1
00:00:00,240 --> 00:00:07,720
Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.

2
00:00:10,840 --> 00:00:13,880
Speaker 2: This is Bloomberg Daybreak Weekend, our global look at the

3
00:00:13,880 --> 00:00:16,440
Speaker 2: top stories in the coming week from our Daybreak anchors

4
00:00:16,520 --> 00:00:19,120
Speaker 2: all around the world. Straight ahead on the program, well,

5
00:00:19,120 --> 00:00:21,400
Speaker 2: look at what we can expect from homebuilders in the

6
00:00:21,440 --> 00:00:24,079
Speaker 2: months ahead. I'm Nathan Hager in Washington.

7
00:00:24,280 --> 00:00:26,560
Speaker 3: I'm Callin Hecker in London. While we're looking ahead to

8
00:00:26,600 --> 00:00:29,880
Speaker 3: the UK jobs numbers and asking whether AI is starting

9
00:00:29,920 --> 00:00:31,280
Speaker 3: to affect productivity.

10
00:00:31,520 --> 00:00:34,400
Speaker 4: I'm Doug Prisner looking at the outlook for Chinese consumer

11
00:00:34,479 --> 00:00:36,879
Speaker 4: spending during the Lunar New Year holiday.

12
00:00:38,360 --> 00:00:42,400
Speaker 1: That's all straight ahead on Bloomberg Daybreak Weekend on Bloomberg

13
00:00:42,400 --> 00:00:46,120
Speaker 1: eleven three year, New York, Bloomberg ninety nine to one, Washington, DC,

14
00:00:46,600 --> 00:00:51,760
Speaker 1: Bloomberg ninety two nine, Boston, DAB Digital Radio, London, Sirias

15
00:00:51,920 --> 00:00:55,440
Speaker 1: XM one twenty one, and around the world on Bloomberg Radio,

16
00:00:55,480 --> 00:00:57,680
Speaker 1: dot Com and the Bloomberg Business App.

17
00:01:02,760 --> 00:01:05,760
Speaker 2: Good day to you. I'm Nathan Hager. We begin today's

18
00:01:05,800 --> 00:01:09,520
Speaker 2: program with homebuilders. Recently, we heard the Trump administration is

19
00:01:09,560 --> 00:01:13,680
Speaker 2: exploring an antitrust investigation into the industry, as the White

20
00:01:13,720 --> 00:01:17,600
Speaker 2: House sharpens its focus on tackling the housing affordability crisis

21
00:01:17,840 --> 00:01:19,920
Speaker 2: for more and what we can expect from homebuilders in

22
00:01:19,959 --> 00:01:22,679
Speaker 2: the months ahead. We're joined by Drew Reading, us home

23
00:01:22,720 --> 00:01:26,400
Speaker 2: building analyst for Bloomberg Intelligence. Drew, how do you see

24
00:01:26,400 --> 00:01:28,600
Speaker 2: the backdrop now in the new home market?

25
00:01:29,080 --> 00:01:32,080
Speaker 5: So in the new home market, the backdrop is still

26
00:01:32,120 --> 00:01:35,720
Speaker 5: a little bit challenged. We have made some progress on affordability, which,

27
00:01:35,760 --> 00:01:38,760
Speaker 5: as we all know, has been the primary constraint for

28
00:01:38,840 --> 00:01:41,000
Speaker 5: buyers out there in the market. Mortgage rates are down

29
00:01:41,040 --> 00:01:44,480
Speaker 5: about one hundred basis points from where we were last year.

30
00:01:45,800 --> 00:01:48,280
Speaker 5: But what we've heard pretty consistently from the builders that

31
00:01:48,320 --> 00:01:51,120
Speaker 5: we talked to is that it's not just about affordability.

32
00:01:51,840 --> 00:01:54,560
Speaker 5: It's also about sentiment. You have more consumers out there

33
00:01:54,560 --> 00:01:57,360
Speaker 5: in the market who may be concerned about the direction

34
00:01:57,440 --> 00:02:00,480
Speaker 5: of the economy, the outlook for employment. There's not a

35
00:02:00,480 --> 00:02:02,400
Speaker 5: lot of urgency. And you know, one of the things

36
00:02:02,440 --> 00:02:04,000
Speaker 5: I think that's happening is you have a lot of

37
00:02:04,000 --> 00:02:07,920
Speaker 5: people sitting on the fence who are saying to themselves, look,

38
00:02:07,960 --> 00:02:10,200
Speaker 5: I think rates might be coming down. I think home

