1 00:00:02,720 --> 00:00:10,559 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,600 --> 00:00:14,560 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:14,600 --> 00:00:17,840 Speaker 1: Eastern on Apple, Cocklay and Android Auto with the Bloomberg 4 00:00:17,920 --> 00:00:21,040 Speaker 1: Business app. Listen on demand wherever you get your podcasts, 5 00:00:21,360 --> 00:00:23,560 Speaker 1: or watch us live on YouTube. 6 00:00:24,320 --> 00:00:27,960 Speaker 2: Of course, it is now only fifteen days into the 7 00:00:28,000 --> 00:00:31,280 Speaker 2: New York City Mayor Zoramum Donnie's tenure, and he is. 8 00:00:31,240 --> 00:00:33,760 Speaker 3: Making moves already. Alex, do you live in the city. 9 00:00:33,880 --> 00:00:34,120 Speaker 4: I do. 10 00:00:34,200 --> 00:00:35,200 Speaker 5: I'm a lifelong New Yorker. 11 00:00:35,280 --> 00:00:37,360 Speaker 2: You're a lifelong New Yorker, so you feel it more 12 00:00:37,360 --> 00:00:39,440 Speaker 2: than I do. I live in the suburbs along with 13 00:00:39,520 --> 00:00:40,120 Speaker 2: John Tuckers. 14 00:00:40,120 --> 00:00:41,560 Speaker 3: So did you get your free bus service? 15 00:00:41,640 --> 00:00:43,320 Speaker 5: Yeah? Not yet, still waiting for. 16 00:00:43,200 --> 00:00:45,800 Speaker 3: You, Still waiting a free child here take the bus. 17 00:00:45,560 --> 00:00:47,840 Speaker 5: That often usually the train, so I don't think it'll 18 00:00:47,840 --> 00:00:49,440 Speaker 5: direct they impact me. 19 00:00:49,800 --> 00:00:53,239 Speaker 3: Okay, but still waiting, still waiting. Let's check in with 20 00:00:53,240 --> 00:00:53,920 Speaker 3: Miles Miller. 21 00:00:54,000 --> 00:00:57,760 Speaker 2: He is our senior reporter covering security the National Desk, 22 00:00:57,880 --> 00:01:00,800 Speaker 2: law enforcement, governments and cities. And it's here where we 23 00:01:00,840 --> 00:01:03,040 Speaker 2: want to talk to him, because Miles is joining us 24 00:01:03,080 --> 00:01:06,800 Speaker 2: from downtown Manhattan. And Miles talk to us a little 25 00:01:06,800 --> 00:01:09,800 Speaker 2: bit about what the new mayor, Zoramumdani is doing when 26 00:01:09,840 --> 00:01:14,640 Speaker 2: it comes to work. He is cracking down on some 27 00:01:14,720 --> 00:01:16,680 Speaker 2: companies and how they're treating workers. 28 00:01:17,760 --> 00:01:21,560 Speaker 6: Yeah, you know, he's enlisted Lena Kahn as an advisor 29 00:01:21,640 --> 00:01:24,400 Speaker 6: unpaid advisor to him, of course, known to the Bloomberg 30 00:01:24,440 --> 00:01:27,920 Speaker 6: audience as the former FTC chair. In addition to that, 31 00:01:28,080 --> 00:01:32,800 Speaker 6: Julie Sue who joined us on our fabulous Labor Fridays 32 00:01:32,880 --> 00:01:35,560 Speaker 6: right the fridays where we get the jobs report. And 33 00:01:35,600 --> 00:01:38,559 Speaker 6: then in addition to that Sam Levine, who was at 34 00:01:38,720 --> 00:01:43,000 Speaker 6: the FTC running enforcement. That's his dream team. And what 35 00:01:43,040 --> 00:01:47,880 Speaker 6: they're doing is going after companies that are involved in delivery, 36 00:01:47,920 --> 00:01:50,040 Speaker 6: that are involved in the gig economy to make sure 37 00:01:50,080 --> 00:01:53,640 Speaker 6: that workers are protected. The story across the Bloomberg terminal 38 00:01:54,240 --> 00:01:58,160 Speaker 6: just about twenty minutes ago is one that really they're 39 00:01:58,320 --> 00:02:02,600 Speaker 6: suing food delivery providers for what they say is withholding 40 00:02:02,680 --> 00:02:06,000 Speaker 6: pay from workers. And it really gets to the heart 41 00:02:06,080 --> 00:02:09,519 Speaker 6: of what the Mammdani administration is going to be about, 42 00:02:10,320 --> 00:02:14,280 Speaker 6: using little known laws to go after big companies to 43 00:02:14,360 --> 00:02:17,400 Speaker 6: fight for who they say is the little guy. The 44 00:02:17,560 --> 00:02:21,800 Speaker 6: company that is being sued today is Motoclick, and the 45 00:02:21,919 --> 00:02:25,600 Speaker 6: allegations are pretty simple that they violated delivery worker laws 46 00:02:25,639 --> 00:02:30,600 Speaker 6: by failing to pay the required minimum rate and deducting 47 00:02:30,760 --> 00:02:34,600 Speaker 6: canceled and refunded orders directly from their paychecks. And these 48 00:02:34,600 --> 00:02:37,960 Speaker 6: are folks who most times are only making you know, 49 00:02:38,040 --> 00:02:42,040 Speaker 6: money off of the tips that they're getting from these 50 00:02:42,400 --> 00:02:43,480 Speaker 6: people who are ordering food. 51 00:02:43,680 --> 00:02:46,440 Speaker 2: What you mentioned, the company that is in question here 52 00:02:46,480 --> 00:02:48,800 Speaker 2: is Motoclick. This is not a company that I think 53 00:02:48,800 --> 00:02:51,280 Speaker 2: a lot of people are necessarily familiar with. We don't 54 00:02:51,560 --> 00:02:53,839 Speaker 2: if you order from DoorDash or a grubhub, you don't 55 00:02:53,840 --> 00:02:56,800 Speaker 2: necessarily have a direct interaction with motoclick, do you. 56 00:02:58,880 --> 00:02:59,120 Speaker 4: Right? 57 00:02:59,240 --> 00:03:02,120 Speaker 6: You know, this is what of those companies that says 58 00:03:02,160 --> 00:03:05,200 Speaker 6: it works with platforms like Uber Eats, door Dash and 59 00:03:05,200 --> 00:03:09,600 Speaker 6: grub hub. You know, you may value order through these companies, 60 00:03:09,639 --> 00:03:11,400 Speaker 6: and then you don't know that the folks who are 61 00:03:11,440 --> 00:03:13,880 Speaker 6: coming to deliver it are actually working with this. You know, 62 00:03:14,080 --> 00:03:20,320 Speaker 6: in some cases last mile company, they are basically integrated 63 00:03:20,360 --> 00:03:23,160 Speaker 6: into the point of sale systems at some of these restaurants. 