 --> 00:04:44,159 Speaker 1: at Dreamforce where one in Zed had a display and 77 00:04:44,279 --> 00:04:47,320 Speaker 1: demo area. But first I wanted to invite back onto 78 00:04:47,320 --> 00:04:50,800 Speaker 1: the show Hamish Miles, the managing director of Salesforce New Zealand, 79 00:04:50,800 --> 00:04:54,159 Speaker 1: to get his take on what's transpired since Agent Force 80 00:04:54,279 --> 00:04:58,800 Speaker 1: unleashed the AI agents almost exactly a year ago. Here's 81 00:04:58,839 --> 00:05:10,240 Speaker 1: Hamish Miles from s Salesforce. Okay, so Hamish, welcome back 82 00:05:10,240 --> 00:05:11,120 Speaker 1: to the business of Tech. 83 00:05:11,120 --> 00:05:11,640 Speaker 2: How are you doing. 84 00:05:11,800 --> 00:05:15,200 Speaker 3: Yeah, awesome, It's been an epic few days. I'm absolutely 85 00:05:15,240 --> 00:05:17,960 Speaker 3: pumped and looking forward to what comes next. 86 00:05:18,120 --> 00:05:21,080 Speaker 1: Yeah, we're on the roof of the Muscone Center in 87 00:05:21,160 --> 00:05:26,000 Speaker 1: San Francisco. Dream Force, the biggest conference in San Francisco, 88 00:05:26,080 --> 00:05:28,760 Speaker 1: the biggest tech conference, has been going all week and 89 00:05:29,400 --> 00:05:32,680 Speaker 1: interesting what you say is that the highlights obviously Agent 90 00:05:32,760 --> 00:05:36,520 Speaker 1: Force three sixty is the centerpiece of this and to me, 91 00:05:36,600 --> 00:05:40,440 Speaker 1: it seems like we're a year into this agentic ai 92 00:05:40,920 --> 00:05:45,839 Speaker 1: movement that Salesforce really led you back in October twenty 93 00:05:45,880 --> 00:05:48,320 Speaker 1: twenty four. It's sort of moved from being a product 94 00:05:48,360 --> 00:05:52,480 Speaker 1: to a platform. This is the systematizing of agentic ai 95 00:05:52,680 --> 00:05:54,839 Speaker 1: into everything that Salesforce does. 96 00:05:54,920 --> 00:05:58,039 Speaker 3: For me, it's been an absolutely fascinating few days and 97 00:05:58,160 --> 00:05:59,960 Speaker 3: you can see the progression of the journey I've been 98 00:06:00,240 --> 00:06:02,760 Speaker 3: GenTech AI and you can see some of the great 99 00:06:02,800 --> 00:06:05,400 Speaker 3: outcomes our customers are starting to produce. I think Agent 100 00:06:05,440 --> 00:06:08,760 Speaker 3: four three sixty is a natural next step for us. 101 00:06:08,880 --> 00:06:10,880 Speaker 3: It makes a lot of sense to our customers. What 102 00:06:10,960 --> 00:06:14,560 Speaker 3: excites me the most is the agentic enterprise. Where are 103 00:06:14,560 --> 00:06:16,479 Speaker 3: we going to go next? And then the combination of 104 00:06:16,600 --> 00:06:19,800 Speaker 3: humans and AI working together things an exciting time for 105 00:06:19,800 --> 00:06:22,000 Speaker 3: the industry and we're just starting right We're just scratching 106 00:06:22,000 --> 00:06:22,480 Speaker 3: the surface. 107 00:06:22,600 --> 00:06:25,800 Speaker 1: Twelve thousand customers, I think half of them are paying 108 00:06:25,920 --> 00:06:30,120 Speaker 1: customers are using agent Voice. Now, what's been the adoption 109 00:06:30,279 --> 00:06:31,200 Speaker 1: like in New Zealand. 110 00:06:31,440 --> 00:06:34,320 Speaker 3: You know, I think we're at the front edge as well. 111 00:06:34,360 --> 00:06:37,080 Speaker 3: I've got some great customers doing some great things. I mean, 112 00:06:37,080 --> 00:06:38,920 Speaker 3: you've heard from Jason Paris at one and said, that's 113 00:06:38,960 --> 00:06:42,760 Speaker 3: an agentic journey, that prepay agent does multiple things all 114 00:06:42,800 --> 00:06:45,000 Speaker 3: in one journey, all in a few minutes for Shre 115 00:06:45,000 --> 00:06:47,520 Speaker 3: and Pike or on the path with field service agents 116 00:06:47,839 --> 00:06:51,719 Speaker 3: and are scaling the premium product with Premium Service zero 117 00:06:51,760 --> 00:06:53,680 Speaker 3: are going to do some exciting things very shortly. 118 00:06:53,720 --> 00:06:55,880 Speaker 1: And it seems to me, like Jason said, the customer 119 00:06:55,920 --> 00:06:58,320 Speaker 1: facing ones, which typically will look like a chatbot or 120 00:06:58,400 --> 00:07:00,960 Speaker 1: maybe a voice call. So but he said, you know 121 00:07:01,040 --> 00:07:04,839 Speaker 1: that prepaid product shifting sort of agent that they've created. 122 00:07:04,839 --> 00:07:06,400 Speaker 1: If you on a mobile plan and you want to 123 00:07:06,440 --> 00:07:08,360 Speaker 1: move to another one, and this will do it all 124 00:07:08,400 --> 00:07:11,680 Speaker 1: automatically and suggest the right plan for you. But he said, 125 00:07:11,680 --> 00:07:14,600 Speaker 1: there's actually seven agents in the background of that, So 126 00:07:14,720 --> 00:07:19,239 Speaker 1: all the handoffs and querrying data from one ZED system, 127 00:07:19,320 --> 00:07:21,640 Speaker 1: there's actually a whole bunch of agents doing that in 128 00:07:21,680 --> 00:07:22,160 Speaker 1: the background. 129 00:07:22,240 --> 00:07:23,840 Speaker 3: Yeah, So they were sort of looking at the first 130 00:07:23,840 --> 00:07:26,520 Speaker 3: stage of orchestration of agents in that sense. So the 131 00:07:26,600 --> 00:07:28,960 Speaker 3: first sort of a augentic agents we spun up. They 132 00:07:29,000 --> 00:07:32,640 Speaker 3: were sort of sort of single task orientated. Salesforce has 133 00:07:32,680 --> 00:07:34,880 Speaker 3: more than two hundred and two hundred and ten. 134 00:07:34,840 --> 00:07:36,160 Speaker 2: Agents live at the moment. 135 00:07:36,600 --> 00:07:38,920 Speaker 3: Internally, I think there are five hundred and fifty sort 136 00:07:38,960 --> 00:07:41,120 Speaker 3: of tasks that it can carry on. We're in this 137 00:07:41,240 --> 00:07:43,720 Speaker 3: age now where this one agent, like the one New 138 00:07:43,800 --> 00:07:47,120 Speaker 3: Zealand or one assystem I think it's called one assistant, 139 00:07:47,200 --> 00:07:50,640 Speaker 3: can orchestrate multiple actions. And in their case it's like 140 00:07:51,240 --> 00:07:53,800 Speaker 3: fraud check. It's a security checking for the trust layer. 141 00:07:54,600 --> 00:07:57,200 Speaker 3: It's have we got the right plan? Can I make 142 00:07:57,200 --> 00:08:01,760 Speaker 3: you some recommendations? And it's absolutely fascinating and we can 143 00:08:01,800 --> 00:08:02,960 Speaker 3: do so much more as well. 144 00:08:03,040 --> 00:08:04,840 Speaker 1: Before I go any further with Hamish, I thought it'd 145 00:08:04,880 --> 00:08:07,200 Speaker 1: be good to bring in Jason Parris from One end Zed, 146 00:08:07,200 --> 00:08:09,960 Speaker 1: who I caught up with at Agent for City in 147 00:08:10,000 --> 00:08:13,160 Speaker 1: the depths of the Moscone Center where all of these 148 00:08:13,200 --> 00:08:17,160 Speaker 1: demos of agents are being shown. So he gave me 149 00:08:17,200 --> 00:08:20,240 Speaker 1: a really good rundown on what exactly one end Zed 150 00:08:20,400 --> 00:08:23,640 Speaker 1: was doing with these AI agents to help roll out 151 00:08:23,640 --> 00:08:27,480 Speaker 1: a new service for its prepaid customers. So tell us 152 00:08:27,480 --> 00:08:29,680 Speaker 1: about how you're using agentic. 153 00:08:29,240 --> 00:08:33,920 Speaker 4: Enterprise, Jason, So, Peter, this is something that's just gone 154 00:08:33,920 --> 00:08:37,520 Speaker 4: into production. We've been working with Salesforce and deploying their 155 00:08:37,520 --> 00:08:39,000 Speaker 4: agent Force technology for over a. 156 00:08:39,040 --> 00:08:42,280 Speaker 5: Year now and this is the latest agent. 