39
00:02:10,240 --> 00:02:12,040
Speaker 5: prices might be coming down. So I'm going to take

40
00:02:12,040 --> 00:02:14,680
Speaker 5: a wait and see approach. Now, with that being said,

41
00:02:14,720 --> 00:02:17,200
Speaker 5: we think that the market can grow this year from

42
00:02:17,240 --> 00:02:19,120
Speaker 5: a sales perspective, A lot of that's going to be

43
00:02:19,160 --> 00:02:22,040
Speaker 5: driven by community count growths. So we actually have new

44
00:02:22,040 --> 00:02:25,080
Speaker 5: home sales rising in the mid single digit range. But

45
00:02:25,120 --> 00:02:27,320
Speaker 5: we do think that housing starts, which is probably the

46
00:02:27,360 --> 00:02:30,839
Speaker 5: most widely followed measure in the new home market, will

47
00:02:30,880 --> 00:02:33,960
Speaker 5: be flatish because builders want to work through their standing

48
00:02:33,960 --> 00:02:36,040
Speaker 5: inventory before putting new product in the ground.

49
00:02:36,320 --> 00:02:39,720
Speaker 2: So that sentiment damper you're talking about, is that across

50
00:02:39,760 --> 00:02:42,960
Speaker 2: the board or is it just in the luxury sector,

51
00:02:43,120 --> 00:02:45,359
Speaker 2: the load to middle income sector? How does it look

52
00:02:45,880 --> 00:02:46,320
Speaker 2: that way?

53
00:02:48,080 --> 00:02:50,800
Speaker 5: Yes, so I think we've heard pretty much across the

54
00:02:50,800 --> 00:02:54,120
Speaker 5: board from builders that sentiment has been a major issue.

55
00:02:54,320 --> 00:02:56,880
Speaker 5: You know, when you start to look at customer profiles,

56
00:02:56,880 --> 00:02:59,960
Speaker 5: certainly the entry level has been a little bit more pressured.

57
00:03:00,040 --> 00:03:03,160
Speaker 5: If you think of that buyer, they're typically more sensitive

58
00:03:03,200 --> 00:03:06,920
Speaker 5: to fluctuations in mortgage rates and monthly payments compared to

59
00:03:07,720 --> 00:03:09,639
Speaker 5: you know, call it a Toll Brothers who is more

60
00:03:09,639 --> 00:03:11,920
Speaker 5: exposed to the luxury end of the market, where you know,

61
00:03:11,960 --> 00:03:15,360
Speaker 5: the buyer is more affluent and doesn't have those same

62
00:03:15,400 --> 00:03:18,280
Speaker 5: brate considerations. But you have to think of housing as

63
00:03:18,320 --> 00:03:22,000
Speaker 5: an ecosystem so while the higher end may be doing better,

64
00:03:22,120 --> 00:03:25,280
Speaker 5: they still need to see movement at lower price points

65
00:03:25,320 --> 00:03:28,280
Speaker 5: in order to facilitate those move up home sales.

66
00:03:28,520 --> 00:03:31,919
Speaker 2: So if builders are sort of working through this despite

67
00:03:32,000 --> 00:03:35,240
Speaker 2: those sentiment concerns, what could that mean for their margins.

68
00:03:35,840 --> 00:03:38,360
Speaker 5: Yeah, that's a great question, and it's probably the number

69
00:03:38,360 --> 00:03:41,800
Speaker 5: one thing on investors' minds because margins have come in

70
00:03:41,880 --> 00:03:44,280
Speaker 5: pretty significantly over the last couple of years. And the

71
00:03:44,360 --> 00:03:47,320
Speaker 5: reason is because builders have had to be pretty aggressive

72
00:03:47,840 --> 00:03:50,120
Speaker 5: in their use of mortgage rate buydowns in order to

73
00:03:50,200 --> 00:03:54,240
Speaker 5: stimulate demand. Now it has helped them maintain sales levels.

74
00:03:54,240 --> 00:03:56,680
Speaker 5: If you look at you know, how new home sales

75
00:03:56,720 --> 00:03:59,120
Speaker 5: has trended verse the resale market, They've held up a

76
00:03:59,120 --> 00:04:02,040
Speaker 5: lot better, but they're having to pay a lot in

77
00:04:02,160 --> 00:04:04,600
Speaker 5: order to buy down these mortgage rates. And you know,

78
00:04:04,600 --> 00:04:06,680
Speaker 5: what we've heard from those that have reported earning so

79
00:04:06,800 --> 00:04:09,320
Speaker 5: far is that they expect the use of incentives is

80
00:04:09,320 --> 00:04:12,600
Speaker 5: going to remain elevated through the spring selling season because

81
00:04:12,600 --> 00:04:14,880
Speaker 5: there's still, you know, a lot of challenges out there.

