WEBVTT 00:00:00.650 --> 00:00:02.477 [music] 00:00:02.560 --> 00:00:05.677 Bloomberg Audio Studios, podcasts, 00:00:05.760 --> 00:00:10.157 radio, news. >> Accenture and Anthropic inking a 00:00:10.240 --> 00:00:14.077 multi-year partnership deal to drive enterprise AI adoption. The two, they're 00:00:14.160 --> 00:00:17.997 going to form the Accenture Anthropic business group with the goal of training 00:00:18.080 --> 00:00:20.237 around 30,000 professionals in 00:00:20.320 --> 00:00:23.757 leveraging AI as a catalyst for 00:00:23.840 --> 00:00:25.837 reinvention. pleased to say joining us 00:00:25.920 --> 00:00:28.157 right now is the CEO of Accenture, Julia 00:00:28.240 --> 00:00:32.157 Julie, and the CEO of Anthropic, Daario 00:00:32.240 --> 00:00:33.917 Amade. Great to have both of you here. 00:00:34.000 --> 00:00:38.077 Uh, and Julie, I'll start with you. Uh, mainly because when I saw this, I 00:00:38.160 --> 00:00:40.957 thought, "Wow, this is neat." Then I also thought about the fact that just 00:00:41.040 --> 00:00:44.237 last week you announced a further expansion of your partnership with 00:00:44.320 --> 00:00:48.477 OpenAI. Talk a little bit about how these two coexists under the Accenture 00:00:48.560 --> 00:00:52.637 umbrella. >> Sure. So, um, all of our partnerships 00:00:52.720 --> 00:00:56.397 start with client demand. So the partnerships are responding to client 00:00:56.480 --> 00:01:01.277 demand and we have a long history. Our clients expect us to be the number one 00:01:01.360 --> 00:01:06.317 partner for every technology company that matters and uh Enthropic this 00:01:06.400 --> 00:01:08.157 partnership that we've announced today 00:01:08.240 --> 00:01:10.557 is uh very important to our clients. And 00:01:10.640 --> 00:01:13.357 so that's the role we play is to make 00:01:13.440 --> 00:01:15.357 sure that we can take the world's best 00:01:15.440 --> 00:01:19.117 technology and mix it up with industry 00:01:19.200 --> 00:01:23.837 knowledge with process and how to actually use it in the enterprise to get 00:01:23.920 --> 00:01:25.997 to an outcome. And as you know today 00:01:26.080 --> 00:01:28.717 it's all about when is AI showing up in 00:01:28.800 --> 00:01:31.277 the P&L. We call that the P&L pivot and 00:01:31.360 --> 00:01:35.757 this partnership uh will help our clients make that pivot. Well, I am 00:01:35.840 --> 00:01:39.037 curious then Dario if you can kind of talk about specifically the anthropic 00:01:39.120 --> 00:01:41.997 tools, the idea here uh of standardizing 00:01:42.080 --> 00:01:46.397 how some of these AI agents actually connect to uh the various uh uh 00:01:46.480 --> 00:01:47.837 tentacles if you will, the various 00:01:47.920 --> 00:01:50.637 applications out there. 00:01:50.720 --> 00:01:53.837 >> Um yes, so we are um uh you know I think 00:01:53.920 --> 00:01:56.157 we're going to start on the coding side. 00:01:56.240 --> 00:01:59.917 Some of the technologies that have been adopted quickly have been uh uh things 00:02:00.000 --> 00:02:04.477 like uh claude code the the the um tool tool we produce to help with development 00:02:04.560 --> 00:02:08.157 and we've seen very large productivity gains with that but we want to go beyond 00:02:08.240 --> 00:02:12.477 that to more general use of our tool uh claude and we want to drive usage of the 00:02:12.560 --> 00:02:15.117 tool across areas like healthcare um 00:02:15.200 --> 00:02:19.757 life sciences financial services public sector you know things that anthropic 00:02:19.840 --> 00:02:24.237 has worked with for a long time you know more broadly I would say that uh 00:02:24.320 --> 00:02:29.197 enterprises have been experimenting with