64 00:03:23,400 --> 00:03:25,480 Speaker 6: And so yeah, you may order from Uber lyft, but 65 00:03:25,560 --> 00:03:28,400 Speaker 6: you don't know that I was sorry, Uber or doordasher, grubhub, 66 00:03:28,400 --> 00:03:30,920 Speaker 6: But you don't understand, you know, in that last mile 67 00:03:30,960 --> 00:03:33,400 Speaker 6: where it's coming from. Well, the city is putting them 68 00:03:33,440 --> 00:03:36,200 Speaker 6: unnotice that, you know that they're going to be sued 69 00:03:36,240 --> 00:03:38,640 Speaker 6: for this. And then in addition to that, the city 70 00:03:38,680 --> 00:03:42,520 Speaker 6: pass laws in the last year or so that protects 71 00:03:42,760 --> 00:03:45,960 Speaker 6: these workers. In addition to this lawsuit, they're also putting 72 00:03:46,200 --> 00:03:49,560 Speaker 6: the delivery companies on notice that there are specific laws 73 00:03:49,760 --> 00:03:53,760 Speaker 6: that protect workers as it relates to deliveries, making sure 74 00:03:53,800 --> 00:03:56,080 Speaker 6: that they get proper wages, minimum wage and all of that. 75 00:03:56,360 --> 00:03:58,520 Speaker 6: And if that's not followed, that they could meet the 76 00:03:58,560 --> 00:04:02,640 Speaker 6: same fate that's being met by motorclick right now miles. 77 00:04:02,680 --> 00:04:06,000 Speaker 5: This of course follows the allegations that DoorDash and Uber 78 00:04:06,080 --> 00:04:09,160 Speaker 5: deprived New York City delivery workers of more than five 79 00:04:09,240 --> 00:04:12,000 Speaker 5: hundred and fifty million dollars in tips. That is a 80 00:04:12,000 --> 00:04:14,720 Speaker 5: lot of money. Is there a sense if this lawsuit 81 00:04:14,760 --> 00:04:17,440 Speaker 5: is successful that they might see those wages come back. 82 00:04:18,720 --> 00:04:18,920 Speaker 7: Yeah. 83 00:04:18,960 --> 00:04:21,760 Speaker 6: I think what the city wants to do, and specifically 84 00:04:21,960 --> 00:04:25,479 Speaker 6: the the Department of Consumer and Worker Protection wants to do, 85 00:04:25,640 --> 00:04:29,919 Speaker 6: is in filing any of these lawsuits or in making 86 00:04:30,000 --> 00:04:33,600 Speaker 6: these claims public, is to put pressure on these companies 87 00:04:33,960 --> 00:04:35,880 Speaker 6: to do the right thing before they get to the 88 00:04:36,000 --> 00:04:39,240 Speaker 6: enforcement level. We've seen a lot of these companies that 89 00:04:39,279 --> 00:04:41,880 Speaker 6: have been sued in the past, whether into the Blasio administration, 90 00:04:41,960 --> 00:04:45,640 Speaker 6: whether being sued by the Controller's office, come to an 91 00:04:45,640 --> 00:04:48,480 Speaker 6: agreement on a settlement, and that money does trickle down 92 00:04:48,560 --> 00:04:51,880 Speaker 6: back to workers. But it doesn't stop with just the 93 00:04:52,000 --> 00:04:55,040 Speaker 6: city Hall and doesn't stop with the Comptroller's office. You know, 94 00:04:55,279 --> 00:04:59,160 Speaker 6: just today the Manhattan DA also you know, trying to 95 00:04:59,200 --> 00:05:01,719 Speaker 6: make it clear that he wants protections for these workers 96 00:05:01,800 --> 00:05:05,479 Speaker 6: because these are you know, these wage cases continue to 97 00:05:05,560 --> 00:05:08,480 Speaker 6: pop up. It was just about a year and a 98 00:05:08,520 --> 00:05:11,840 Speaker 6: half ago, two years ago that Grimaldi's Pizza was being 99 00:05:12,120 --> 00:05:16,400 Speaker 6: accused of of wage theft and holding back pay pay 100 00:05:16,480 --> 00:05:18,720 Speaker 6: for these low paid workers. And that's going to be 101 00:05:18,800 --> 00:05:20,680 Speaker 6: a major focus of this administration. 102 00:05:22,080 --> 00:05:26,040 Speaker 2: So can you reconcile this this first action, it's kind 103 00:05:26,040 --> 00:05:28,239 Speaker 2: of like a shot across about by the mum donnie 104 00:05:28,240 --> 00:05:32,400 Speaker 2: administration with the promises it had made to its supporters, 105 00:05:32,400 --> 00:05:35,400 Speaker 2: to voters, to folks in the city, like alex Hemanova, 106 00:05:35,400 --> 00:05:38,000 Speaker 2: who's a lifelong New Yorker, is this is this kind 107 00:05:38,040 --> 00:05:40,799 Speaker 2: of the what they promised to prioritize. 108 00:05:41,000 --> 00:05:45,480 Speaker 6: Yeah, I mean, you know, they have changed the role 109 00:05:45,640 --> 00:05:48,640 Speaker 6: that Julie Sue is in. It used to be the 110 00:05:48,920 --> 00:05:52,160 Speaker 6: mayor for a deputy mayor for economic development. But it's 111 00:05:52,160 --> 00:05:55,800 Speaker 6: not just economic development, it's it's really with a focus 112 00:05:55,880 --> 00:05:59,400 Speaker 6: on worker protection. It's really on a focus on equality 113 00:05:59,440 --> 00:06:02,760 Speaker 6: and rights for people. And you know, this is a 114 00:06:02,800 --> 00:06:05,960 Speaker 6: person who has spent a good amount of time in Washington, 115 00:06:06,000 --> 00:06:09,160 Speaker 6: had spent time in California, who is going to be 116 00:06:09,279 --> 00:06:11,919 Speaker 6: leading this effort. You know, when you look at Lena 117 00:06:12,000 --> 00:06:15,600 Speaker 6: Khan being involved in decision making here at city Hall 118 00:06:15,839 --> 00:06:17,839 Speaker 6: and going and doing what she knows best right and 119 00:06:17,920 --> 00:06:23,320 Speaker 6: going through you know, very complex parts of the city 120 00:06:23,400 --> 00:06:26,320 Speaker 6: Charter to find where you can really stick it to 121 00:06:27,320 --> 00:06:29,800 Speaker 6: companies or where they could stick it to companies, you know, 122 00:06:29,920 --> 00:06:33,280 Speaker 6: it really shows that this is a top priority for him. 123 00:06:34,040 --> 00:06:36,919 Speaker 6: You know, and in addition to that, this role, the 124 00:06:37,040 --> 00:06:41,240 Speaker 6: role in consumer protection was one of the first roles 125 00:06:41,240 --> 00:06:46,680 Speaker 6: he filled after being being elected and right before take 126 00:06:46,720 --> 00:06:49,080 Speaker 6: it or right after he took office, because he knew 127 00:06:49,080 --> 00:06:51,800 Speaker 6: it was going to be something that people really relate to. 128 00:06:52,600 --> 00:06:54,800 Speaker 5: Miles, when was the last time that we saw a 129 00:06:54,839 --> 00:06:57,320 Speaker 5: New York City mayor go after big companies like this? 130 00:06:57,480 --> 00:06:58,400 Speaker 5: Is this unusual. 