82
00:04:15,160 --> 00:04:18,839
Speaker 2: We've seen a lot of focus from Washington on the

83
00:04:18,920 --> 00:04:23,960
Speaker 2: housing sector as well. These ideas about limiting institutional purchases

84
00:04:24,040 --> 00:04:27,640
Speaker 2: of single family homes, maybe allowing more use of four

85
00:04:27,680 --> 00:04:31,520
Speaker 2: O one k's for a first time down payment, things

86
00:04:31,600 --> 00:04:34,799
Speaker 2: like that. Does that affect your view on the outlook

87
00:04:34,839 --> 00:04:37,520
Speaker 2: for the housing market if some of these policy ideas

88
00:04:37,520 --> 00:04:38,279
Speaker 2: come into fruition.

89
00:04:39,440 --> 00:04:42,560
Speaker 5: Yeah. So policy has certainly become the biggest wildcard I

90
00:04:42,600 --> 00:04:44,800
Speaker 5: think for home builders in twenty twenty six. They've been

91
00:04:45,320 --> 00:04:48,040
Speaker 5: squarely in the crosshairs of the administration for four or

92
00:04:48,080 --> 00:04:50,520
Speaker 5: five months or so, given you know, the heightened focus

93
00:04:50,560 --> 00:04:54,360
Speaker 5: on affordability. You know, outside some of the things you discussed,

94
00:04:54,360 --> 00:04:57,760
Speaker 5: like the proposalal ban institutional purchases, we really don't have

95
00:04:57,800 --> 00:05:00,920
Speaker 5: a lot of concrete ideas. We've got plenty of tweets

96
00:05:00,920 --> 00:05:04,679
Speaker 5: and leaked news stories, but nothing substantial yet. I think,

97
00:05:04,960 --> 00:05:06,800
Speaker 5: you know, we could hear something at the State of

98
00:05:06,800 --> 00:05:08,680
Speaker 5: the Union in a couple of weeks. What that may be,

99
00:05:08,760 --> 00:05:11,600
Speaker 5: I don't know, but you know, the administration has been

100
00:05:11,640 --> 00:05:15,080
Speaker 5: critical of the large public home builders in particular. You know,

101
00:05:15,120 --> 00:05:17,640
Speaker 5: they've talked about their landholding, saying, you know, they owned

102
00:05:17,640 --> 00:05:19,680
Speaker 5: two million lots, they need to start building on them,

103
00:05:20,040 --> 00:05:23,160
Speaker 5: and they've even threatened to withhold liquidity from them if

104
00:05:23,200 --> 00:05:26,360
Speaker 5: they don't start building. You know, they said the builders

105
00:05:26,360 --> 00:05:28,680
Speaker 5: shouldn't be buying back their stock, which has become a

106
00:05:28,680 --> 00:05:31,479
Speaker 5: big part of their business model. And then the other

107
00:05:31,520 --> 00:05:33,400
Speaker 5: piece that we think could be a risk going forward

108
00:05:33,480 --> 00:05:37,240
Speaker 5: is you know, the discussion about mortgage rate buydowns. You know,

109
00:05:37,279 --> 00:05:39,520
Speaker 5: there were some tweets out there saying that they're artificially

110
00:05:39,560 --> 00:05:42,320
Speaker 5: propping up prices. So it does seem that they're looking

111
00:05:42,360 --> 00:05:44,520
Speaker 5: at everything, and I think ultimately what it does is

112
00:05:44,600 --> 00:05:48,760
Speaker 5: creates a more volatile operating environment and two way volatility

113
00:05:48,760 --> 00:05:49,400
Speaker 5: for the stocks.

114
00:05:49,760 --> 00:05:53,159
Speaker 2: Are you seeing the industry actively making preparations for whatever

115
00:05:53,200 --> 00:05:55,400
Speaker 2: could come down from the Trump administration?