157 00:08:42,240 --> 00:08:46,040 Speaker 4: And So from a tallocommunications perspective, one of the most 158 00:08:46,360 --> 00:08:50,200 Speaker 4: challenging journeys that a customer can go through is migration. 159 00:08:50,480 --> 00:08:53,040 Speaker 4: So when you're moving from a plan that you probably 160 00:08:53,040 --> 00:08:55,640 Speaker 4: are quite happy with to a new plan that we 161 00:08:55,679 --> 00:08:58,320 Speaker 4: think you should be interested in, it's quite often a 162 00:08:58,360 --> 00:09:01,160 Speaker 4: complex and clunky process or a customer to go through. 163 00:09:01,160 --> 00:09:02,319 Speaker 5: And it's also a bad. 164 00:09:02,160 --> 00:09:06,320 Speaker 4: One for a talco because you can get that reconsideration moment, 165 00:09:06,440 --> 00:09:09,080 Speaker 4: and you want the journey to be so seamless and 166 00:09:09,160 --> 00:09:13,000 Speaker 4: effortless that you love the Talco even more at the 167 00:09:13,080 --> 00:09:17,920 Speaker 4: end of it. And so we've deployed an agentic agent 168 00:09:18,280 --> 00:09:22,000 Speaker 4: in our business, which is helping hundreds of thousands of 169 00:09:22,000 --> 00:09:23,920 Speaker 4: our customers move to. 170 00:09:24,440 --> 00:09:26,360 Speaker 5: A better prepaid plan for them. 171 00:09:26,640 --> 00:09:30,480 Speaker 4: We've started with our most difficult customers, tens of thousands 172 00:09:30,520 --> 00:09:35,640 Speaker 4: of those and four hundred percent improvement and engagement on 173 00:09:35,679 --> 00:09:39,440 Speaker 4: the agentic journey compared to the journeys that we would 174 00:09:39,480 --> 00:09:44,680 Speaker 4: traditionally have used through normal retail or call center or 175 00:09:44,679 --> 00:09:47,000 Speaker 4: even our online website presence. 176 00:09:47,400 --> 00:09:52,080 Speaker 1: So is the customer interacting with the agent directly, yes, 177 00:09:52,120 --> 00:09:53,520 Speaker 1: by a chatbody or something. 178 00:09:53,520 --> 00:09:57,000 Speaker 4: Yeah, So via the agent itself, right, it'll authenticate you 179 00:09:57,360 --> 00:10:00,839 Speaker 4: to know who you are. It'll know so the plan 180 00:10:01,520 --> 00:10:05,080 Speaker 4: that you're on currently, but also the next best plan 181 00:10:05,280 --> 00:10:08,800 Speaker 4: for you. It will present a carousel of options that 182 00:10:08,800 --> 00:10:11,240 Speaker 4: you can interact with, and the agent will talk to 183 00:10:11,280 --> 00:10:14,079 Speaker 4: you about the pros and cons of the plan compared 184 00:10:14,160 --> 00:10:16,520 Speaker 4: to what you're currently on, and then we'll ask you 185 00:10:16,559 --> 00:10:18,480 Speaker 4: to confirm and then once you're happy with. 186 00:10:18,480 --> 00:10:20,760 Speaker 5: It, it'll tell you that you're done. 187 00:10:21,120 --> 00:10:24,800 Speaker 4: Right and await, it'll have a record for you and 188 00:10:24,840 --> 00:10:28,679 Speaker 4: for us of what we've agreed should anything change, and 189 00:10:28,720 --> 00:10:31,440 Speaker 4: then also the agent will ask if it can help 190 00:10:31,520 --> 00:10:35,040 Speaker 4: you with some other frequently asked questions of someone who 191 00:10:35,120 --> 00:10:37,640 Speaker 4: is a mobile customer that might want to know. So 192 00:10:38,360 --> 00:10:40,320 Speaker 4: that part of it we're going to continue to build 193 00:10:40,360 --> 00:10:41,199 Speaker 4: out and approve on. 194 00:10:41,840 --> 00:10:45,920 Speaker 5: But the upgrade path for a customer. 195 00:10:47,160 --> 00:10:50,800 Speaker 4: Seamless, and it took us five weeks to build and 196 00:10:51,200 --> 00:10:51,719 Speaker 4: deploy it. 197 00:10:51,840 --> 00:10:54,520 Speaker 1: Right so, and doesn't require a lot of coding or 198 00:10:54,559 --> 00:10:56,760 Speaker 1: anything like that. It's all drag and drop, build your 199 00:10:56,760 --> 00:10:58,440 Speaker 1: own templated agent building. 200 00:10:58,640 --> 00:11:03,120 Speaker 4: Yeah, so some configuration, but it's mainly around data cleaner, 201 00:11:03,240 --> 00:11:06,920 Speaker 4: making sure the data is accurate, integration with our existing 202 00:11:07,640 --> 00:11:12,760 Speaker 4: it the Salesforce Agent Force product set are mainly taken 203 00:11:12,920 --> 00:11:13,560 Speaker 4: and deployed. 204 00:11:14,000 --> 00:11:16,480 Speaker 5: The time to deploy it probably is build. 205 00:11:16,760 --> 00:11:19,200 Speaker 4: It's making sure you understand what the journey is and 206 00:11:19,240 --> 00:11:22,280 Speaker 4: the integration with your own rest of your technology and 207 00:11:22,679 --> 00:11:25,520 Speaker 4: the data cleanup. Like the very first agent we built 208 00:11:25,720 --> 00:11:29,000 Speaker 4: with Salesforce took us eight hours and then two weeks 209 00:11:29,040 --> 00:11:32,040 Speaker 4: to deploy again because of the data and the integration 210 00:11:32,120 --> 00:11:33,839 Speaker 4: with another to other technology. 211 00:11:34,040 --> 00:11:37,760 Speaker 1: Right So, those tens and thousands of problematic customers there, 212 00:11:37,840 --> 00:11:39,920 Speaker 1: ones that are may be about to churn off one 213 00:11:39,960 --> 00:11:42,120 Speaker 1: into the you're going to go somewhere else, So that 214 00:11:42,840 --> 00:11:45,280 Speaker 1: the agent is looking at all the data that sits 215 00:11:45,280 --> 00:11:48,240 Speaker 1: in Salesforce about that customer, going okay, I know what 216 00:11:48,320 --> 00:11:50,079 Speaker 1: you need. Here are some suggestions. 217 00:11:50,320 --> 00:11:52,440 Speaker 5: Yeah, well that's the Salesforce Marketing Cloud. 218 00:11:52,520 --> 00:11:55,760 Speaker 4: So an another tool within the ecosystem that helps us 219 00:11:56,000 --> 00:11:59,960 Speaker 4: look at our data set, query customers into different SEGM 220 00:12:00,080 --> 00:12:03,480 Speaker 4: and cohorts and put exactly that brief in and then 221 00:12:03,520 --> 00:12:06,120 Speaker 4: it will give us that subset. And so you know 222 00:12:06,200 --> 00:12:10,600 Speaker 4: that when you are trialing an agentic tool with your 223 00:12:10,600 --> 00:12:13,360 Speaker 4: most difficult customers, if it works for them, it's going 224 00:12:13,400 --> 00:12:15,280 Speaker 4: to work for everyone. So you always start with the 225 00:12:15,360 --> 00:12:18,839 Speaker 4: naliest ones first, normally to give you confidence that when 226 00:12:18,880 --> 00:12:21,280 Speaker 4: you do decide to scale it from tens of thousands 227 00:12:21,320 --> 00:12:24,640 Speaker 4: to hundreds of thousands to millions of customers, you've got 228 00:12:24,640 --> 00:12:25,240 Speaker 4: that clients. 229 00:12:25,520 --> 00:12:28,200 Speaker 1: So like, if I'm looking at changing plans, I'll go 230 00:12:28,280 --> 00:12:30,160 Speaker 1: to the one in ZED website and I'll see all 231 00:12:30,160 --> 00:12:32,920 Speaker 1: the panels here. If the different are the broadband or 232 00:12:33,000 --> 00:12:35,640 Speaker 1: mobile plans that you've got, so in the near future 233 00:12:35,720 --> 00:12:37,760 Speaker 1: you're more likely to just go straight to an agent 234 00:12:37,800 --> 00:12:38,839 Speaker 1: and say this. 235 00:12:38,880 --> 00:12:39,439 Speaker 2: Is what I need. 236 00:12:39,480 --> 00:12:40,200 Speaker 1: What have you got for me? 237 00:12:40,760 --> 00:12:43,200 Speaker 4: Yeah, you will, and we'll be transparent about it as well, 238 00:12:43,240 --> 00:12:45,440 Speaker 4: by the way, so it's not as if you'll think 239 00:12:45,480 --> 00:12:46,520 Speaker 4: you're talking to a human. 