131 00:06:59,440 --> 00:07:04,080 Speaker 6: No, I mean in the Basio administration, we saw companies targeted, 132 00:07:04,480 --> 00:07:07,840 Speaker 6: certainly UH. And then you know, in the Atoms administration, 133 00:07:07,960 --> 00:07:12,160 Speaker 6: it was certainly a very pro business administration trying to 134 00:07:12,280 --> 00:07:16,320 Speaker 6: work with business, but also sort of the bonus on 135 00:07:16,440 --> 00:07:17,080 Speaker 6: businesses to. 136 00:07:18,920 --> 00:07:19,040 Speaker 4: UH. 137 00:07:19,160 --> 00:07:23,120 Speaker 6: And so it's it's a this is obviously a different tactic, 138 00:07:23,960 --> 00:07:27,400 Speaker 6: and I think for the first time you're seeing UH 139 00:07:27,560 --> 00:07:31,200 Speaker 6: an administration where they're not taking people really from big 140 00:07:31,240 --> 00:07:33,880 Speaker 6: business and saying, Okay, here's how you can work on 141 00:07:34,000 --> 00:07:38,120 Speaker 6: economic development. In the Vasio administration, Lesha Glenn was the 142 00:07:38,120 --> 00:07:41,160 Speaker 6: Deputy Mayor for economic Development and had come from the 143 00:07:41,200 --> 00:07:44,080 Speaker 6: business community. No, these are people who've worked in government 144 00:07:44,160 --> 00:07:47,320 Speaker 6: for some time and are trying to figure out a 145 00:07:47,320 --> 00:07:50,200 Speaker 6: way to make government work for people who you know, 146 00:07:50,480 --> 00:07:54,520 Speaker 6: don't have much money, or to hit at the affordability crisis. 147 00:07:55,120 --> 00:07:57,320 Speaker 6: It's a it's really a first of its kind approach 148 00:07:57,360 --> 00:07:58,440 Speaker 6: to doing this kind of work. 149 00:07:59,240 --> 00:08:02,160 Speaker 2: Stay with us more from Bloomberg Intelligence coming up after this. 150 00:08:05,760 --> 00:08:09,440 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 151 00:08:09,520 --> 00:08:12,240 Speaker 1: weekdays at ten am. He's done on Apple, Cocklay and 152 00:08:12,240 --> 00:08:14,560 Speaker 1: Android Auto with the Bloomberg Business app. 153 00:08:14,680 --> 00:08:15,520 Speaker 3: Listen on demand. 154 00:08:15,560 --> 00:08:19,120 Speaker 1: Wherever you get your podcasts or watch us live on YouTube. 155 00:08:20,080 --> 00:08:22,880 Speaker 2: Let's move over to the tech sector because there's some 156 00:08:22,920 --> 00:08:27,080 Speaker 2: big news for the AI sector given that Taiwan Semiconductor 157 00:08:27,120 --> 00:08:30,320 Speaker 2: Manufacturing and partner of Nvidia and other chip makers, came 158 00:08:30,320 --> 00:08:33,280 Speaker 2: out with a monster forecast. Man Deep saying is our 159 00:08:33,280 --> 00:08:36,280 Speaker 2: global tech research had apt Bloomberg Intelligence and he joins 160 00:08:36,320 --> 00:08:40,840 Speaker 2: US now and TSMC is a bellweather for the AI story, 161 00:08:41,040 --> 00:08:45,200 Speaker 2: and the revenue forecast it has given is growth of 162 00:08:45,200 --> 00:08:48,800 Speaker 2: almost thirty percent, handily beating analystsessimates. 163 00:08:49,440 --> 00:08:52,920 Speaker 4: Well, I mean, right now, we are in an environment 164 00:08:53,000 --> 00:08:57,480 Speaker 4: where the supply constraints are at the component level, at 165 00:08:57,520 --> 00:09:01,840 Speaker 4: the fab level, I mean TSMC doubt how advanced nodes 166 00:09:01,840 --> 00:09:05,600 Speaker 4: are almost seventy seven percent of their revenue. So that 167 00:09:05,840 --> 00:09:08,480 Speaker 4: just goes to show that if they have more wayfor 168 00:09:08,559 --> 00:09:12,640 Speaker 4: capacity at the advanced node level, they'll probably be you know, 169 00:09:13,040 --> 00:09:16,360 Speaker 4: growing even faster. And that's why they raise their own capex. 170 00:09:16,679 --> 00:09:19,559 Speaker 4: So think of the trickle down effect. Hyperscalers are raising 171 00:09:19,600 --> 00:09:23,880 Speaker 4: their capex. TSMC, being the fab layer, is raising their capex. 172 00:09:23,920 --> 00:09:27,240 Speaker 4: And this is the entire supply chain that everyone realizes 173 00:09:27,679 --> 00:09:30,160 Speaker 4: they need more data center capacity when it comes to 174 00:09:30,240 --> 00:09:33,600 Speaker 4: running AI and all the way through the supply chain. 175 00:09:33,720 --> 00:09:36,960 Speaker 4: Right now, it's trickling down now. The question is obviously 176 00:09:37,120 --> 00:09:39,760 Speaker 4: of overbuild and if and when, you know, we'll hit 177 00:09:39,800 --> 00:09:43,960 Speaker 4: an equilibrium. And from what we have seen in terms 178 00:09:44,000 --> 00:09:48,920 Speaker 4: of partnerships and deal making like open Ai Cerebris, I 179 00:09:48,960 --> 00:09:52,640 Speaker 4: mean right now, they're trying to procure as much chip 180 00:09:52,720 --> 00:09:56,199 Speaker 4: capacity as they can because I mean Opening has said 181 00:09:56,640 --> 00:10:00,400 Speaker 4: their revenue growth is a function of the power and 182 00:10:00,480 --> 00:10:04,280 Speaker 4: chip available computer availability they have, so right last year 183 00:10:04,320 --> 00:10:09,240 Speaker 4: they grew their power and computer availability three x, their 184 00:10:09,280 --> 00:10:13,320 Speaker 4: revenue grew three x. So that's the kind of part 185 00:10:13,320 --> 00:10:15,440 Speaker 4: of the cycle we are in. And the question is 186 00:10:16,000 --> 00:10:19,000 Speaker 4: you know how long it's going to sustain and so 187 00:10:19,000 --> 00:10:22,600 Speaker 4: so far as signs are, this is going to carry 188 00:10:22,640 --> 00:10:24,480 Speaker 4: through at least through twenty twenty six. 189 00:10:24,800 --> 00:10:27,960 Speaker 5: Mandy, what does the strong outlook from TSMC mean for 190 00:10:28,160 --> 00:10:31,240 Speaker 5: Intel and its foundry business. Intel is up some thirty 191 00:10:31,360 --> 00:10:34,040 Speaker 5: percent this year. Is it a positive sign for them 192 00:10:34,040 --> 00:10:37,200 Speaker 5: that demand is there or signed that TSMC is a 193 00:10:37,240 --> 00:10:38,360 Speaker 5: dominant name here. 194 00:10:38,679 --> 00:10:42,559 Speaker 4: Actually, there was some demand spill over to an Intel 195 00:10:42,720 --> 00:10:46,079 Speaker 4: and Samsung, especially on the non data center side. So 196 00:10:46,440 --> 00:10:50,840 Speaker 4: I mentioned TSMC is heavily skewed towards advanced notes and 197 00:10:50,960 --> 00:10:55,520 Speaker 4: more towards data centers. Well, there is demand for you know, 198 00:10:55,720 --> 00:11:00,360 Speaker 4: chip capacity on the PC side, smartphone side, and that's 199 00:11:00,360 --> 00:11:03,360 Speaker 4: where there is some spillover that's carrying over to an 200 00:11:03,360 --> 00:11:07,240 Speaker 4: Intel on the PC side, to Samsung as well. And 201 00:11:07,320 --> 00:11:10,840 Speaker 4: so right now, everyone seems to be benefiting from overall 202 00:11:10,960 --> 00:11:13,239 Speaker 4: chip demand across the board. 