WEBVTT 00:00:00.440 --> 00:00:01.280 Roger, welcome. 00:00:01.640 --> 00:00:06.720 Roger, AI promises such big productivity and efficiency gains, 00:00:06.720 --> 00:00:10.320 yet so many companies aren't realizing that. 00:00:10.560 --> 00:00:12.080 What is standing in the way? 00:00:13.360 --> 00:00:15.640 Yeah, it's a great question because I think, 00:00:15.640 --> 00:00:17.680 you know, we're two years plus into Gen. 00:00:17.720 --> 00:00:20.040 AI and there's so many companies that are frustrated by it. 00:00:20.120 --> 00:00:22.600 I learned a lesson from BCG that, you know, 00:00:22.600 --> 00:00:26.120 disruptive technologies go in through phases, the efficiency, 00:00:26.120 --> 00:00:28.320 effectiveness and then transformation. 00:00:28.320 --> 00:00:32.080 And I think one of the challenges has been that so many companies jump to 00:00:32.080 --> 00:00:34.680 complex exotic use cases from the very beginning. 00:00:35.400 --> 00:00:40.800 Whereas if you follow that pattern, there's very clear value to be created in known areas. 00:00:40.800 --> 00:00:44.680 So if it's in the back office, if it's in the call center, 00:00:44.680 --> 00:00:49.360 doing those known use cases, driving real bottom line impact from it. 00:00:50.120 --> 00:00:55.240 But then the in that process, your teams are learning and building fluency on Gen. 00:00:55.240 --> 00:00:59.440 AI, how to innovate with it, how to operate with it, how to secure it. 00:00:59.440 --> 00:01:02.160 So I think this notion, I think it was very boring to many 00:01:02.160 --> 00:01:04.560 companies that might have spun up hundreds of Gen. 00:01:04.560 --> 00:01:06.840 AI pilots to focus on these known use cases. 00:01:06.840 --> 00:01:09.720 But honestly, that advice is what I give clients now 00:01:09.720 --> 00:01:13.400 because start from the known pattern, build your muscle around it, 00:01:13.400 --> 00:01:17.600 and then tackle what's been true across so many different ways of disruptive 00:01:17.600 --> 00:01:18.560 technology before. 00:01:19.160 --> 00:01:23.240 So how do you identify where in your company you're going to see the best 00:01:23.240 --> 00:01:27.720 results from AI rather than just, you know, trying loads of different things? 00:01:27.720 --> 00:01:31.880 And especially when economic times are a little bit tougher, budgets are tight, 00:01:31.880 --> 00:01:35.720 how do you make sure that it's most effective some quick, scalable wins? 00:01:36.480 --> 00:01:38.960 Well, Georgie, I'd start with the end of what you said. 00:01:39.040 --> 00:01:42.760 I think we clearly live in uncertain macroeconomic times. 00:01:43.240 --> 00:01:46.960 And I think that puts the onus on really what we're talking about is we tell 00:01:46.960 --> 00:01:49.360 clients is being kind of lean and being flexible, 00:01:49.360 --> 00:01:51.520 getting efficient so that we preserve cash. 00:01:51.520 --> 00:01:55.880 So we're ready as the changes economy happened and putting in flexibility so AI 00:01:55.880 --> 00:01:58.560 can help us navigate the twists and turns ahead. 00:01:59.360 --> 00:02:01.120 We get back to identifying use cases. 00:02:01.120 --> 00:02:03.680 I think some of them are we're discussing earlier, 00:02:03.680 --> 00:02:07.600 it's the simple known efficiency use cases, the back office, the call center, 00:02:07.600 --> 00:02:09.960 things like that where we know there's value. 00:02:10.760 --> 00:02:13.200 And that's, but then there's a really highly creative 00:02:13.200 --> 00:02:17.040 process where if you're in certain things, if you're in media and you're not doing 00:02:17.040 --> 00:02:18.800 all your language translation with Gen. 00:02:18.840 --> 00:02:21.440 AI already, if you're in the education space and 00:02:21.440 --> 00:02:25.800 you're not transforming how education is done in kind of a custom tutor for every 00:02:25.800 --> 00:02:26.680 student with Gen. 00:02:26.840 --> 00:02:27.800 AI, you're falling behind. 00:02:27.800 --> 00:02:32.000 So I think there's this combination of known patterns that are true across many 00:02:32.000 --> 00:02:36.120 industries and then specific patterns where in specific verticals you need to 00:02:36.120 --> 00:02:39.920 be thinking hard about how this technology gives you advantage and also 00:02:39.920 --> 00:02:43.520 look out for the disruptors that will take advantage of it as well. 00:02:44.040 --> 00:02:48.720 I want to look at cost because as businesses look to scale up AI, 00:02:48.720 --> 00:02:55.320 how do you make sure that costs don't spiral and you still get that long term value? 00:02:56.360 --> 00:03:00.160 So we've done this at IBM jointly with BCG and we talked externally now about 00:03:00.160 --> 00:03:02.560 this cost transformation we've jointly been on. 00:03:02.560 --> 00:03:06.200 And so I think again, we began with productivity and efficiency 00:03:06.200 --> 00:03:07.200 as the use cases. 00:03:07.760 --> 00:03:13.120 That combination of BCG is our advisor on process reengineering paired with the 00:03:13.120 --> 00:03:14.680 power of generative AI. 00:03:15.320 --> 00:03:19.840 We've taken 3 1/2 billion dollars out of the run rate of IBM of real cash 00:03:19.840 --> 00:03:22.240 generation from that joint combination. 00:03:22.240 --> 00:03:26.160 So I think beginning with places where you there's a real business case of not 00:03:26.160 --> 00:03:29.160 just the technology, but how does it reshape your business. 00:03:29.160 --> 00:03:33.680 That's what we've done with BCG and kind of work proof positive at IBM that done 00:03:33.680 --> 00:03:36.800 well it can drop generate phenomenal economic results. 00:03:36.800 --> 00:03:38.600 Roger, thank you so much for your time. 00:03:38.960 --> 00:03:39.520 Thanks Georgie. 00:03:39.520 --> 00:03:40.240 Pleasure to be here.