240 00:12:46,600 --> 00:12:49,600 Speaker 5: You'll know that you're talking to an agentic tool. 241 00:12:50,120 --> 00:12:53,160 Speaker 4: Increasingly, because they're doing such a good job, we think 242 00:12:53,200 --> 00:12:55,800 Speaker 4: that our customers will go thank God, because I don't 243 00:12:55,800 --> 00:12:58,240 Speaker 4: want to talk to those use of body humans. I'd 244 00:12:58,240 --> 00:13:01,680 Speaker 4: like to talk to more efficient and so that's exactly 245 00:13:02,160 --> 00:13:04,280 Speaker 4: how that will work. And then what we will do 246 00:13:04,400 --> 00:13:08,080 Speaker 4: is we'll keep the human conversations to the probably more 247 00:13:08,080 --> 00:13:11,520 Speaker 4: important ones. So if I really have a complex technical 248 00:13:11,559 --> 00:13:12,520 Speaker 4: issue that I need. 249 00:13:12,360 --> 00:13:15,119 Speaker 5: Some help with, or I want to talk to someone. 250 00:13:14,840 --> 00:13:17,680 Speaker 4: About upgrading my handset because it's going to cost me 251 00:13:17,720 --> 00:13:21,640 Speaker 4: three thousand dollars to do that, or maybe unfortunately I'm 252 00:13:21,679 --> 00:13:25,720 Speaker 4: calling because there's been someone who's l or under financial 253 00:13:25,720 --> 00:13:28,640 Speaker 4: stress or has passed away in the family, those are 254 00:13:28,679 --> 00:13:31,400 Speaker 4: the moments where you really want to have a conversation 255 00:13:31,600 --> 00:13:36,080 Speaker 4: with a person versus a tool. So we're deploying the 256 00:13:36,160 --> 00:13:41,760 Speaker 4: technology or the agentic technology on the areas where really 257 00:13:41,880 --> 00:13:46,000 Speaker 4: humans shouldn't be doing that work, but it's just by 258 00:13:46,040 --> 00:13:48,560 Speaker 4: default that we're having to throw a lot of people 259 00:13:48,600 --> 00:13:51,160 Speaker 4: at it. Now we can put those people onto more 260 00:13:51,200 --> 00:13:54,440 Speaker 4: important stuff and let the agents do the hard yards 261 00:13:54,480 --> 00:13:54,839 Speaker 4: for us. 262 00:13:54,920 --> 00:13:58,360 Speaker 1: Yeah, so that the agent will complete the transaction. So 263 00:13:58,600 --> 00:14:00,480 Speaker 1: if you decide yes, I do to move on to 264 00:14:00,480 --> 00:14:02,680 Speaker 1: a different plan, that will do that automatically. 265 00:14:02,800 --> 00:14:03,679 Speaker 5: Yeah, that's great. 266 00:14:03,720 --> 00:14:05,920 Speaker 1: And then so everything in the back end in terms 267 00:14:05,960 --> 00:14:08,760 Speaker 1: of your record of what plan they're on, that's all 268 00:14:08,840 --> 00:14:10,400 Speaker 1: updated automatically by the agent. 269 00:14:10,480 --> 00:14:14,319 Speaker 4: Yeah, correctly, So into our CRM Salesforce tool at the 270 00:14:14,320 --> 00:14:17,720 Speaker 4: same time. So you've got the ecosystem of the traditional 271 00:14:17,760 --> 00:14:21,400 Speaker 4: customer relationship management, which we're moving. 272 00:14:21,160 --> 00:14:22,640 Speaker 5: On to Salesforce. 273 00:14:22,680 --> 00:14:25,200 Speaker 4: So all of our prepaid customers, all our products, all 274 00:14:25,240 --> 00:14:28,280 Speaker 4: our plans are now on the Salesforce CRM, and then 275 00:14:28,320 --> 00:14:31,360 Speaker 4: you apply the agentic player on top of it, so the. 276 00:14:31,320 --> 00:14:32,840 Speaker 5: Intelligence layer on top of it. 277 00:14:32,960 --> 00:14:36,120 Speaker 4: Yeah, where you've got a whole bunch of agents performing 278 00:14:36,120 --> 00:14:38,280 Speaker 4: a whole bunch of tasks and one of them is 279 00:14:38,720 --> 00:14:43,000 Speaker 4: a plan upgrade or a customer migration. So end to ends, 280 00:14:43,000 --> 00:14:45,000 Speaker 4: the ecosystem has a record and that the. 281 00:14:45,680 --> 00:14:46,560 Speaker 5: Customers clear about. 282 00:14:46,560 --> 00:14:50,400 Speaker 4: The only thing is there's disco movement, dancing and music, 283 00:14:50,680 --> 00:14:52,840 Speaker 4: and that doesn't happen when you're on our website. 284 00:14:52,600 --> 00:14:55,360 Speaker 1: Right right, Yeah, Well, interestingly, you know they have been 285 00:14:55,400 --> 00:15:00,600 Speaker 1: talking here about Agent Force Voice, which they're piloting get 286 00:15:00,600 --> 00:15:03,600 Speaker 1: a lot of coal traffic. Still people want to call 287 00:15:03,680 --> 00:15:06,160 Speaker 1: up and then you know, if it's overloaded, you might 288 00:15:06,160 --> 00:15:08,680 Speaker 1: get a callback option or something like that. What do 289 00:15:08,720 --> 00:15:11,800 Speaker 1: you think about the option of being able to talk 290 00:15:11,840 --> 00:15:14,800 Speaker 1: to an agent's and you know how hard it is 291 00:15:14,800 --> 00:15:17,520 Speaker 1: to get voice recognition and stuff really accurate. 292 00:15:17,600 --> 00:15:20,160 Speaker 5: Do you see promise in that it's a game changer. 293 00:15:20,480 --> 00:15:24,520 Speaker 4: It's probably of all the things that were discussed yesterday 294 00:15:24,560 --> 00:15:28,840 Speaker 4: that personally I'm most excited about. I genuinely believe that 295 00:15:29,280 --> 00:15:32,920 Speaker 4: voice to agentic tools is the game changer because you 296 00:15:32,960 --> 00:15:35,920 Speaker 4: think about, I don't know, an eighty year old who 297 00:15:36,000 --> 00:15:40,680 Speaker 4: might be really kind of resistant or nervous about typing 298 00:15:40,720 --> 00:15:44,320 Speaker 4: something into an AI which is perceived to be a bot, 299 00:15:44,960 --> 00:15:48,120 Speaker 4: Whereas actually, if I could have a conversation where there's 300 00:15:48,240 --> 00:15:51,760 Speaker 4: no latency, that it's a humanized conversation that you can 301 00:15:51,760 --> 00:15:57,280 Speaker 4: build rapport through transparency that you're talking to an agentic tool, 302 00:15:57,640 --> 00:16:00,920 Speaker 4: it's probably an easier step for needed just to talk 303 00:16:00,960 --> 00:16:02,880 Speaker 4: to an AI agent in the same way I would 304 00:16:02,960 --> 00:16:05,680 Speaker 4: talk to an agent and a call center compared to 305 00:16:05,840 --> 00:16:10,119 Speaker 4: being forced down a text or social media type conversation. 306 00:16:10,760 --> 00:16:12,520 Speaker 4: And I think it's going to be way more efficient, 307 00:16:12,600 --> 00:16:14,600 Speaker 4: like even the way that I use my own tools. 308 00:16:14,640 --> 00:16:15,680 Speaker 5: Now, if I'm talking to. 309 00:16:16,160 --> 00:16:19,240 Speaker 4: Chat GPT, I'm not texting you speak of having a 310 00:16:19,240 --> 00:16:22,400 Speaker 4: conversation with it. Yeah, And I think even that's what 311 00:16:22,440 --> 00:16:24,800 Speaker 4: ob an Ai has seen over the last three years 312 00:16:24,920 --> 00:16:27,960 Speaker 4: of when the first versions of chat GPT, it was 313 00:16:28,040 --> 00:16:30,960 Speaker 4: all people were using it like a Google search query. 314 00:16:31,400 --> 00:16:35,360 Speaker 5: Now it's a conversation. And I think that conversation can 315 00:16:35,400 --> 00:16:36,560 Speaker 5: move from a text. 316 00:16:36,280 --> 00:16:39,680 Speaker 4: Based one to a voice based one with lower latency. 