203 00:11:13,200 --> 00:11:16,000 Speaker 2: Right and something else that's in demand is memory. And 204 00:11:16,040 --> 00:11:18,800 Speaker 2: we've seen Micron, we've seen sand Disk, we've seen Western 205 00:11:18,840 --> 00:11:22,840 Speaker 2: Digital really benefit from that demand for memory chips. But 206 00:11:22,960 --> 00:11:24,920 Speaker 2: it also there's a downside to that because you have 207 00:11:24,920 --> 00:11:28,360 Speaker 2: hardware companies as a result under pressure because they need 208 00:11:28,400 --> 00:11:30,280 Speaker 2: to pay for that memory and they need to go 209 00:11:30,280 --> 00:11:33,600 Speaker 2: out and source it and it's not always available unless you. 210 00:11:33,640 --> 00:11:38,560 Speaker 4: Are Jensen and Nvidia, who has really managed the supply chain. Well, 211 00:11:38,600 --> 00:11:42,840 Speaker 4: I mean, I was amazed how Nvidia mentioned that they 212 00:11:42,960 --> 00:11:46,080 Speaker 4: still feel comfortable holding on to that mid seventy percent 213 00:11:46,200 --> 00:11:50,960 Speaker 4: ross margins. They're one of the biggest users of HBM memory. 214 00:11:51,040 --> 00:11:53,840 Speaker 4: That is a supply constrained right now, and the prices 215 00:11:53,880 --> 00:11:56,560 Speaker 4: are going through the roof, but they have logged in 216 00:11:56,679 --> 00:12:01,319 Speaker 4: those multi year agreements where these suppliers can really raise prices, 217 00:12:01,679 --> 00:12:05,199 Speaker 4: and so from that perspective, the bigger you are, if 218 00:12:05,240 --> 00:12:08,080 Speaker 4: you're an Apple, I'm sure they can source their memory. 219 00:12:08,120 --> 00:12:11,280 Speaker 4: They may have to pay higher prices and it will 220 00:12:11,320 --> 00:12:14,360 Speaker 4: impact their gross margins, but not to the same extent 221 00:12:14,400 --> 00:12:17,440 Speaker 4: it's going to hit a smaller hardware vender. And that's 222 00:12:17,480 --> 00:12:19,720 Speaker 4: what I think we'll find out this earning season. 223 00:12:19,920 --> 00:12:22,760 Speaker 5: Man Deep also looking at the story today about Oracle 224 00:12:22,840 --> 00:12:27,199 Speaker 5: struggling to hire workout workers for the buildout of its 225 00:12:27,240 --> 00:12:30,360 Speaker 5: headquarters in Nashville. What has this AI build out meant 226 00:12:30,440 --> 00:12:33,840 Speaker 5: for hiring the talent war? Is there anyone who's winning it? 227 00:12:34,200 --> 00:12:36,800 Speaker 4: Yeah, I mean we read the story on the terminal 228 00:12:36,800 --> 00:12:42,280 Speaker 4: about electricians, you know, having almost a doubling off their pay, 229 00:12:42,320 --> 00:12:45,960 Speaker 4: and so anyone who is linked to that data center 230 00:12:46,080 --> 00:12:49,840 Speaker 4: construction right now is in high demand. And so it 231 00:12:49,880 --> 00:12:53,960 Speaker 4: doesn't surprise me that you are sort of in this 232 00:12:54,120 --> 00:12:58,319 Speaker 4: environment where laborers in short supply, you know, components are 233 00:12:58,320 --> 00:13:01,800 Speaker 4: in short supply, and putting all these things together is 234 00:13:01,840 --> 00:13:06,640 Speaker 4: taking longer time because everyone wants them to be ready overnight. Well, 235 00:13:07,480 --> 00:13:09,920 Speaker 4: that's where you're running into these bottom lines. 236 00:13:10,040 --> 00:13:12,920 Speaker 2: Well too, Alex's point, Oracle is trying to attract workers 237 00:13:12,920 --> 00:13:16,920 Speaker 2: in Nashville where it's developing this riverfront headquarters. Is that 238 00:13:16,960 --> 00:13:18,840 Speaker 2: a place where the tech talent will flock to. 239 00:13:19,600 --> 00:13:22,360 Speaker 4: I mean, we've seen what has happened in Texas right 240 00:13:22,480 --> 00:13:26,640 Speaker 4: in terms of companies going to Texas just because it's 241 00:13:26,840 --> 00:13:29,480 Speaker 4: easier to set up data centers over there. 242 00:13:29,679 --> 00:13:31,559 Speaker 3: So oh and no income tax. 243 00:13:31,520 --> 00:13:36,200 Speaker 4: No income tax, that's right. So all these pockets I 244 00:13:36,240 --> 00:13:39,800 Speaker 4: think are having their moment in terms of one attracting 245 00:13:40,280 --> 00:13:43,320 Speaker 4: these big companies. And if you have power, and I 246 00:13:43,400 --> 00:13:46,880 Speaker 4: haven't studied Nashville in that detail, but if you have power, 247 00:13:47,200 --> 00:13:50,400 Speaker 4: then it suddenly becomes a very attractive destination. 248 00:13:51,800 --> 00:13:54,640 Speaker 2: Stay with us. More from Bloomberg Intelligence coming up after this. 249 00:13:58,440 --> 00:14:01,800 Speaker 1: You're listening to the Bloomberg and Helogen's podcast. Catch us 250 00:14:01,880 --> 00:14:04,800 Speaker 1: Live weekdays at ten am. He's done on Apple, Cocklay 251 00:14:04,800 --> 00:14:07,760 Speaker 1: and Android Auto with the Bloomberg Business App. Listen on 252 00:14:07,840 --> 00:14:11,120 Speaker 1: demand wherever you get your podcasts, or watch us live 253 00:14:11,160 --> 00:14:11,800 Speaker 1: on YouTube. 254 00:14:12,640 --> 00:14:15,360 Speaker 2: One of the tailwinds for the market heading into this 255 00:14:15,440 --> 00:14:18,320 Speaker 2: year was the expectation of a spate of deal making, 256 00:14:18,440 --> 00:14:21,720 Speaker 2: and to that point, we did learn today that Boston 257 00:14:21,760 --> 00:14:25,000 Speaker 2: Scientific is looking to buy p Number for about fourteen 258 00:14:25,080 --> 00:14:27,920 Speaker 2: and a half billion dollars. Obviously, with the big banks 259 00:14:28,000 --> 00:14:32,120 Speaker 2: reporting earnings, bank executives are also making comments. David Solomon, 260 00:14:32,200 --> 00:14:34,160 Speaker 2: the CEO of Goldman Sachs, says that we are not 261 00:14:34,320 --> 00:14:36,160 Speaker 2: yet in the middle of a full on M and 262 00:14:36,240 --> 00:14:38,960 Speaker 2: A cycle, and he sees a very very good year 263 00:14:39,040 --> 00:14:41,720 Speaker 2: for M and A overall. Let's bring in Jennifer Ree, 264 00:14:41,760 --> 00:14:44,640 Speaker 2: she is our senior litigation analyst for Bloomberg Intelligence, to 265 00:14:44,680 --> 00:14:47,880 Speaker 2: talk to us about the antitrust landscape. Is there an 266 00:14:47,960 --> 00:14:52,360 Speaker 2: active antitrust monitoring happening right now because this administration has 267 00:14:52,400 --> 00:14:55,240 Speaker 2: signaled that it wants to see deals being made. 268 00:14:55,520 --> 00:14:55,760 Speaker 4: Yeah. 269 00:14:55,800 --> 00:14:58,120 Speaker 7: Absolutely, and it certainly is a big change from the 270 00:14:58,120 --> 00:15:01,200 Speaker 7: Biden administration, where we kind of had the opposite sentiment. 