116
00:05:55,520 --> 00:05:57,880
Speaker 5: Drew, yes, So, I mean at this point it's kind

117
00:05:57,880 --> 00:06:00,520
Speaker 5: of just business as usual. We've heard from most of

118
00:06:00,600 --> 00:06:04,080
Speaker 5: them that you know, really since the end of last year,

119
00:06:04,120 --> 00:06:09,359
Speaker 5: they've been working alongside the administration and policymakers in a

120
00:06:09,400 --> 00:06:13,080
Speaker 5: collaborative manner to try to come up with solutions, you know,

121
00:06:13,120 --> 00:06:15,320
Speaker 5: whether they be demand side stimulants or a way to

122
00:06:15,400 --> 00:06:19,840
Speaker 5: get more supply into the market. So as of now,

123
00:06:19,880 --> 00:06:22,120
Speaker 5: it's business as usual. We'll have to wait until it

124
00:06:22,120 --> 00:06:22,840
Speaker 5: comes down the pike.

125
00:06:23,200 --> 00:06:25,120
Speaker 2: Thanks for this, Drew, great having you on with us.

126
00:06:25,240 --> 00:06:29,280
Speaker 2: That's Drew Redding homebuilders analyst for Bloomberg Intelligence. Let's take

127
00:06:29,279 --> 00:06:31,480
Speaker 2: a look now at some stocks making news in the

128
00:06:31,520 --> 00:06:34,680
Speaker 2: week ahead. I'm Nathan Hager, joined by Bloomberg News Equities

129
00:06:34,720 --> 00:06:38,280
Speaker 2: reporter Alexandra Semanova and Alex are gonna hear from some

130
00:06:38,400 --> 00:06:40,880
Speaker 2: big ones this week in terms of the earnings, The

131
00:06:40,880 --> 00:06:45,040
Speaker 2: biggest name in retail is reporting on Thursday. What are

132
00:06:45,040 --> 00:06:46,800
Speaker 2: we expecting from Walmart?

133
00:06:47,200 --> 00:06:49,799
Speaker 6: Hey, Nathan, So it is indeed going to be another

134
00:06:50,160 --> 00:06:54,039
Speaker 6: busy earnings week. Walmart is such a bellweather of low

135
00:06:54,160 --> 00:06:56,760
Speaker 6: and mid income consumers, so that's going to be an

136
00:06:56,800 --> 00:06:59,880
Speaker 6: important company to watch. It is scheduled to report earnings

137
00:07:00,000 --> 00:07:03,640
Speaker 6: results before the bell on February nineteenth. And something to

138
00:07:03,760 --> 00:07:06,240
Speaker 6: note ahead of its earnings read out is Walmart just

139
00:07:06,279 --> 00:07:09,680
Speaker 6: saw its market cap eclips the one trillion dollar mark

140
00:07:09,720 --> 00:07:12,840
Speaker 6: on February third for the first time ever. This is

141
00:07:13,400 --> 00:07:16,040
Speaker 6: something that you don't see from retailers. It's something you

142
00:07:16,120 --> 00:07:19,400
Speaker 6: typically see from tech giants. So Walmart is now in

143
00:07:19,440 --> 00:07:23,720
Speaker 6: a category typically occupied by big tech heavyweights such as

144
00:07:24,160 --> 00:07:28,600
Speaker 6: Nvidia and Alphabet Inc. And Walmart is a long time favorite,

145
00:07:28,640 --> 00:07:31,920
Speaker 6: of course, of bargain hunting consumers, which is why it

146
00:07:31,960 --> 00:07:35,320
Speaker 6: has been doing so well. It has flexed its massive

147
00:07:35,400 --> 00:07:39,680
Speaker 6: scale and supplier network to keep prices low and grab

148
00:07:39,800 --> 00:07:44,000
Speaker 6: market share across various income levels. And not only has

149
00:07:44,040 --> 00:07:48,160
Speaker 6: Walmart maintained its appeal to households looking for value, it's

150
00:07:48,200 --> 00:07:52,680
Speaker 6: also been recently drawing some new wealthier shoppers as well

151
00:07:52,680 --> 00:07:55,480
Speaker 6: with its online business. So when we get to those results,

152
00:07:55,520 --> 00:07:57,400
Speaker 6: some of the key metrics to watch will be same

153
00:07:57,840 --> 00:08:02,560
Speaker 6: store sales performance. That is going to be an important

154
00:08:03,280 --> 00:08:06,920
Speaker 6: metric to monitor growth for long term revenue and profit

155
00:08:07,480 --> 00:08:12,320
Speaker 6: expansion for the company, contribution from higher margin businesses to

156
00:08:12,640 --> 00:08:15,600
Speaker 6: and inventory management. And I want to point out that

157
00:08:15,640 --> 00:08:18,600
Speaker 6: the stock is up something like nineteen percent year to date,

158
00:08:18,720 --> 00:08:21,200
Speaker 6: so the bar is pretty high going into these results.