317 00:16:40,320 --> 00:16:42,920 Speaker 1: It's going to be a game change dealing which salesforce 318 00:16:43,640 --> 00:16:47,760 Speaker 1: say they've been able to cope with background noise, distracted callers, 319 00:16:48,560 --> 00:16:50,440 Speaker 1: QWI accent, all that sort of stuff. If we can 320 00:16:50,520 --> 00:16:51,160 Speaker 1: nail all of that. 321 00:16:51,720 --> 00:16:54,240 Speaker 5: Yeah. And also I think talking about the ki. 322 00:16:54,360 --> 00:16:58,080 Speaker 4: Accent, the ability for you to talk in different languages 323 00:16:58,120 --> 00:16:59,520 Speaker 4: and understand each other at the same time. 324 00:17:00,160 --> 00:17:01,600 Speaker 5: How cool is that? 325 00:17:01,960 --> 00:17:05,480 Speaker 4: So you think the possibilities are endless, And I think 326 00:17:05,600 --> 00:17:08,840 Speaker 4: that the voice upgrades is going to be a really 327 00:17:08,840 --> 00:17:09,680 Speaker 4: big feature. 328 00:17:09,400 --> 00:17:11,280 Speaker 5: And it's one of the things I've been talking to. 329 00:17:11,480 --> 00:17:14,280 Speaker 4: Salesforce about over here is how can New Zealand be 330 00:17:14,359 --> 00:17:17,159 Speaker 4: a world first in Talco for the service. 331 00:17:17,240 --> 00:17:19,840 Speaker 5: So you look around here and you look at the brands. 332 00:17:20,280 --> 00:17:22,600 Speaker 4: I am really proud that one New Zealand is the 333 00:17:22,640 --> 00:17:25,240 Speaker 4: only Talco here. But also the way that we get 334 00:17:25,280 --> 00:17:30,080 Speaker 4: the attention of a company like Salesforces by moving a pace. 335 00:17:30,720 --> 00:17:33,679 Speaker 4: And so it's our job to say, serves Salesforce has 336 00:17:33,720 --> 00:17:37,119 Speaker 4: got a cool feature, let's experiment. 337 00:17:36,640 --> 00:17:38,000 Speaker 5: With it and roll it out in New Zealand. 338 00:17:38,000 --> 00:17:41,359 Speaker 1: First, where do you see the other real areas of 339 00:17:41,440 --> 00:17:44,800 Speaker 1: promise for agents across one in z Well? 340 00:17:44,840 --> 00:17:48,000 Speaker 5: I think actually sales is probably the next next area. 341 00:17:48,000 --> 00:17:50,920 Speaker 5: We've been focusing a lot on service. 342 00:17:52,320 --> 00:17:55,879 Speaker 4: But again kind of sales is in the DNA of Salesforce, right, 343 00:17:55,880 --> 00:18:00,240 Speaker 4: It's in the name, and so everything from being able 344 00:18:00,320 --> 00:18:04,600 Speaker 4: to pre qualify leads before our salespeople talk to the 345 00:18:04,640 --> 00:18:06,920 Speaker 4: customer to be able to capture the information I've got 346 00:18:07,000 --> 00:18:10,080 Speaker 4: the customer wants, the size of the business, the complexity, 347 00:18:10,480 --> 00:18:14,479 Speaker 4: and then also do some sales coaching for our teams 348 00:18:15,000 --> 00:18:17,680 Speaker 4: next best action that they might want to take all 349 00:18:17,720 --> 00:18:20,960 Speaker 4: of those things as a tool that can sit beside 350 00:18:21,280 --> 00:18:24,080 Speaker 4: your salesperson to do a lot of the heavy lifting 351 00:18:24,160 --> 00:18:27,159 Speaker 4: before they actually need to talk to the customer, but 352 00:18:27,280 --> 00:18:30,760 Speaker 4: also sales coaching to get higher conversion as part of 353 00:18:30,760 --> 00:18:31,879 Speaker 4: that conversation. 354 00:18:32,560 --> 00:18:33,960 Speaker 5: That's something the next big wave. 355 00:18:34,080 --> 00:18:38,000 Speaker 4: So we've already using salesforce within marketing, we're using salesforce 356 00:18:38,040 --> 00:18:41,600 Speaker 4: within service and that great journeys and now using I 357 00:18:41,600 --> 00:18:46,119 Speaker 4: think salesforce and from a sales perspective, whether it's any segment, 358 00:18:46,160 --> 00:18:51,160 Speaker 4: consumer or small business or large enterprise. That's the next wave. 359 00:18:51,240 --> 00:18:53,200 Speaker 4: And it's proven technology, which. 360 00:18:52,960 --> 00:18:55,400 Speaker 5: Is why we're so excited to roll without. 361 00:18:55,520 --> 00:18:58,440 Speaker 1: Yeah, and you're seeing the return on investment already. 362 00:18:58,119 --> 00:19:01,720 Speaker 5: Across our AI investment five times return wow. Yeah. 363 00:19:01,760 --> 00:19:05,879 Speaker 4: And so we've been deploying AI and all the variations 364 00:19:05,920 --> 00:19:08,760 Speaker 4: of it, so robotic process automation and machine learning for 365 00:19:08,800 --> 00:19:09,639 Speaker 4: over ten years. 366 00:19:09,960 --> 00:19:12,560 Speaker 5: We've only been deploying agentic for last year. 367 00:19:12,359 --> 00:19:15,000 Speaker 4: Because no one even really knew about it twelve months 368 00:19:15,000 --> 00:19:20,640 Speaker 4: twelve months ago. But yeah, five times ROI on our 369 00:19:20,680 --> 00:19:23,200 Speaker 4: AI investment. So we a lot of people are saying 370 00:19:23,720 --> 00:19:26,880 Speaker 4: is the value there? We can see the value absolutely, 371 00:19:27,280 --> 00:19:29,199 Speaker 4: and we think this is just the beginning. 372 00:19:29,240 --> 00:19:29,920 Speaker 5: We want more. 373 00:19:37,240 --> 00:19:40,840 Speaker 1: So there are these early adopters and one inserts a 374 00:19:40,880 --> 00:19:44,440 Speaker 1: real example of that. Jason said, for every dollar he's 375 00:19:44,480 --> 00:19:48,200 Speaker 1: investing in AI, he's already getting a five dollar return 376 00:19:48,280 --> 00:19:51,040 Speaker 1: on that investment. So that's incredible. So where is that 377 00:19:51,119 --> 00:19:55,560 Speaker 1: coming from. That's obviously efficiencies and is it people. It's 378 00:19:55,800 --> 00:19:57,720 Speaker 1: people not having to do all of that work and 379 00:19:57,720 --> 00:19:59,359 Speaker 1: you can deploy them to somewhere else. 380 00:19:59,480 --> 00:20:01,720 Speaker 3: That agent on twenty four to seven and when it launched, 381 00:20:01,720 --> 00:20:03,399 Speaker 3: it launched at four o'clock in the morning, and it 382 00:20:03,480 --> 00:20:05,719 Speaker 3: had nine conversations by the time the core center had 383 00:20:05,720 --> 00:20:08,879 Speaker 3: come alive and nine engagements a week later. We're talking 384 00:20:08,920 --> 00:20:11,919 Speaker 3: about four hundred percent improvement and conversion of plans, you know, 385 00:20:11,960 --> 00:20:14,439 Speaker 3: getting people off old prepaid plans onto the new plans 386 00:20:14,440 --> 00:20:16,760 Speaker 3: that they want to promote, and a four times improvement 387 00:20:17,040 --> 00:20:20,639 Speaker 3: rate on the traditional rate. I know that sounds ironic, 388 00:20:20,640 --> 00:20:23,360 Speaker 3: traditional journey digital journeys that they have by the web. 389 00:20:23,480 --> 00:20:25,000 Speaker 3: I think they've still got the same head count the 390 00:20:25,440 --> 00:20:28,520 Speaker 3: people doing it. So it's augmenting humans to make them 391 00:20:28,520 --> 00:20:30,440 Speaker 3: more efficient and it can be open twenty four seven, 392 00:20:30,440 --> 00:20:32,680 Speaker 3: which as a consumer, that's a great thing. 393 00:20:33,000 --> 00:20:35,240 Speaker 1: What do we need to do in new Zealand to 394 00:20:35,359 --> 00:20:38,080 Speaker 1: address this issue that Mike Benioff raised, you know, in 395 00:20:38,119 --> 00:20:41,520 Speaker 1: his keynote on the first day, this gap between incredible 396 00:20:41,560 --> 00:20:45,240 Speaker 1: innovation that is moving at pace and this sort of 397 00:20:46,200 --> 00:20:49,920 Speaker 1: lag and adoption. The companies are just struggling a little 398 00:20:49,960 --> 00:20:52,560 Speaker 1: bit to keep up. Is it purely an education issue 399 00:20:52,640 --> 00:20:55,800 Speaker 1: or do they not have the confidence and frankly the 400 00:20:55,840 --> 00:20:58,320 Speaker 1: money at the moment and tight times to say we're 401 00:20:58,320 --> 00:20:59,000 Speaker 1: going to invest in this. 402 00:20:59,240 --> 00:21:00,440 Speaker 2: So I'll park the. 403 00:21:00,400 --> 00:21:03,280 Speaker 3: Training sort of side, because I think skills is really important. 