271 00:15:01,360 --> 00:15:04,120 Speaker 7: I mean, we are really seeing very little activity from 272 00:15:04,120 --> 00:15:06,040 Speaker 7: the Department of Justice, a little bit more from the 273 00:15:06,040 --> 00:15:08,760 Speaker 7: Federal Trade Commission, but even in their case, it's been 274 00:15:08,800 --> 00:15:12,760 Speaker 7: pretty restrained. And it seems that both authorities are really 275 00:15:12,800 --> 00:15:15,160 Speaker 7: willing to work with the companies if they think that 276 00:15:15,160 --> 00:15:17,120 Speaker 7: there's a problem with the deal, to work out some 277 00:15:17,240 --> 00:15:19,440 Speaker 7: kind of settlement. And that's what didn't exist during the 278 00:15:19,440 --> 00:15:22,680 Speaker 7: Biden administration and why deal making was so stymied At 279 00:15:22,680 --> 00:15:25,920 Speaker 7: that time, and I think most companies see if we 280 00:15:25,960 --> 00:15:27,800 Speaker 7: can come up if we have a problem, A lot 281 00:15:27,800 --> 00:15:29,760 Speaker 7: of deals don't. But if we do and we can 282 00:15:29,760 --> 00:15:31,920 Speaker 7: come up with a solution, we can probably get it cleared. 283 00:15:33,080 --> 00:15:36,080 Speaker 5: Jen you mentioned muted activity from the regulators, but are 284 00:15:36,120 --> 00:15:39,400 Speaker 5: there any industries that they're targeting right now more than others. 285 00:15:39,520 --> 00:15:40,520 Speaker 3: Well, it looks like it. 286 00:15:40,520 --> 00:15:43,200 Speaker 7: It's interesting that we see Boston Scientific has a deal 287 00:15:43,280 --> 00:15:46,080 Speaker 7: because of the few challenges that have been brought to 288 00:15:46,160 --> 00:15:48,680 Speaker 7: deals by the FTC, they've been in the healthcare space, 289 00:15:49,000 --> 00:15:52,520 Speaker 7: one in the housing area construction adhesives, which is a 290 00:15:52,520 --> 00:15:55,520 Speaker 7: recent case they filed, but two in the healthcare space. 291 00:15:56,680 --> 00:15:59,280 Speaker 7: And it doesn't surprise me really because these are very 292 00:15:59,280 --> 00:16:03,400 Speaker 7: sensitive sector's, consumer facing sectors, and that does align with 293 00:16:03,920 --> 00:16:06,680 Speaker 7: essentially a populist agenda, which they talked about in the 294 00:16:06,680 --> 00:16:09,240 Speaker 7: beginning when they took on their positions, and so I 295 00:16:09,280 --> 00:16:12,640 Speaker 7: think we'll probably see if we see continued activity in 296 00:16:12,680 --> 00:16:15,560 Speaker 7: those areas or other very sensitive consumer areas. 297 00:16:16,560 --> 00:16:18,080 Speaker 2: The other thing that we need to keep in mind 298 00:16:18,120 --> 00:16:19,960 Speaker 2: is most of these companies that we're talking about are 299 00:16:19,960 --> 00:16:23,040 Speaker 2: big multinationals. They operate all around the world, so you 300 00:16:23,040 --> 00:16:25,520 Speaker 2: have US regulators and they may be stepping back and 301 00:16:25,640 --> 00:16:28,760 Speaker 2: letting things happen, but regulators in Europe may not be. 302 00:16:28,880 --> 00:16:32,800 Speaker 2: And I bring this up because we heard reports yesterday 303 00:16:32,880 --> 00:16:36,440 Speaker 2: that Paramount and Netflix have been meeting with European Commission 304 00:16:36,680 --> 00:16:40,640 Speaker 2: officials as part of their bid for Warner Brothers. What 305 00:16:41,080 --> 00:16:44,560 Speaker 2: can pare contrast, for instance, the European Commission regulators with 306 00:16:44,680 --> 00:16:45,440 Speaker 2: those in the US. 307 00:16:46,360 --> 00:16:48,320 Speaker 7: You know, there's been a little bit of a pullback. 308 00:16:48,520 --> 00:16:51,760 Speaker 7: I think when I think of really big regulators in antitrust, 309 00:16:51,800 --> 00:16:55,480 Speaker 7: I think of US, China, UK and Europe. These are 310 00:16:55,480 --> 00:16:58,080 Speaker 7: the jurisdictions which would be willing to actually block. 311 00:16:57,880 --> 00:16:58,680 Speaker 3: A global deal. 312 00:16:59,400 --> 00:17:01,680 Speaker 7: And we've seen a little bit of pullback across the board, 313 00:17:01,720 --> 00:17:04,159 Speaker 7: and not so much with China. It's really just a 314 00:17:04,200 --> 00:17:06,280 Speaker 7: black box there. I can't speak to what they're doing. 315 00:17:06,280 --> 00:17:09,040 Speaker 7: But in the UK and in Europe there has also 316 00:17:09,080 --> 00:17:11,720 Speaker 7: been a bit of a pullback, especially in the UK 317 00:17:12,000 --> 00:17:15,240 Speaker 7: after they kind of got really chided from Microsoft Activision 318 00:17:15,240 --> 00:17:18,600 Speaker 7: and trying to step in there. The thing is, for 319 00:17:18,720 --> 00:17:21,200 Speaker 7: companies doing a deal that might have scrutiny in Europe, 320 00:17:21,240 --> 00:17:23,960 Speaker 7: it's a bit scarier than in the US because they 321 00:17:23,960 --> 00:17:26,520 Speaker 7: have the ability under their law to actually block a deal, 322 00:17:26,960 --> 00:17:29,720 Speaker 7: whereas the US regulators don't. They have to go to 323 00:17:29,760 --> 00:17:31,840 Speaker 7: court and they have to win in court in order 324 00:17:31,880 --> 00:17:34,320 Speaker 7: to actually block a deal. It is far more difficult 325 00:17:34,320 --> 00:17:36,960 Speaker 7: for them. It is easier in the EU. And Netflix, 326 00:17:37,000 --> 00:17:39,040 Speaker 7: by the way, is gigantic. I didn't know this until 327 00:17:39,080 --> 00:17:41,520 Speaker 7: I started looking at the deal, but it's really really. 328 00:17:41,280 --> 00:17:42,359 Speaker 3: Big outside the US. 329 00:17:42,840 --> 00:17:46,080 Speaker 7: An HBO is getting bigger in many of the countries 330 00:17:46,080 --> 00:17:48,960 Speaker 7: in Europe. It's recently expanded in Italy, in a seven 331 00:17:49,000 --> 00:17:49,880 Speaker 7: or eight other countries. 332 00:17:50,119 --> 00:17:53,400 Speaker 3: So they will that deal. I think no matter which. 