AI for quite a while, but uh you know I 00:02:29.280 --> 00:02:32.717 think really you know as Julie said with the with the P&L the the important thing 00:02:32.800 --> 00:02:37.917 is really to deploy these at scale and you know to actually drive ROI for them. 00:02:38.000 --> 00:02:39.357 And so that's what we're trying to do. 00:02:39.440 --> 00:02:43.277 That's why we have this whole business center. That's why we're training 30,000 00:02:43.360 --> 00:02:45.837 people to use Claude. And we're going to 00:02:45.920 --> 00:02:48.797 work with CIOS of companies to track how 00:02:48.880 --> 00:02:53.277 how how they're using uh Claude through Accenture, how they're uh deploying the 00:02:53.360 --> 00:02:56.397 tools, what returns they're getting, what returns they're getting from the 00:02:56.480 --> 00:02:59.437 tools. So, we're going to work with Accenture to manage the whole life 00:02:59.520 --> 00:03:01.997 cycle. We think these tools are are are 00:03:02.080 --> 00:03:06.637 are revolutionary. We've seen that from their use inside Anthropic and many 00:03:06.720 --> 00:03:10.717 enterprises already. [snorts] But, uh, the thing we're most excited for is is 00:03:10.800 --> 00:03:14.157 to make sure that, you know, we can we can really, uh, uh, spread these across 00:03:14.240 --> 00:03:17.597 the enterprise world. And, you know, that's that's where Accenture comes in 00:03:17.680 --> 00:03:20.797 and can really drive these things at a scale that hasn't been done before. 00:03:20.880 --> 00:03:22.317 >> Yeah, it's interesting, Dario. I mean, 00:03:22.400 --> 00:03:24.797 you think about AI, some of these uh, 00:03:24.880 --> 00:03:27.997 LLMs, they're very popular with 00:03:28.080 --> 00:03:31.997 consumers, individuals. Uh, they've been well socialized. But when it comes to 00:03:32.080 --> 00:03:35.757 enterprises, when it comes to that business customer, you touched on maybe 00:03:35.840 --> 00:03:38.157 some of the skepticisms that CIOS have 00:03:38.240 --> 00:03:41.597 in really adopting AI as you look into 00:03:41.680 --> 00:03:46.237 2026, this deal with Accenture. Uh how much further does it put you when it 00:03:46.320 --> 00:03:49.837 comes to sort of unlocking the enterprise world and what's the goal 00:03:49.920 --> 00:03:52.477 when it comes to 2026? 00:03:52.560 --> 00:03:54.957 >> Yes. So, um you know, we we've already 00:03:55.040 --> 00:03:57.197 seen substantial enterprise adoption. 00:03:57.280 --> 00:04:02.157 This year, Anthropics revenue went from 1 billion uh annualized rate at the 00:04:02.240 --> 00:04:05.437 beginning of the year to 10 billion annualized rate at the end of the year. 00:04:05.520 --> 00:04:09.837 Um, so we've already seen a lot of adoption and you know 80 80% of that 00:04:09.920 --> 00:04:13.437 revenue is enterprise and within that particularly with things like coding but 00:04:13.520 --> 00:04:18.157 in other areas we're we're starting to see very strong ROI but the scale of 00:04:18.240 --> 00:04:22.317 this is so large right the scale of what needs to be done right there's hundreds 00:04:22.400 --> 00:04:24.957 of billions maybe trillions of of you 00:04:25.040 --> 00:04:29.437 know kind of enterprise enterprise productivity out there value to be 00:04:29.520 --> 00:04:32.957 created and so that while while it has been growing quickly and we've been 00:04:33.040 --> 00:04:37.117 overcoming that skepticism I think what needs to be done h has you know is 00:04:37.200 --> 00:04:40.717 enormous in scale compared to what to what has been done what has been done 00:04:40.800 --> 00:04:44.877 already and that's why partnerships with Accenture are so important that you know 00:04:44.960 --> 00:04:49.197 we really need to get to a scale that it's it's you know a young company needs 00:04:49.280 --> 00:04:52.957 to needs to partner with someone who really understands the enterprise world 00:04:53.040 --> 00:04:55.837 >> and Julie you made the point that you know one of the big questions here is 00:04:55.920 --> 00:04:59.997 when we're going to see AI show up uh in the P&L there's also the big question of 00:05:00.080 --> 00:05:04.237 when you see AI really show up in the job market and I'm curious you know 00:05:04.320 --> 00:05:08.317 whether you're seeing AI slow down hiring for entry- levelvel jobs. Over at 00:05:08.400 --> 00:05:11.677 Accenture, for example, [snorts] 00:05:11.760 --> 00:05:14.317 >> we are really focused on creating 00:05:14.400 --> 00:05:18.077 sustainable entry-level jobs with AI. 00:05:18.160 --> 00:05:21.597 And so our pivot in the talent side is 00:05:21.680 --> 00:05:24.717 how do we now take our entrylevel 00:05:24.800 --> 00:05:29.437 uh uh uh people, we call them reinventors coming in and give them the 00:05:29.520 --> 00:05:33.517 skills so they can operate at a higher level. So for example, if you can now do 00:05:33.600 --> 00:05:37.277 things that maybe would have taken you two years, uh then you're losing two 00:05:37.360 --> 00:05:41.997 years of experience at client. So how do we now intro we're now introducing 00:05:42.080 --> 00:05:44.077 communication training to help close 00:05:44.160 --> 00:05:47.117 that gap? And so we believe it's way too 00:05:47.200 --> 00:05:50.477 early to call the end of entrylevel jobs 00:05:50.560 --> 00:05:52.877 versus the responsibility that we have 00:05:52.960 --> 00:05:55.917 as a company and as companies across the 00:05:56.000 --> 00:05:59.197 globe to change the way that we train 00:05:59.280 --> 00:06:03.837 and that we think about jobs. so that we have sustainable entry level jobs. 00:06:03.920 --> 00:06:05.757 >> I am curious though uh Julie as you sort 00:06:05.840 --> 00:06:08.877 of prep your own uh folks in internally 00:06:08.960 --> 00:06:13.037 for uh not only using the tools yourselves but obviously the idea that 00:06:13.120 --> 00:06:15.437 these tools ultimately will then somehow 00:06:15.520 --> 00:06:18.157 be used by clients. What has been the 00:06:18.240 --> 00:06:21.037 uptake internally? How much retraining 00:06:21.120 --> 00:06:24.637 have you had to do for your own folks? 00:06:24.720 --> 00:06:27.277 >> Our training has been massive. Uh it 00:06:27.360 --> 00:06:30.237 starts with back in 2019 we introduced 00:06:30.320 --> 00:06:33.037 uh classical AI training. So when chatpt 00:06:33.120 --> 00:06:35.917 came on that we were already had 500,000 00:06:36.000 --> 00:06:37.997 people trained in the fundamentals of AI 00:06:38.080 --> 00:06:40.237 in addition to the specialists. We just 00:06:40.320 --> 00:06:43.277 kicked off our entire 750,000 00:06:43.360 --> 00:06:46.877 or so reinventors agentic AI training 00:06:46.960 --> 00:06:48.797 and in fact this partnership is all 00:06:48.880 --> 00:06:51.357 about tapping into the talent advantage 00:06:51.440 --> 00:06:54.157 that Accenture brings because you need 00:06:54.240 --> 00:06:59.117 great technology expertise you also need the industry expertise like in banking 00:06:59.200 --> 00:07:03.277 you need to know your be able to know your customer and so we're training all 00:07:03.360 --> 00:07:07.997 of our people those who understand industry and function and that's a big 00:07:08.080 --> 00:07:11.757 talent advantage. So Dario, but this goes back to the idea kind of of what 00:07:11.840 --> 00:07:15.117 you're contributing and the idea that a lot of people