404 00:21:03,359 --> 00:21:04,840 Speaker 2: We need more skills in the market. 405 00:21:05,000 --> 00:21:07,960 Speaker 3: But I think there's probably a little bit of reluctance 406 00:21:08,040 --> 00:21:12,040 Speaker 3: to make a start, and I think people think about data, 407 00:21:12,080 --> 00:21:14,480 Speaker 3: but data doesn't have to be perfect. You've probably got 408 00:21:14,600 --> 00:21:17,199 Speaker 3: three areas of data goal bronze, silver and gold and 409 00:21:17,240 --> 00:21:19,359 Speaker 3: your account information. Well that's goal. We want to wrap 410 00:21:19,359 --> 00:21:21,680 Speaker 3: that one. Now, that's true, but marketing messages, et cetera. 411 00:21:21,960 --> 00:21:24,119 Speaker 3: Data doesn't have to be perfect and it never will be. 412 00:21:24,400 --> 00:21:26,200 Speaker 3: And you've worked out on your journey. But I think 413 00:21:26,240 --> 00:21:29,800 Speaker 3: most importantly you can start, make a start because it's 414 00:21:29,840 --> 00:21:32,200 Speaker 3: a low risk entry. Is the agent going to be 415 00:21:32,200 --> 00:21:34,520 Speaker 3: perfect straight away? No, it won't be, But will it 416 00:21:34,600 --> 00:21:37,080 Speaker 3: learn yes, it will. Can we make corrections very quickly, yes, 417 00:21:37,160 --> 00:21:41,240 Speaker 3: I will. So start experimenting, do something internal first before 418 00:21:41,240 --> 00:21:44,720 Speaker 3: you go external, and you'll incremnially keep on improving. And 419 00:21:44,760 --> 00:21:47,200 Speaker 3: I think for New Zelling customers we need to really 420 00:21:47,280 --> 00:21:48,920 Speaker 3: keep moving already. 421 00:21:48,960 --> 00:21:50,440 Speaker 2: Look with this customer, we're seeing. 422 00:21:50,200 --> 00:21:54,240 Speaker 3: Great productivity gains, like great productivity leagain, so it's cost effective. 423 00:21:55,080 --> 00:21:58,720 Speaker 3: It's also seeing revenue increase and productivity. And I think 424 00:21:59,000 --> 00:22:01,520 Speaker 3: it's a pretty strong message to share a New Zealand. 425 00:22:01,720 --> 00:22:05,240 Speaker 1: So you know there's Data three sixty which is data Cloud, 426 00:22:05,320 --> 00:22:08,720 Speaker 1: so that's all been agentized and all that, so it's 427 00:22:08,720 --> 00:22:11,800 Speaker 1: all there. If you want to put your data on Salesforce, 428 00:22:11,840 --> 00:22:13,919 Speaker 1: you can do all of this stuff enable it in 429 00:22:13,920 --> 00:22:15,360 Speaker 1: in a very simple way. A few of the other 430 00:22:15,480 --> 00:22:18,080 Speaker 1: sort of innovative things that I think have come out 431 00:22:18,080 --> 00:22:21,200 Speaker 1: of this week is the move into voice agent Force 432 00:22:21,400 --> 00:22:24,639 Speaker 1: voice so if you can power a voice interaction with 433 00:22:24,680 --> 00:22:28,959 Speaker 1: a customer with an agent's and it'd be a good experience. 434 00:22:29,040 --> 00:22:30,520 Speaker 1: Have you seen that demo. 435 00:22:30,440 --> 00:22:33,520 Speaker 3: Or have you used We've seen it demode and we're 436 00:22:33,560 --> 00:22:35,840 Speaker 3: looking into the first few New Zealand customers to get 437 00:22:35,880 --> 00:22:39,760 Speaker 3: on and start trialing it right and that's happening shortly so, 438 00:22:39,880 --> 00:22:42,320 Speaker 3: but I won't talk about it today, but it's going 439 00:22:42,359 --> 00:22:45,320 Speaker 3: to be really impactful because we want to meet the 440 00:22:45,320 --> 00:22:48,080 Speaker 3: customer where they are in the journey, and quite often 441 00:22:48,119 --> 00:22:50,679 Speaker 3: that's voice. It's a voice conversation, could be a text, 442 00:22:50,760 --> 00:22:52,560 Speaker 3: and it could be a digital channel, and it could 443 00:22:52,560 --> 00:22:54,800 Speaker 3: be an agent, but more often than not, a still voice. 444 00:22:54,840 --> 00:22:57,159 Speaker 3: It's I think seventy eighty percent for some businesses that 445 00:22:57,160 --> 00:22:59,960 Speaker 3: are coming in and protectingly for telcos. 446 00:23:00,160 --> 00:23:01,880 Speaker 2: Thin think about having a digital twin. 447 00:23:01,920 --> 00:23:05,360 Speaker 3: If you're in the contact center, my name's Maddie, and 448 00:23:05,720 --> 00:23:07,880 Speaker 3: I create a digital twin that's on twenty four to seven. 449 00:23:08,240 --> 00:23:10,840 Speaker 3: I can have a personal relationship with you, Peter, twenty 450 00:23:10,840 --> 00:23:12,600 Speaker 3: four seven. I don't even have to be at work 451 00:23:12,720 --> 00:23:15,240 Speaker 3: and to answer some of your questions, and so you 452 00:23:15,240 --> 00:23:18,000 Speaker 3: actually feel like you will have a personalized service with 453 00:23:18,119 --> 00:23:21,040 Speaker 3: your digital assistant who has actually got a human behind it. 454 00:23:21,280 --> 00:23:22,800 Speaker 3: That I think for a lot of people will be 455 00:23:22,880 --> 00:23:25,800 Speaker 3: very very good experience and quite comforting to have that 456 00:23:25,840 --> 00:23:27,760 Speaker 3: consistent service because you know when you ring up, you're 457 00:23:27,800 --> 00:23:28,720 Speaker 3: a different person every time. 458 00:23:28,760 --> 00:23:30,360 Speaker 2: Now I want to speak to Maddie. 459 00:23:30,520 --> 00:23:32,680 Speaker 1: Yeah, it's going to be interesting to see it at scale, 460 00:23:33,040 --> 00:23:34,399 Speaker 1: particularly with the Kiwi accent. 461 00:23:34,480 --> 00:23:37,879 Speaker 3: How Yeah, So that is a really because that's when 462 00:23:37,920 --> 00:23:40,119 Speaker 3: you get into you know, people talk about large language 463 00:23:40,119 --> 00:23:43,119 Speaker 3: models and contextual stuff, so that accent, that stuff is 464 00:23:43,119 --> 00:23:45,960 Speaker 3: going to be really important. But also picking up other 465 00:23:46,240 --> 00:23:48,119 Speaker 3: languages as well. You know in New Zealand we just 466 00:23:48,240 --> 00:23:51,920 Speaker 3: you know have TODAYO and we have all those languages 467 00:23:51,960 --> 00:23:55,160 Speaker 3: from all the people come from other parts of the world. Yeah, 468 00:23:55,160 --> 00:23:58,080 Speaker 3: pacifica language in Latin America, Asia. 469 00:23:58,680 --> 00:23:59,800 Speaker 2: Yeah, it's going to be interesting. 470 00:24:00,040 --> 00:24:02,160 Speaker 1: That is going to be really interesting. A couple other 471 00:24:02,200 --> 00:24:06,920 Speaker 1: things move into it service management. You know, that's obviously 472 00:24:07,440 --> 00:24:09,960 Speaker 1: was a bit of a gap there, but as Bennyov said, 473 00:24:10,000 --> 00:24:15,320 Speaker 1: you know from it query support, queries, organizing field staff, technicians, 474 00:24:15,320 --> 00:24:17,000 Speaker 1: all of that sort of thing that's an area Service 475 00:24:17,040 --> 00:24:19,520 Speaker 1: now is really good at. But it is going to 476 00:24:19,520 --> 00:24:21,760 Speaker 1: be possible now on the Salesforce platform. 