333 00:17:53,160 --> 00:17:56,000 Speaker 7: Company ends up buying, Warner Brothers is going to get 334 00:17:56,000 --> 00:17:59,239 Speaker 7: a lot of scrutiny, and certainly scrutiny in EU, and 335 00:17:59,280 --> 00:18:01,320 Speaker 7: that is going to be one area where they're going 336 00:18:01,359 --> 00:18:02,800 Speaker 7: to have to work, I think, to get clearance. 337 00:18:03,400 --> 00:18:05,280 Speaker 5: Jen The past couple of years saw a lot of 338 00:18:05,400 --> 00:18:09,040 Speaker 5: high profile antitrust cases, specifically within big tech. We had 339 00:18:09,119 --> 00:18:12,359 Speaker 5: rulings against Google and Meta. What kind of precedent have 340 00:18:12,480 --> 00:18:15,760 Speaker 5: they set for big tech regulation in twenty twenty six. 341 00:18:16,000 --> 00:18:18,280 Speaker 7: Well, what they're showing is that it's going to be very, 342 00:18:18,359 --> 00:18:21,360 Speaker 7: very difficult for US and anti trust agencies to actually 343 00:18:21,560 --> 00:18:24,760 Speaker 7: tame what they view as monopolistic conduct. I mean, they 344 00:18:25,080 --> 00:18:29,480 Speaker 7: did win technically against Google with respect to monopolizing search, 345 00:18:29,760 --> 00:18:33,159 Speaker 7: but the remedy was fairly weak. They didn't get what 346 00:18:33,200 --> 00:18:35,920 Speaker 7: they were looking for. Look at what Google's doing now 347 00:18:35,960 --> 00:18:40,359 Speaker 7: with AI with Apple, which is exactly what the plaintiffs 348 00:18:40,359 --> 00:18:43,720 Speaker 7: were trying to avoid, you know, dominance in AI after 349 00:18:43,800 --> 00:18:44,760 Speaker 7: dominance in search. 350 00:18:46,000 --> 00:18:48,480 Speaker 3: So the difficulty they have is even. 351 00:18:48,280 --> 00:18:50,680 Speaker 7: Where they win on liability, they have a really tough 352 00:18:50,720 --> 00:18:53,720 Speaker 7: time with remedies. Most US federal judges are going to 353 00:18:53,760 --> 00:18:56,360 Speaker 7: be very cautious when it comes to meddling in business 354 00:18:56,600 --> 00:18:59,240 Speaker 7: and the way a sector may develop, especially in technology, 355 00:18:59,240 --> 00:19:01,960 Speaker 7: because it's so changing and nobody knows where it's going. 356 00:19:02,520 --> 00:19:05,520 Speaker 7: So when you have these cautious judges, you're just not 357 00:19:05,600 --> 00:19:08,560 Speaker 7: going to get the drastic remedies that are probably the 358 00:19:08,600 --> 00:19:11,840 Speaker 7: remedies that are needed to really do something about the 359 00:19:11,880 --> 00:19:14,680 Speaker 7: market positions of some of these companies. So we're seeing 360 00:19:14,680 --> 00:19:16,840 Speaker 7: that it's going to be difficult, but we haven't seen 361 00:19:16,880 --> 00:19:19,000 Speaker 7: as much of a let up on the cases that 362 00:19:19,040 --> 00:19:23,280 Speaker 7: were inherited from the Biden administration. This DOJ and FTC 363 00:19:23,400 --> 00:19:25,840 Speaker 7: are continuing to go after these cases in court. They're 364 00:19:25,880 --> 00:19:28,200 Speaker 7: continuing to pursue what you might think of as a 365 00:19:28,280 --> 00:19:31,840 Speaker 7: drastic remedy a structural remedy. The next test will be 366 00:19:31,840 --> 00:19:34,919 Speaker 7: Live Nation, which is going to trial March second against 367 00:19:34,920 --> 00:19:36,320 Speaker 7: the DOJ and some states. 368 00:19:36,760 --> 00:19:38,560 Speaker 2: Okay, so we'll watch for them. Then it's a bit 369 00:19:38,600 --> 00:19:42,800 Speaker 2: of leftover from the previous administration. We talk about regulators, 370 00:19:43,080 --> 00:19:46,359 Speaker 2: and that's usually how the antitrust enforcement shows up, or 371 00:19:46,400 --> 00:19:49,480 Speaker 2: any kind of pushback from government authorities. 372 00:19:49,480 --> 00:19:51,280 Speaker 3: But there's also the role of President. 373 00:19:50,880 --> 00:19:54,439 Speaker 2: Trump as well, and he's made clear that because he 374 00:19:54,880 --> 00:19:57,879 Speaker 2: has some firm opinions about certain companies and certain sectors, 375 00:19:57,920 --> 00:20:00,439 Speaker 2: that he's going to be what he says personally in 376 00:20:00,480 --> 00:20:00,880 Speaker 2: some of them. 377 00:20:00,920 --> 00:20:01,360 Speaker 3: That's right. 378 00:20:01,520 --> 00:20:03,399 Speaker 2: Is there a playbook for this? I mean, how do 379 00:20:03,840 --> 00:20:07,160 Speaker 2: regulators work in concert with a mercurial president? 380 00:20:07,680 --> 00:20:08,920 Speaker 3: You know, there really. 381 00:20:08,720 --> 00:20:11,600 Speaker 7: Isn't a playbook. This is somewhat unprecedented. Now there are 382 00:20:11,600 --> 00:20:13,720 Speaker 7: many that would argue that this kind of started during 383 00:20:13,720 --> 00:20:18,040 Speaker 7: the Biden administration, but we have authorities at the Federal 384 00:20:18,040 --> 00:20:20,280 Speaker 7: Trade Commission and Department of Justice that are very much 385 00:20:20,320 --> 00:20:22,520 Speaker 7: trying to align what they're doing in the anti trust 386 00:20:22,560 --> 00:20:25,760 Speaker 7: space with the policy priorities of this administration, I think 387 00:20:25,840 --> 00:20:28,520 Speaker 7: much more so than in the past. And they just 388 00:20:28,600 --> 00:20:31,560 Speaker 7: don't look like they'd be willing to buck the White 389 00:20:31,600 --> 00:20:36,320 Speaker 7: House if the White House has some feel or some something, 390 00:20:36,440 --> 00:20:39,800 Speaker 7: you know, an issue with the deal. Right, So we're 391 00:20:39,800 --> 00:20:42,879 Speaker 7: seeing a lot of alignment, and we're also seeing a 392 00:20:42,920 --> 00:20:45,880 Speaker 7: lot of reemptive alignment. It's preemptive alignment. And we're seeing 393 00:20:45,880 --> 00:20:48,520 Speaker 7: a lot of lobbying which we hadn't seen before too 394 00:20:48,600 --> 00:20:51,719 Speaker 7: in the overruling of the Anti Trust Division by senior 395 00:20:51,760 --> 00:20:55,280 Speaker 7: officials who are talking to lobbyists. And so there is 396 00:20:55,320 --> 00:20:57,359 Speaker 7: a lot of concern right now in the anti trust 397 00:20:57,359 --> 00:21:00,960 Speaker 7: community about the rule of lobbying really prevailing over the 398 00:21:01,040 --> 00:21:03,560 Speaker 7: rule of law when it comes to merger enforcement. 399 00:21:04,080 --> 00:21:05,920 Speaker 2: And this is stuff that we see after the fact, 400 00:21:06,320 --> 00:21:09,040 Speaker 2: after an announcement has made, as opposed to during it. 401 00:21:09,119 --> 00:21:09,560 Speaker 4: That's right. 