159
00:08:21,360 --> 00:08:24,680
Speaker 2: Yeah, certainly with a trillion dollar valuation now and with

160
00:08:24,760 --> 00:08:28,520
Speaker 2: the fact that Walmart recently relisted to the Nasdaq, it

161
00:08:28,560 --> 00:08:32,000
Speaker 2: really does seem like they're leaning into this tech side

162
00:08:32,040 --> 00:08:34,280
Speaker 2: of the story. But we're also going to hear from

163
00:08:34,640 --> 00:08:37,120
Speaker 2: another name that we think of more traditionally on the

164
00:08:37,120 --> 00:08:39,640
Speaker 2: tech side, door Dash reports on Tuesday.

165
00:08:39,320 --> 00:08:42,360
Speaker 6: Right, Yeah, it does, Nathan. So I'd say for this company,

166
00:08:42,400 --> 00:08:45,440
Speaker 6: the main thing investors will be watching is signs that

167
00:08:45,480 --> 00:08:49,120
Speaker 6: it can monetize on heavy capex spending, so during the

168
00:08:49,240 --> 00:08:52,720
Speaker 6: last earnings report from DoorDash, it took a record plunge

169
00:08:52,760 --> 00:08:55,400
Speaker 6: after the company said it's going to spend more on

170
00:08:55,840 --> 00:08:59,800
Speaker 6: investments next year to build new products and bolster internal tools,

171
00:09:00,280 --> 00:09:04,440
Speaker 6: which really weighed on its earnings forecast. These increased costs

172
00:09:04,440 --> 00:09:08,840
Speaker 6: contributed to a muted fourth quarter forecast for adjusted even

173
00:09:08,880 --> 00:09:12,120
Speaker 6: A specifically, with the company expecting that metric to be

174
00:09:12,520 --> 00:09:15,400
Speaker 6: around seven hundred and ten million dollars to eight hundred

175
00:09:15,440 --> 00:09:18,960
Speaker 6: and ten million dollars, so watch that number. Also watch

176
00:09:19,080 --> 00:09:22,160
Speaker 6: order growth, which is currently exceeding that of some of

177
00:09:22,160 --> 00:09:25,520
Speaker 6: its online delivery peers, and it's also supposed to get

178
00:09:25,520 --> 00:09:29,800
Speaker 6: a potential boost from Delivery, which it acquired recently, so

179
00:09:29,920 --> 00:09:33,320
Speaker 6: that's going to be something to monitor during those results.

180
00:09:34,040 --> 00:09:37,200
Speaker 6: And then it is also expanding into new categories beyond

181
00:09:37,320 --> 00:09:41,920
Speaker 6: just restaurant delivery, so groceries and convenience, which are expected

182
00:09:41,960 --> 00:09:45,800
Speaker 6: to aid with consumer retention and a head of the report,

183
00:09:45,840 --> 00:09:48,160
Speaker 6: some of the big Wall Street firms did lower their

184
00:09:48,200 --> 00:09:51,480
Speaker 6: price targets on the company. Bank of America was one

185
00:09:51,480 --> 00:09:55,040
Speaker 6: of them, lowering their price target to two hundred and

186
00:09:55,120 --> 00:09:57,720
Speaker 6: sixty dollars a share from three hundred and five dollars

187
00:09:57,720 --> 00:09:59,839
Speaker 6: a share, but it did still maintain a buy rating.

188
00:10:00,200 --> 00:10:03,880
Speaker 6: Goldman Sachs added DoorDash actually to its US conviction list,

189
00:10:04,000 --> 00:10:07,000
Speaker 6: so that's pretty positive. And one more thing to note is,

190
00:10:07,040 --> 00:10:10,840
Speaker 6: of course, DoorDash and Uber just lost a bid to

191
00:10:11,000 --> 00:10:14,200
Speaker 6: block a New York City law requiring a tipping option

192
00:10:14,320 --> 00:10:18,520
Speaker 6: to be presented to customers at checkout from going into effect,

193
00:10:18,600 --> 00:10:22,319
Speaker 6: so it's likely we're going to see perhaps management commentary

194
00:10:22,440 --> 00:10:25,760
Speaker 6: on that front. DoorDash has been having a pretty hard

195
00:10:25,760 --> 00:10:28,240
Speaker 6: start to the years, down something like twenty seven percent

196
00:10:28,320 --> 00:10:28,680
Speaker 6: so far.