477 00:24:21,480 --> 00:24:23,520 Speaker 3: Too, you know, because we've always been sales service and 478 00:24:23,520 --> 00:24:27,320 Speaker 3: marketing very externally focusing. It's not that much different from 479 00:24:27,359 --> 00:24:30,800 Speaker 3: our service operations and you know, raising tickets and distributing, 480 00:24:30,840 --> 00:24:33,480 Speaker 3: so it's quite a natural adjacency for us to enter 481 00:24:33,880 --> 00:24:37,320 Speaker 3: and it's going to give customers that singular platform opportunity 482 00:24:37,440 --> 00:24:39,800 Speaker 3: if I raise a field service ticket or I raise 483 00:24:39,800 --> 00:24:42,439 Speaker 3: a ticket which turns into a field service action. You know, 484 00:24:42,520 --> 00:24:44,960 Speaker 3: that could be a tech person or it could be 485 00:24:45,000 --> 00:24:47,760 Speaker 3: a contractor. And as a consumer, I don't really care. 486 00:24:48,000 --> 00:24:49,679 Speaker 3: I just want that service, and I think that we 487 00:24:49,840 --> 00:24:52,240 Speaker 3: lean naturally into that, so you know, it's a great 488 00:24:52,240 --> 00:24:53,280 Speaker 3: option for our customers. 489 00:24:53,280 --> 00:24:57,000 Speaker 1: Any use cases you saw as you walked around Agent 490 00:24:57,040 --> 00:25:00,600 Speaker 1: Force City downstairs that you thought, Wow, that's its pretty cool. 491 00:25:00,760 --> 00:25:03,440 Speaker 3: I've enjoyed, and excuse the pun here, watching the journey 492 00:25:03,440 --> 00:25:06,399 Speaker 3: of Heathrow Airport. You know, I've been on planes and 493 00:25:06,480 --> 00:25:11,000 Speaker 3: thought I've missed a gift opportunity for family member that 494 00:25:11,119 --> 00:25:14,040 Speaker 3: might have had a birthday or something like that, a 495 00:25:14,160 --> 00:25:16,560 Speaker 3: moment in their life that I so the opportunity to 496 00:25:16,560 --> 00:25:20,080 Speaker 3: interact with their agent. Also know, I need a gift 497 00:25:20,600 --> 00:25:22,200 Speaker 3: and I need to go to Judy Free. Can you 498 00:25:22,280 --> 00:25:24,320 Speaker 3: have that ready for me? And I'm running late already 499 00:25:24,920 --> 00:25:28,320 Speaker 3: and having that shopping consumer experience at the airport making 500 00:25:28,400 --> 00:25:30,399 Speaker 3: life really easy. And also like once say no, I 501 00:25:30,480 --> 00:25:34,000 Speaker 3: booked publishing data, pushing data to meet your flight's on time. 502 00:25:34,280 --> 00:25:36,320 Speaker 3: It's going to be at this gate. Oh, by the way, 503 00:25:36,320 --> 00:25:39,600 Speaker 3: we've changed the gate. Just making life easy at an airport, 504 00:25:39,600 --> 00:25:42,080 Speaker 3: because airports can be stressful. Yeah, I just think that's 505 00:25:42,119 --> 00:25:43,000 Speaker 3: a wonderful story. 506 00:25:43,240 --> 00:25:49,280 Speaker 1: Yeah, and many the what I've seen, like Chicago Medical University, 507 00:25:49,840 --> 00:25:52,960 Speaker 1: a huge health provided as four billion dollars in revenue, 508 00:25:53,200 --> 00:25:56,080 Speaker 1: and like us in New Zealand, they're using patient portals. 509 00:25:56,160 --> 00:25:58,800 Speaker 1: You can you can get all of that, but every 510 00:25:58,800 --> 00:26:01,280 Speaker 1: time you so you need to talk to your doctor 511 00:26:01,359 --> 00:26:03,639 Speaker 1: or a nurse, it's sometimes it's by a text message, 512 00:26:03,640 --> 00:26:06,400 Speaker 1: sometimes it's a phone call, sometimes it's an email. It's 513 00:26:06,440 --> 00:26:10,120 Speaker 1: just all scattered. Bringing that all into one interface where 514 00:26:10,119 --> 00:26:13,880 Speaker 1: you can query it through chat. They just think it's 515 00:26:13,920 --> 00:26:16,679 Speaker 1: going to cut their call volumes by seventy percent. 516 00:26:16,760 --> 00:26:18,600 Speaker 3: I can play that foward to that digital twins. So 517 00:26:18,680 --> 00:26:21,160 Speaker 3: the person that's with you on that journey. Yeah, because 518 00:26:21,160 --> 00:26:24,080 Speaker 3: sometimes when people go through these procedures, Yeah, very stressful, 519 00:26:24,160 --> 00:26:26,920 Speaker 3: lots of information, someone coaching you through. Yes, your appointments 520 00:26:26,960 --> 00:26:29,199 Speaker 3: here in two days, you're going to be this. This 521 00:26:29,240 --> 00:26:30,520 Speaker 3: is what they're going to be talking about. This is 522 00:26:30,560 --> 00:26:33,160 Speaker 3: what was talked about in the session. Yeah, So it's 523 00:26:33,359 --> 00:26:35,800 Speaker 3: I think I said it. I think we're I'm not 524 00:26:35,840 --> 00:26:37,879 Speaker 3: even sure we're scratching the surface yet. I mean, I 525 00:26:37,880 --> 00:26:39,560 Speaker 3: think the opportunity is going to be huge and when 526 00:26:39,560 --> 00:26:41,160 Speaker 3: we sit here in ten years time, we'll look back 527 00:26:41,200 --> 00:26:43,520 Speaker 3: and go, Wow, what a start. Yeah. 528 00:26:43,600 --> 00:26:46,639 Speaker 1: And you know, we touched on the capability issue and 529 00:26:46,640 --> 00:26:49,320 Speaker 1: the training issue, and I think that is a bit 530 00:26:49,359 --> 00:26:52,040 Speaker 1: of a gap, particularly in New Zealand. I mean there 531 00:26:52,160 --> 00:26:54,119 Speaker 1: is this perception it's all sort of vibe coding. You 532 00:26:54,119 --> 00:26:56,919 Speaker 1: don't need that much expertise to do it, but you 533 00:26:57,000 --> 00:26:58,880 Speaker 1: sort of do to do it properly and to put 534 00:26:58,920 --> 00:27:01,359 Speaker 1: in the right governance around it, and just have the 535 00:27:01,400 --> 00:27:04,320 Speaker 1: confidence across the business for people to go I want 536 00:27:04,359 --> 00:27:07,360 Speaker 1: to go in this journey. And what I've learned this week, 537 00:27:07,400 --> 00:27:09,439 Speaker 1: it's got to be from the leadership of the company 538 00:27:09,440 --> 00:27:11,280 Speaker 1: saying we are going to be in like Jason Paris 539 00:27:11,320 --> 00:27:13,560 Speaker 1: and said, we're going to be in AI centric talco 540 00:27:13,600 --> 00:27:15,199 Speaker 1: and the first one in New Zealand. To do it, 541 00:27:15,480 --> 00:27:17,320 Speaker 1: you sort of have to have that approach. What do 542 00:27:17,359 --> 00:27:18,320 Speaker 1: we need to do to get there? 543 00:27:18,359 --> 00:27:21,119 Speaker 3: In New Zealand we have a skills gap and the 544 00:27:21,160 --> 00:27:23,240 Speaker 3: tech sector and I think some support around that would 545 00:27:23,240 --> 00:27:25,879 Speaker 3: be amazing. Lo we have all these programs online and 546 00:27:25,960 --> 00:27:28,600 Speaker 3: probably the entire industry feels the same way. So some 547 00:27:28,680 --> 00:27:32,199 Speaker 3: assistance in getting more people into the tech secer, and 548 00:27:32,240 --> 00:27:34,879 Speaker 3: we know it transforms people's lives, right, they can go 549 00:27:34,920 --> 00:27:37,320 Speaker 3: from minimum wage to double that quite quickly. 550 00:27:37,359 --> 00:27:38,280 Speaker 2: So that's one aspect. 551 00:27:38,320 --> 00:27:40,879 Speaker 3: And I think to your point around what do New 552 00:27:40,960 --> 00:27:43,960 Speaker 3: Zealand companies need to do, You're absolutely right. Leadership needs 553 00:27:43,960 --> 00:27:45,159 Speaker 3: to come from the top. And if you look at 554 00:27:45,200 --> 00:27:48,679 Speaker 3: any successful transformation project over the last ten to twenty 555 00:27:48,760 --> 00:27:51,560 Speaker 3: years in technology, the one core ingredient that I had 556 00:27:51,600 --> 00:27:54,560 Speaker 3: that it got right was governance, and leadership came from 557 00:27:54,560 --> 00:27:55,959 Speaker 3: the top. If you look at all the ones that 558 00:27:55,960 --> 00:27:58,320 Speaker 3: have missed and delayed, and you know there is a 559 00:27:58,480 --> 00:28:02,240 Speaker 3: graveyard of transformation projects that have missed their deadlines, they 560 00:28:02,280 --> 00:28:05,200 Speaker 3: have a common theme that the leadership wasn't all on board. 