402 00:21:09,600 --> 00:21:11,720 Speaker 7: We see reports and of course I'm not privy to 403 00:21:11,880 --> 00:21:14,239 Speaker 7: what's going on behind closed doors, but there has been 404 00:21:14,280 --> 00:21:17,520 Speaker 7: a lot of news reporting and a former senior FTC 405 00:21:17,600 --> 00:21:20,520 Speaker 7: official who recently left, who has spoken out about some 406 00:21:20,640 --> 00:21:22,160 Speaker 7: of the activities related to the. 407 00:21:22,119 --> 00:21:23,440 Speaker 3: Hewlett Packard Juniper deal. 408 00:21:23,640 --> 00:21:26,120 Speaker 7: Now, most recently, we have a deal between two huge 409 00:21:26,119 --> 00:21:29,560 Speaker 7: real estate brokerages, Compass and Anywhere, that was cleared very 410 00:21:29,600 --> 00:21:32,640 Speaker 7: quickly without even a deep investigation by the Federal Trade 411 00:21:32,640 --> 00:21:35,600 Speaker 7: Commission upside the Department of Justice. That surprised a lot 412 00:21:35,640 --> 00:21:37,479 Speaker 7: of people. I think it even surprised the companies that 413 00:21:37,480 --> 00:21:41,359 Speaker 7: have projected to close much later this year. And apparently 414 00:21:41,400 --> 00:21:43,399 Speaker 7: that was also because lobbyist had stepped in. 415 00:21:44,520 --> 00:21:47,440 Speaker 2: Stay with us more from Bloomberg Intelligence coming up after this. 416 00:21:51,160 --> 00:21:54,879 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 417 00:21:54,960 --> 00:21:58,040 Speaker 1: weekdays at ten am easterne on Apple Coarplay and Android 418 00:21:58,040 --> 00:22:01,360 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 419 00:22:01,400 --> 00:22:04,520 Speaker 1: you get your podcasts, or watch us live on YouTube. 420 00:22:05,440 --> 00:22:07,760 Speaker 2: We need to talk about AI, not so far, not 421 00:22:07,840 --> 00:22:10,480 Speaker 2: so much so far as to how it's impacting the 422 00:22:10,520 --> 00:22:13,000 Speaker 2: stock market, because we've seen that and we see that today, 423 00:22:13,119 --> 00:22:16,480 Speaker 2: but how companies are actually integrating it and how consumers 424 00:22:16,520 --> 00:22:20,600 Speaker 2: are experiencing it. Lindsay Dutch is our Bloomberg Intelligence Consumer 425 00:22:20,640 --> 00:22:24,439 Speaker 2: Hardlines senior analysts, and she's been researching this idea of 426 00:22:24,520 --> 00:22:29,280 Speaker 2: retailers embracing AI. But I guess there's a recognition, Lindsay 427 00:22:29,359 --> 00:22:33,320 Speaker 2: that for impulse purchases, which are so critical for the industry, 428 00:22:34,040 --> 00:22:36,040 Speaker 2: you still need a human touch, so it can't be 429 00:22:36,080 --> 00:22:39,920 Speaker 2: done remotely. It can't be done virtually. It's usually done 430 00:22:39,920 --> 00:22:41,840 Speaker 2: in person, and it's kind of unpredictable. 431 00:22:44,080 --> 00:22:47,000 Speaker 8: Yes, Hi Scarlett, thanks so much for having me. I 432 00:22:47,240 --> 00:22:50,679 Speaker 8: just returned from the NRF conference, forty thousand people. There 433 00:22:50,680 --> 00:22:53,880 Speaker 8: lots of retailer leaders there. You know, AI was all 434 00:22:53,920 --> 00:22:56,400 Speaker 8: the buzz. It was pretty much the topic of every session. 435 00:22:58,040 --> 00:22:59,800 Speaker 8: And as I think about it, there's a lot of 436 00:23:00,040 --> 00:23:04,320 Speaker 8: really cool technology going into this, and retailers are mostly 437 00:23:04,440 --> 00:23:08,520 Speaker 8: using AI to improve employee productivity, move employees up the 438 00:23:08,600 --> 00:23:14,159 Speaker 8: value chain, improve afflirational efficiency. And on the customer side, 439 00:23:14,280 --> 00:23:16,840 Speaker 8: we're mostly seeing it in terms of like a customer 440 00:23:16,880 --> 00:23:20,480 Speaker 8: service chatbot, maybe some personalization when you look at your 441 00:23:20,560 --> 00:23:24,080 Speaker 8: email ads. But there's you know, new levels that are 442 00:23:24,080 --> 00:23:26,639 Speaker 8: coming that will really you know, amp up. You know, 443 00:23:26,840 --> 00:23:31,000 Speaker 8: AI's place in that retail shopping journey. But as you mentioned, 444 00:23:31,040 --> 00:23:33,960 Speaker 8: I think, you know that spur of the moment, that's spontaneity, 445 00:23:34,000 --> 00:23:35,880 Speaker 8: when you find something that you love and you have 446 00:23:35,920 --> 00:23:36,480 Speaker 8: to buy it. 447 00:23:36,840 --> 00:23:37,879 Speaker 3: You know, that's a big. 448 00:23:37,720 --> 00:23:41,840 Speaker 8: Piece of the shopping and retail world, and that really 449 00:23:41,880 --> 00:23:45,240 Speaker 8: still you need some human element in that process. 450 00:23:45,840 --> 00:23:48,520 Speaker 5: Lindsay, we talk often about the death of brick and 451 00:23:48,560 --> 00:23:51,919 Speaker 5: mortar stores. People aren't going into physical stores as much 452 00:23:51,920 --> 00:23:54,680 Speaker 5: as they are shopping online. Do you think that AI 453 00:23:54,800 --> 00:23:57,800 Speaker 5: can reignite the excitement for going into a store and 454 00:23:57,880 --> 00:23:59,360 Speaker 5: experiencing the technology. 455 00:24:00,600 --> 00:24:03,720 Speaker 8: So I actually think we're already seeing a return to 456 00:24:03,760 --> 00:24:06,119 Speaker 8: brick and mortar, you know, coming out of the pandemic. 457 00:24:06,200 --> 00:24:08,919 Speaker 8: You know, people realize how important it is to have 458 00:24:08,960 --> 00:24:13,480 Speaker 8: an in person experience. More recently, you know, I've heard comments, 459 00:24:13,640 --> 00:24:15,800 Speaker 8: you know, I follow best Buy. You know they have 460 00:24:15,920 --> 00:24:19,320 Speaker 8: talked about that gen Z and younger shoppers are showing 461 00:24:19,320 --> 00:24:22,040 Speaker 8: a much stronger preference to shop in the store, to 462 00:24:22,280 --> 00:24:25,280 Speaker 8: talk to their geek squad, you know, you know, to 463 00:24:25,320 --> 00:24:28,000 Speaker 8: get advice, to browse things in person. We also see 464 00:24:28,000 --> 00:24:30,960 Speaker 8: that from an alta beauty as well. So I do 465 00:24:31,040 --> 00:24:33,800 Speaker 8: think e commerce penetation will continue to rise. 466 00:24:33,840 --> 00:24:34,399 Speaker 3: As a whole. 