WEBVTT 1 00:00:01.590 --> 00:00:04.740 I see AI in three buckets on where we capture value. 2 00:00:04.740 --> 00:00:07.500 The first is applied AI, where we use AI 3 00:00:07.500 --> 00:00:10.380 to improve our operation, to improve our experience. 4 00:00:10.380 --> 00:00:14.550 The second is leverage AI to drive better products, 5 00:00:14.550 --> 00:00:15.930 the products that customers see. 6 00:00:15.930 --> 00:00:17.880 We have a better product because of AI. 7 00:00:17.880 --> 00:00:20.490 The third is how we take part in the AI ecosystem 8 00:00:20.490 --> 00:00:21.540 to drive more revenue 9 00:00:21.540 --> 00:00:23.550 just from the ecosystem alone. 10 00:00:23.550 --> 00:00:27.120 The single biggest opportunity for us is customer care. 11 00:00:27.120 --> 00:00:30.120 We have, I would think, probably one of the largest pools 12 00:00:30.120 --> 00:00:32.280 of customer care agents in the world, 13 00:00:32.280 --> 00:00:34.530 and they do an incredible job every single day-- 14 00:00:34.530 --> 00:00:35.640 answering questions, selling 15 00:00:35.640 --> 00:00:37.830 to customers, taking care of customers. 16 00:00:37.830 --> 00:00:42.150 The first opportunity for me is cognitive offload. 17 00:00:42.150 --> 00:00:45.090 Our frontline agents carry so much in their head, 18 00:00:45.090 --> 00:00:47.520 whether it's the rate, it's the plans, it's the technology, 19 00:00:47.520 --> 00:00:49.140 it's the handsets. 20 00:00:49.140 --> 00:00:51.270 They have a lot going on in a short period of time. 21 00:00:51.270 --> 00:00:53.430 They have to reproduce a lot of that. 22 00:00:53.430 --> 00:00:57.510 When you pair an agent who has empathy connection 23 00:00:57.510 --> 00:01:00.180 and emotional connection with customers, with data, 24 00:01:00.180 --> 00:01:01.740 and they bring the two together, 25 00:01:01.740 --> 00:01:04.410 you get a personalized engine that's very tough to beat. 26 00:01:04.410 --> 00:01:06.810 So that's how we think customer agents will 27 00:01:06.810 --> 00:01:08.880 evolve over a period of time. 28 00:01:08.880 --> 00:01:11.130 I see an environment where 29 00:01:11.130 --> 00:01:13.380 the agents will do different things, 30 00:01:13.380 --> 00:01:15.870 but the scenario that's most likely is you take the 31 00:01:15.870 --> 00:01:17.040 capacity that's freed up. 32 00:01:17.040 --> 00:01:20.220 It could be as high as 40, 50% over the next three years 33 00:01:20.220 --> 00:01:21.750 and deploy that in other areas. 34 00:01:22.590 --> 00:01:26.280 We want to be the best deployed conversational 35 00:01:26.280 --> 00:01:28.050 AI tool in the world. 36 00:01:28.050 --> 00:01:29.910 That's our goal. Agentic is good. 37 00:01:29.910 --> 00:01:32.760 We know how to do it, but conversational AI is the most 38 00:01:32.760 --> 00:01:35.520 difficult part of AI where customers are talking either 39 00:01:35.520 --> 00:01:37.140 through chat or through voice. 40 00:01:37.140 --> 00:01:39.240 In real time, things are happening to do that. 41 00:01:39.240 --> 00:01:42.480 So Project 624 was a massive launch in that space. 42 00:01:42.480 --> 00:01:43.650 We did a couple of things. 43 00:01:43.650 --> 00:01:46.290 The first biggest one we did was an app. 44 00:01:46.290 --> 00:01:47.670 We completely redesigned app. 45 00:01:47.670 --> 00:01:50.400 We, from the bottom up, made it about the customer, 46 00:01:50.400 --> 00:01:52.890 but more importantly, we launched the Verizon assistant, 47 00:01:52.890 --> 00:01:55.560 which is the world's most advanced AI app 48 00:01:55.560 --> 00:01:57.090 in the space that we have. 49 00:01:57.090 --> 00:01:58.560 You can check your bill, it can tell you 50 00:01:58.560 --> 00:01:59.700 why your bill went up. 51 00:01:59.700 --> 00:02:00.960 They're saying you want to travel to Italy, 52 00:02:00.960 --> 00:02:02.610 it'll hook you up with roaming. 53 00:02:02.610 --> 00:02:04.260 It can do hundreds of things 54 00:02:04.260 --> 00:02:08.010 that typically chatbots have never been able to do. 55 00:02:08.010 --> 00:02:10.410 And in the unlikely event it cannot solve it, 56 00:02:10.410 --> 00:02:12.000 it pushes it to a customer agent 57 00:02:12.000 --> 00:02:13.620 who has all the history to do that. 58 00:02:15.300 --> 00:02:17.130 We work very closely with Google. 59 00:02:17.130 --> 00:02:20.010 Google's one of our, I would say, almost like an R&D 60 00:02:20.010 --> 00:02:21.390 partner to us. 61 00:02:21.390 --> 00:02:23.220 We bring our teams together in a single building. 62 00:02:23.220 --> 00:02:24.780 They work together on some of that. 63 00:02:24.780 --> 00:02:26.940 There's a lot of AI that we've used to route calls 64 00:02:26.940 --> 00:02:29.700 and other things, so we've got maybe 15 other things 65 00:02:29.700 --> 00:02:32.370 that we launched, but it's our single biggest CX release 66 00:02:32.370 --> 00:02:33.930 we've ever done in our history, 67 00:02:33.930 --> 00:02:35.460 and we're pretty grateful to Google. 68 00:02:36.930 --> 00:02:40.680 I've had a 22-year relationship with BCG in different forms. 69 00:02:40.680 --> 00:02:42.510 There are two or three things that don't change 70 00:02:42.510 --> 00:02:44.160 and a couple of things that have changed. 71 00:02:44.160 --> 00:02:47.880 What doesn't change is relentless focus on client outcomes. 72 00:02:47.880 --> 00:02:49.530 It goes back to the fundamentals. 73 00:02:49.530 --> 00:02:52.200 Are you working on the problems I want you to work on? 74 00:02:52.200 --> 00:02:54.900 Are you driving the outcomes I want you to drive? 75 00:02:54.900 --> 00:02:56.430 And then more importantly, are you helping me 76 00:02:56.430 --> 00:02:57.810 build a better mousetrap? 77 00:02:57.810 --> 00:03:00.420 That's the three things I measure BCG on. 78 00:03:00.420 --> 00:03:02.010 I'm extremely happy and I look forward 79 00:03:02.010 --> 00:03:03.450 to another 22 more years with them.