561 00:28:05,640 --> 00:28:06,679 Speaker 2: I think as we move into. 562 00:28:06,560 --> 00:28:10,160 Speaker 3: The surgetic enterprise, it'll break down the silos of how 563 00:28:10,200 --> 00:28:14,119 Speaker 3: we work. You know, relationships will become absolutely critical. What 564 00:28:14,200 --> 00:28:17,800 Speaker 3: does the agent do, which is really task and function 565 00:28:17,920 --> 00:28:20,679 Speaker 3: and high processes and orientated to what do the humans 566 00:28:20,680 --> 00:28:25,240 Speaker 3: do then, which is relationships, empathy, context and that constant 567 00:28:25,280 --> 00:28:30,960 Speaker 3: training and oversight. So governance leadership really important and. 568 00:28:29,920 --> 00:28:32,600 Speaker 1: We just need to start I mean it's still pretty 569 00:28:32,640 --> 00:28:37,960 Speaker 1: soft in New Zealand's economically hoping we'll turn our coin 570 00:28:38,080 --> 00:28:40,960 Speaker 1: interest in what you're seeing, I mean that rich data 571 00:28:41,040 --> 00:28:43,960 Speaker 1: coming from your customers as to how they're doing, and 572 00:28:45,400 --> 00:28:47,440 Speaker 1: there seems to be an opportunity here to cut cost, 573 00:28:47,840 --> 00:28:52,160 Speaker 1: to use salesforce and agents to actually take some costs 574 00:28:52,160 --> 00:28:53,840 Speaker 1: out of your business, which is what they need to 575 00:28:53,880 --> 00:28:54,440 Speaker 1: do at the moment. 576 00:28:54,800 --> 00:28:57,920 Speaker 3: Everyone's quite cost conscious, but they're also productivity oritented. So 577 00:28:58,240 --> 00:29:01,000 Speaker 3: how do you do both? And I think the opportunity 578 00:29:01,280 --> 00:29:03,600 Speaker 3: is that you know we can. You can reduce cost, 579 00:29:03,800 --> 00:29:07,320 Speaker 3: you can increase your productivity, and typically that means improving 580 00:29:07,320 --> 00:29:08,120 Speaker 3: your top line. 581 00:29:08,280 --> 00:29:09,000 Speaker 2: I think you're right. 582 00:29:09,040 --> 00:29:11,400 Speaker 3: I think you know there's no secret that the economy 583 00:29:11,440 --> 00:29:13,440 Speaker 3: is sort of bouncing around a wee bit at the moment. 584 00:29:13,440 --> 00:29:16,040 Speaker 3: We're hoping to see it continue to improve. But the 585 00:29:16,080 --> 00:29:19,280 Speaker 3: customers that we've got that are embracing the agentic journey 586 00:29:19,280 --> 00:29:21,600 Speaker 3: are seeing some pretty good results early in the piece, 587 00:29:21,600 --> 00:29:23,520 Speaker 3: which is encouraging. And I would love to see more 588 00:29:23,520 --> 00:29:25,880 Speaker 3: of New Zealand. I think we New Zealand can lift 589 00:29:25,920 --> 00:29:28,280 Speaker 3: if we embrace this agentic journey. Yeah, because you will 590 00:29:28,320 --> 00:29:30,320 Speaker 3: get cost out and you will get productivity up and 591 00:29:30,360 --> 00:29:31,400 Speaker 3: you probably get revenue up. 592 00:29:31,400 --> 00:29:33,520 Speaker 1: It's good to see the governments just put seventy million 593 00:29:33,600 --> 00:29:38,000 Speaker 1: into literally asking for AI centric projects through the new 594 00:29:38,040 --> 00:29:42,000 Speaker 1: Advanced Technology Institute, which is the first big investment in 595 00:29:42,080 --> 00:29:45,520 Speaker 1: AI at a government levels. That so, I guess is compelling. 596 00:29:45,880 --> 00:29:46,480 Speaker 2: Yeah, and I. 597 00:29:46,400 --> 00:29:50,080 Speaker 3: Think we need to continue that push for training, right, 598 00:29:50,200 --> 00:29:52,160 Speaker 3: training and skills in the industry because that will help 599 00:29:52,240 --> 00:29:54,880 Speaker 3: New Zealand lift that will benefit all of our businesses, 600 00:29:55,320 --> 00:30:00,080 Speaker 3: central government, the vendor, community, partners and you know, the 601 00:30:00,120 --> 00:30:01,000 Speaker 3: community in the end. 602 00:30:01,200 --> 00:30:01,720 Speaker 2: Yeah. 603 00:30:02,080 --> 00:30:04,680 Speaker 1: Just finally, the other thing that struck me this week 604 00:30:04,800 --> 00:30:06,120 Speaker 1: is around Slack. 605 00:30:06,320 --> 00:30:07,760 Speaker 2: Oh yeah, this is cool. 606 00:30:07,880 --> 00:30:11,080 Speaker 1: Yeah, and Slack sort of being like I've used it 607 00:30:11,560 --> 00:30:14,800 Speaker 1: not in the salesforce domain, but you know, as a 608 00:30:14,800 --> 00:30:17,840 Speaker 1: lot of media companies use slack great for messaging, but 609 00:30:17,880 --> 00:30:20,280 Speaker 1: it's become more than that, hasn't. It's become the front 610 00:30:20,360 --> 00:30:23,280 Speaker 1: end really of sales. That's quite what it was originally 611 00:30:23,280 --> 00:30:26,200 Speaker 1: found for. But right now it's the central console for 612 00:30:26,240 --> 00:30:27,520 Speaker 1: people to go and get their work. 613 00:30:27,840 --> 00:30:28,000 Speaker 2: Now. 614 00:30:28,040 --> 00:30:29,880 Speaker 3: I made a quote earlier two before, you know, two 615 00:30:29,960 --> 00:30:32,440 Speaker 3: hundred and thirteen agents, five hundred and fifty tasks. I 616 00:30:32,440 --> 00:30:34,720 Speaker 3: got that through Slack because Jason was asking me a question. 617 00:30:34,720 --> 00:30:36,280 Speaker 3: He goes, how many agents you've got? I went, so 618 00:30:36,280 --> 00:30:38,479 Speaker 3: I went to slack pot, which I'm now using more 619 00:30:38,520 --> 00:30:42,760 Speaker 3: than Gemini to ask questions about internally, how many agents 620 00:30:42,760 --> 00:30:42,960 Speaker 3: we have. 621 00:30:43,000 --> 00:30:43,560 Speaker 2: What are they doing? 622 00:30:43,640 --> 00:30:47,280 Speaker 3: So we're surfacing all that Argentic layer through Slack. Now 623 00:30:47,320 --> 00:30:49,400 Speaker 3: that won't be just us, you know, we've got partnerships 624 00:30:49,400 --> 00:30:52,760 Speaker 3: with work Day and Slack will become that console for 625 00:30:53,160 --> 00:30:54,720 Speaker 3: where you go to get that information. 626 00:30:55,200 --> 00:30:57,960 Speaker 1: Is New Zealand a big, big market for Slack? 627 00:30:58,000 --> 00:30:59,640 Speaker 2: Are there a lot of customers there? Yeah, we have 628 00:30:59,680 --> 00:31:00,720 Speaker 2: some great customers. 629 00:31:00,760 --> 00:31:03,959 Speaker 3: I think Zero is a huge user of Slack, huge 630 00:31:04,120 --> 00:31:05,800 Speaker 3: user and there've been a reference for us for a 631 00:31:05,840 --> 00:31:08,520 Speaker 3: while McCloud cranes. Right, So then the other end of 632 00:31:08,560 --> 00:31:12,160 Speaker 3: the scale in the ESMB space an organization out there 633 00:31:12,160 --> 00:31:15,040 Speaker 3: lifting and shifting parts of New Zealand around with cranes. 634 00:31:15,440 --> 00:31:17,960 Speaker 3: So it's something that can fact any price that we 635 00:31:18,000 --> 00:31:21,200 Speaker 3: have Ryman homes and you know when they change rooms around, 636 00:31:21,240 --> 00:31:24,480 Speaker 3: they use that Slack as their workflow when they start 637 00:31:24,840 --> 00:31:28,520 Speaker 3: updating their villages. Yeah, yeah, it's cool. So that has 638 00:31:28,640 --> 00:31:31,120 Speaker 3: come a long way. Yeah, Okay, well good luck. 639 00:31:31,160 --> 00:31:33,720 Speaker 1: It's going to be really interesting to see in it 640 00:31:33,800 --> 00:31:37,160 Speaker 1: twelve months time, where the heck we're at Given what's 641 00:31:37,240 --> 00:31:39,320 Speaker 1: changed in the last year, it's. 642 00:31:39,720 --> 00:31:40,600 Speaker 2: In the next twelve months. 