467 00:24:34,840 --> 00:24:37,840 Speaker 8: I think these new technologies will continue to support more 468 00:24:37,880 --> 00:24:41,720 Speaker 8: shopping online, but I do think there is a personal 469 00:24:41,800 --> 00:24:46,520 Speaker 8: element that will remain. And you know, we see strong 470 00:24:46,600 --> 00:24:49,280 Speaker 8: brick and mortar demand on the retail real estate side, 471 00:24:49,320 --> 00:24:51,600 Speaker 8: and that is expected to continue for some time. 472 00:24:52,800 --> 00:24:56,119 Speaker 2: Having said all that, how does AI enhance the ability 473 00:24:56,240 --> 00:25:00,679 Speaker 2: for stores to be able to reach out to consumers 474 00:25:00,840 --> 00:25:05,400 Speaker 2: so that they're there and have the right recommendations when 475 00:25:05,480 --> 00:25:08,560 Speaker 2: consumers are in the mood to make impulse purchases. 476 00:25:09,600 --> 00:25:13,160 Speaker 8: Yeah, so right now, I think the best consumer facing 477 00:25:14,119 --> 00:25:18,040 Speaker 8: use of AI is really increasing discovery exactly what you're saying, 478 00:25:18,200 --> 00:25:22,399 Speaker 8: So being able to serve up product online when a 479 00:25:22,440 --> 00:25:24,640 Speaker 8: customer is looking for it. And you know, this new 480 00:25:24,720 --> 00:25:29,440 Speaker 8: tool that Google co developed with Walmart and others, Universal 481 00:25:29,640 --> 00:25:32,920 Speaker 8: Commerce Protocol, is going to do just that. So you 482 00:25:32,960 --> 00:25:36,240 Speaker 8: can pop into this tool which is powered by Gemini, 483 00:25:37,000 --> 00:25:39,000 Speaker 8: and you can say I'm looking for a navy boot 484 00:25:39,000 --> 00:25:41,920 Speaker 8: blazer that I don't want to have dry cleaned, and 485 00:25:42,240 --> 00:25:46,280 Speaker 8: it will serve up you know, the product from the brand. 486 00:25:47,000 --> 00:25:51,560 Speaker 8: You can transact right there, so it's all seamless. Something 487 00:25:51,640 --> 00:25:54,560 Speaker 8: like that, you know, is a great tool to bring 488 00:25:55,080 --> 00:25:58,480 Speaker 8: product directly to the person and close the gap between 489 00:25:58,760 --> 00:26:01,959 Speaker 8: looking for something that you want, finding it, and transacting it. 490 00:26:02,520 --> 00:26:04,840 Speaker 8: And we see a lot of technology, you know, coming 491 00:26:04,880 --> 00:26:07,560 Speaker 8: to the fore that that's going to allow that to happen. 492 00:26:08,440 --> 00:26:12,240 Speaker 5: Lindsay, AI and new technology can be really complicated for 493 00:26:12,400 --> 00:26:15,879 Speaker 5: consumers to navigate. What are companies doing to help guide 494 00:26:15,880 --> 00:26:19,760 Speaker 5: shoppers through maximizing the experience they get with AI. 495 00:26:21,359 --> 00:26:22,520 Speaker 3: Yeah, that's a tough one. 496 00:26:22,600 --> 00:26:24,960 Speaker 8: I mean I think that you know, people in generally 497 00:26:25,240 --> 00:26:28,880 Speaker 8: are using more tools like Gemini, you know, for all 498 00:26:28,920 --> 00:26:32,639 Speaker 8: sorts of things chat, GPT that will you increase that 499 00:26:32,760 --> 00:26:35,600 Speaker 8: comfort level. And we have seen over time, you know, 500 00:26:35,880 --> 00:26:39,080 Speaker 8: I also cover home furnishings. You know, in the beginning, 501 00:26:39,160 --> 00:26:41,280 Speaker 8: when people were starting to transact online, like no one 502 00:26:41,320 --> 00:26:43,960 Speaker 8: wanted to buy a couch or a big product like 503 00:26:44,000 --> 00:26:45,879 Speaker 8: that that that you would typically want to sit on 504 00:26:45,960 --> 00:26:47,159 Speaker 8: and feel. 505 00:26:47,560 --> 00:26:49,439 Speaker 3: And you know that over time, you. 506 00:26:49,440 --> 00:26:53,679 Speaker 8: Know, retailers have figured out how to showcase their product 507 00:26:53,720 --> 00:26:57,560 Speaker 8: in a digital way that makes comfortable customers more comfortable 508 00:26:57,560 --> 00:27:01,480 Speaker 8: transacting on a big ticket item like that that you 509 00:27:01,520 --> 00:27:04,040 Speaker 8: would normally really want to see in person. And I 510 00:27:04,080 --> 00:27:06,640 Speaker 8: think the same thing would be true for these other 511 00:27:06,800 --> 00:27:10,800 Speaker 8: new technologies. It will take time, you know, adoption will rise, 512 00:27:10,920 --> 00:27:14,040 Speaker 8: it will rise slowly, and that's why I think it's 513 00:27:14,040 --> 00:27:16,280 Speaker 8: a real balance. You have to be, you know, in 514 00:27:16,280 --> 00:27:18,359 Speaker 8: that tech world, but you also have to be in person. 515 00:27:18,960 --> 00:27:21,960 Speaker 2: Well said what surprised you the most, lindsay, very quickly 516 00:27:22,040 --> 00:27:24,119 Speaker 2: at NRF twenty twenty six when you went there. 517 00:27:24,000 --> 00:27:25,720 Speaker 3: What kind of blew you away? 518 00:27:27,560 --> 00:27:31,919 Speaker 8: You know, I think the retail environment right now has 519 00:27:32,160 --> 00:27:35,760 Speaker 8: in twenty twenty five, is an extremely challenging environment, you know, 520 00:27:35,800 --> 00:27:38,159 Speaker 8: And I think what's most impressive is, you know, the 521 00:27:38,160 --> 00:27:41,200 Speaker 8: people in the industry are just so excited to take 522 00:27:41,240 --> 00:27:45,160 Speaker 8: on new challenges in twenty twenty six, you know, even 523 00:27:45,200 --> 00:27:48,400 Speaker 8: though we're still battling costs from tariffs, trying to implement 524 00:27:48,400 --> 00:27:52,600 Speaker 8: all this technology, a difficult consumer backdrop. So there's just 525 00:27:52,680 --> 00:27:55,320 Speaker 8: a lot of excitement in the industry and everyone is 526 00:27:55,359 --> 00:27:58,320 Speaker 8: just so excited to rise to that next new challenge. 527 00:27:58,320 --> 00:27:59,439 Speaker 8: And I love that energy. 528 00:28:00,280 --> 00:28:04,960 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 529 00:28:05,160 --> 00:28:09,120 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 530 00:28:09,320 --> 00:28:12,600 Speaker 1: ten am to noon Eastern on Bloomberg dot com, the 531 00:28:12,680 --> 00:28:16,560 Speaker 1: iHeartRadio app, tune In, and the Bloomberg Business app. You 532 00:28:16,600 --> 00:28:19,879 Speaker 1: can also watch us live every weekday on YouTube and 533 00:28:20,119 --> 00:28:22,000 Speaker 1: always on the Bloomberg terminal.