have been looking for more 00:07:15.200 --> 00:07:19.357 of a standardized model to be able to work off of and obviously anthropic at 00:07:19.440 --> 00:07:23.197 least the way as you guys promote yourselves. The idea of open source, the 00:07:23.280 --> 00:07:26.637 idea of maybe a little bit more transparency. There was a report today 00:07:26.720 --> 00:07:31.037 in your information that you along with a couple of others uh including uh 00:07:31.120 --> 00:07:35.917 Google and open AAI for that matter are going to be part of this AI foundation 00:07:36.000 --> 00:07:39.837 that will seek to create a more standardized system for some of this. 00:07:39.920 --> 00:07:42.317 Can you talk a little bit about that? 00:07:42.400 --> 00:07:44.477 >> Yes. So, so this is um we're we're 00:07:44.560 --> 00:07:47.517 donating uh MCP which is the called the 00:07:47.600 --> 00:07:49.837 model context protocol along with some 00:07:49.920 --> 00:07:52.237 other things to a to a to a foundation. 00:07:52.320 --> 00:07:54.957 And and what MCP is, it's it's a tool 00:07:55.040 --> 00:07:57.437 that uh uh uh kind of governs and 00:07:57.520 --> 00:08:00.797 standardizes how AI models intersect 00:08:00.880 --> 00:08:04.477 with data. If you think about it, you can think of an AI model as kind of as 00:08:04.560 --> 00:08:07.997 kind of the brain, right? You have a smart brain that knows a lot of things. 00:08:08.080 --> 00:08:12.077 And when I bring that brain into an enterprise context, there's all this 00:08:12.160 --> 00:08:15.917 kind of knowledge and and tacit knowledge that is present in the 00:08:16.000 --> 00:08:19.037 enterprise. And so bringing them together is always a challenge. You 00:08:19.120 --> 00:08:23.037 know, the way I often like to say it is, you know, suppose I took some very smart 00:08:23.120 --> 00:08:25.517 person off the street and, you know, plopped them into the middle of my 00:08:25.600 --> 00:08:29.117 enterprise, gave them an executive role and say, "Okay, congratulations. You 00:08:29.200 --> 00:08:32.797 know, you're in you're in charge. You get to make all the decisions." Now, as 00:08:32.880 --> 00:08:36.237 smart as that person is, they wouldn't at least not right away make make make 00:08:36.320 --> 00:08:39.917 make make immediately good immediately good decisions. So, there's this 00:08:40.000 --> 00:08:43.277 integration layer that's missing and and you know, I think these tools are 00:08:43.360 --> 00:08:46.957 designed to facilitate that integration layer and and make it easier. And so 00:08:47.040 --> 00:08:50.237 we're we're excited to provide these things to the world and and you know 00:08:50.320 --> 00:08:53.517 kind of kind of make it easier to facilitate access to the technology 00:08:53.600 --> 00:08:56.157 across the world. >> And Dario, before we let the two of you 00:08:56.240 --> 00:08:59.997 go, I have to ask while we have you, there has been reporting that you've 00:09:00.080 --> 00:09:02.557 been in early talks for an IPO as early 00:09:02.640 --> 00:09:06.397 as 2026. Can you confirm that? Uh 00:09:06.480 --> 00:09:11.117 currently we are we are just focused on growing our business um uh and you know 00:09:11.200 --> 00:09:15.197 growing growing growing enterprise uh growing enterprise revenue as as you can 00:09:15.280 --> 00:09:17.677 see in this partnership. >> All right. Well, obviously it's a great 00:09:17.760 --> 00:09:21.357 partnership. I've known Julie for some time and certainly uh you picked a good 00:09:21.440 --> 00:09:25.917 partner there. Dario Amade is the CEO of Anthropic. Julia, great to see you once 00:09:26.000 --> 00:09:30.720 again. and Julie, the CEO over at Accenture.