643 00:31:40,640 --> 00:31:43,360 Speaker 3: What I'd love to see is the multiple agents and 644 00:31:43,400 --> 00:31:46,560 Speaker 3: the orchestration of work, and then the human and agent 645 00:31:46,760 --> 00:31:49,560 Speaker 3: collaboration going on, and those journeys as they spread across 646 00:31:49,600 --> 00:31:52,000 Speaker 3: the enterprise. It's just going to go deeper and wider. 647 00:31:52,400 --> 00:31:56,200 Speaker 3: I think the numbers that we're seeing early now are fascinating, 648 00:31:56,320 --> 00:31:57,800 Speaker 3: just fascinating. So what is it going to be in 649 00:31:57,800 --> 00:32:00,160 Speaker 3: twelve months. I think we're going to be in for 650 00:32:00,240 --> 00:32:01,640 Speaker 3: some really great surprises. 651 00:32:01,720 --> 00:32:04,280 Speaker 1: Well, let's revisit then and see where we're at. 652 00:32:04,360 --> 00:32:05,040 Speaker 2: It has to come back. 653 00:32:05,280 --> 00:32:07,800 Speaker 3: This is my fourth one on the bounce, and I think, 654 00:32:08,320 --> 00:32:11,080 Speaker 3: far away the best one I've been giant leaps every 655 00:32:11,120 --> 00:32:11,560 Speaker 3: time it's in. 656 00:32:12,120 --> 00:32:12,320 Speaker 2: Yeah. 657 00:32:12,600 --> 00:32:15,920 Speaker 3: Yeah, also really satisfying to see our customers going so well, 658 00:32:15,960 --> 00:32:16,560 Speaker 3: like it's just. 659 00:32:16,520 --> 00:32:19,440 Speaker 2: A real us kiwis. It's a really proud moment. 660 00:32:19,640 --> 00:32:22,000 Speaker 1: Right, Okay, Hey, well thanks for coming back on the 661 00:32:22,040 --> 00:32:24,000 Speaker 1: Business of Tech and we'll see any years time. 662 00:32:24,080 --> 00:32:25,480 Speaker 2: Yeah, thanks Peter, thank you. 663 00:32:33,240 --> 00:32:35,720 Speaker 1: So my head was spending after a week immersed in 664 00:32:35,800 --> 00:32:39,000 Speaker 1: the agentic enterprise, I definitely felt I got a lot 665 00:32:39,040 --> 00:32:41,880 Speaker 1: more of a handle on the tangible things AI agents 666 00:32:41,920 --> 00:32:46,000 Speaker 1: can now achieve. It's plenty of hype at Dreamforce. It's 667 00:32:46,040 --> 00:32:50,880 Speaker 1: basically a sales organization at height, but this agentic wave 668 00:32:51,120 --> 00:32:55,920 Speaker 1: is coming for businesses Salesforce, customer or not. Every organization 669 00:32:55,960 --> 00:32:58,280 Speaker 1: needs to figure out what that means for them. And 670 00:32:58,320 --> 00:33:01,960 Speaker 1: when we do have AI centric companies that are automating 671 00:33:01,960 --> 00:33:04,400 Speaker 1: more and more of the work many people do, it 672 00:33:04,480 --> 00:33:07,040 Speaker 1: is going to have serious consequences for the workforce, which 673 00:33:07,040 --> 00:33:10,040 Speaker 1: I don't think we fully appreciate yet. There's only so 674 00:33:10,120 --> 00:33:13,680 Speaker 1: much augmenting of tasks that will be done before agents 675 00:33:13,760 --> 00:33:18,360 Speaker 1: really do eat into certain roles. It's just a matter 676 00:33:18,400 --> 00:33:21,560 Speaker 1: of when that happens and how quickly. So I thought 677 00:33:21,560 --> 00:33:25,760 Speaker 1: i'd finish off the podcast with this particularly insightful comment 678 00:33:25,800 --> 00:33:29,680 Speaker 1: from Pete butodhage Edge, who rounded out Dreamforce with a 679 00:33:29,720 --> 00:33:34,000 Speaker 1: really nice discussion about AI, about keeping our purpose in 680 00:33:34,040 --> 00:33:36,720 Speaker 1: mind when we develop AI, what are we really doing 681 00:33:36,760 --> 00:33:39,160 Speaker 1: all of this activity for and who does it serve? 682 00:33:39,520 --> 00:33:42,600 Speaker 6: Anyway, here's Pete footage Edge. I imagine a machine that 683 00:33:42,720 --> 00:33:45,520 Speaker 6: could do more and more things picture like the replicator 684 00:33:45,600 --> 00:33:48,920 Speaker 6: from Star Trek, like you can basically make everything, and 685 00:33:49,120 --> 00:33:53,080 Speaker 6: the more sophisticated the machine gets, the fewer people you 686 00:33:53,120 --> 00:33:56,360 Speaker 6: need to work in until one day all you really 687 00:33:56,440 --> 00:33:59,160 Speaker 6: need is just one guy to push a button and 688 00:33:59,240 --> 00:34:03,160 Speaker 6: the machine can do everything else. And where that leads 689 00:34:03,200 --> 00:34:08,120 Speaker 6: you is the wages that that worker can command, according 690 00:34:08,120 --> 00:34:11,400 Speaker 6: to economic theory, fall towards zero. And all that actually 691 00:34:11,400 --> 00:34:14,719 Speaker 6: matters is who owns the machine. If we come out 692 00:34:14,719 --> 00:34:16,719 Speaker 6: of the thought experiment, what is the machine? It's the 693 00:34:16,760 --> 00:34:21,320 Speaker 6: intellectual property, it's the software, it's the physical plant, the compute, 694 00:34:21,680 --> 00:34:24,000 Speaker 6: all of those things that add up into these firms 695 00:34:24,080 --> 00:34:24,799 Speaker 6: right that are doing this. 696 00:34:25,360 --> 00:34:27,160 Speaker 7: And I think there is a question of how some 697 00:34:27,239 --> 00:34:31,200 Speaker 7: of that ownership gets shared in a broader way, some 698 00:34:31,280 --> 00:34:34,040 Speaker 7: kind of dividend that might come to the American people, 699 00:34:34,040 --> 00:34:37,160 Speaker 7: for example, which I think is fair game, given that we, 700 00:34:37,440 --> 00:34:40,240 Speaker 7: the American taxpayer, kind of sort of invented the Internet 701 00:34:41,440 --> 00:34:43,600 Speaker 7: and that these models trained on our data. Right, So 702 00:34:43,640 --> 00:34:46,440 Speaker 7: there's an economic conversation that we need to have that 703 00:34:47,000 --> 00:34:49,279 Speaker 7: respects the dignity of the role that humans played in 704 00:34:49,320 --> 00:34:50,480 Speaker 7: creating this technology. 705 00:34:53,239 --> 00:34:55,880 Speaker 1: That's it for the Business of Tech Powered by two Greece. 706 00:34:55,960 --> 00:34:58,840 Speaker 1: Thanks so much to Hamish Miles for having me at 707 00:34:58,920 --> 00:35:01,840 Speaker 1: Dreamforce again and coming back on the podcast. Thanks to 708 00:35:02,000 --> 00:35:05,000 Speaker 1: Jason Parris from one in Z we're giving us those 709 00:35:05,000 --> 00:35:08,160 Speaker 1: insights into how one in d ed is rolling out 710 00:35:08,520 --> 00:35:13,200 Speaker 1: a Genticai to really good effect. Show notes her at Businessdesk, 711 00:35:13,200 --> 00:35:16,160 Speaker 1: dot co, dot NZED. You'll find them in the podcast section, 712 00:35:16,480 --> 00:35:19,920 Speaker 1: and of course you can stream the podcast from iHeartRadio 713 00:35:20,520 --> 00:35:23,319 Speaker 1: or in your favorite podcast app. Next week, got a 714 00:35:23,320 --> 00:35:26,359 Speaker 1: really nice episode for you. Sir Peter Beck comes back 715 00:35:26,440 --> 00:35:30,479 Speaker 1: on the show, reflecting on twenty years of rocket Lab. Yes, 716 00:35:30,880 --> 00:35:33,480 Speaker 1: the anniversary is just around the corner, twenty years of 717 00:35:33,520 --> 00:35:36,759 Speaker 1: one of our most famous successful tech companies. I've just 718 00:35:36,760 --> 00:35:40,719 Speaker 1: written a book that has three hundred beautiful pages from 719 00:35:40,800 --> 00:35:44,600 Speaker 1: the history off rocket Lab that's going out next week 720 00:35:44,640 --> 00:35:48,480 Speaker 1: as well, and so great to have Sir Peter to 721 00:35:48,560 --> 00:35:54,000 Speaker 1: reflect on that as he prepares for the launch off Neutron. 722 00:35:54,719 --> 00:35:56,800 Speaker 1: Tune in next week for another episode of the Business 723 00:35:56,800 --> 00:35:58,239 Speaker 1: of Tech. I'll catch you then,