197
00:10:29,120 --> 00:10:31,240
Speaker 2: Well, another big name we're going to hear from is

198
00:10:31,320 --> 00:10:36,280
Speaker 2: a bell Weather on the agriculture economy. Deer has really

199
00:10:36,320 --> 00:10:38,640
Speaker 2: been on a tear since the start of the year. Alex.

200
00:10:38,880 --> 00:10:41,839
Speaker 6: Yeah, it has been a really interesting company to watch,

201
00:10:41,880 --> 00:10:43,760
Speaker 6: given the fact that it's kind of been at the

202
00:10:43,800 --> 00:10:48,000
Speaker 6: center of Wall Street's big rotation trade into sectors outside

203
00:10:48,040 --> 00:10:51,360
Speaker 6: of technology. So it's actually trading at a record high

204
00:10:51,440 --> 00:10:54,320
Speaker 6: now amid a rally that has come as interest rate

205
00:10:54,400 --> 00:10:58,280
Speaker 6: cuts and strong US growth push investors into sectors of

206
00:10:58,320 --> 00:11:01,559
Speaker 6: the market closely linked to the health of the US economy.

207
00:11:01,640 --> 00:11:05,840
Speaker 6: So deer Cell's construction equipment in addition to its iconic

208
00:11:06,280 --> 00:11:09,440
Speaker 6: farmer machinery, and that's been an industry that up until

209
00:11:09,480 --> 00:11:12,600
Speaker 6: recently was really struggling. Investors are betting it could get

210
00:11:12,600 --> 00:11:16,040
Speaker 6: a boost from the Fed's monetary easing and some data

211
00:11:16,040 --> 00:11:19,160
Speaker 6: that showed that the US economy is expanding at a

212
00:11:19,160 --> 00:11:22,400
Speaker 6: healthy pace. So when the company reports earnings, Wall Street

213
00:11:22,400 --> 00:11:25,560
Speaker 6: will be looking for any update on its industry outlook.

214
00:11:26,000 --> 00:11:29,360
Speaker 6: Investors are still waiting for a rebound in the US

215
00:11:29,400 --> 00:11:33,240
Speaker 6: farm economy, specifically, so something that would spur farmers to

216
00:11:33,320 --> 00:11:37,840
Speaker 6: buy new tractors and other equipment. Deer shares had hit

217
00:11:37,880 --> 00:11:41,720
Speaker 6: a record last May on the same hopes, but that

218
00:11:41,800 --> 00:11:44,160
Speaker 6: turned out to be a headfake, So the key question

219
00:11:44,360 --> 00:11:47,880
Speaker 6: is will this also be The farm economy is projected

220
00:11:47,920 --> 00:11:51,120
Speaker 6: to extend its downturn actually through twenty twenty six so far,

221
00:11:52,200 --> 00:11:56,600
Speaker 6: expecting net farm income to fall by one percent according

222
00:11:56,640 --> 00:11:59,800
Speaker 6: to the USDA, and Deer also said in November that

223
00:11:59,840 --> 00:12:03,440
Speaker 6: it expected industry sales of large equipment to fall fifteen

224
00:12:03,520 --> 00:12:06,320
Speaker 6: percent to twenty percent in the US and Canada, So

225
00:12:06,800 --> 00:12:09,280
Speaker 6: we're going to see what it says on those fronts.

226
00:12:09,320 --> 00:12:12,000
Speaker 6: It is up nearly thirty two percent year to date,

227
00:12:12,360 --> 00:12:14,880
Speaker 6: yet again a company that has a really high bar

228
00:12:15,000 --> 00:12:16,120
Speaker 6: going into report.

229
00:12:16,360 --> 00:12:19,280
Speaker 2: Yeah, certainly sounds like it. Thanks for this, alex great

230
00:12:19,280 --> 00:12:20,800
Speaker 2: having you on with US's great to be with you.

231
00:12:20,960 --> 00:12:24,920
Speaker 2: That's Bloomberg News Equities reporter Alexandra Semonova. And coming up

232
00:12:24,960 --> 00:12:27,520
Speaker 2: on Bloomberg day Break weekend, we'll look ahead to jobs

233
00:12:27,600 --> 00:12:31,640
Speaker 2: numbers in the UK. Is AI starting to affect productivity.

234
00:12:31,920 --> 00:12:46,360
Speaker 2: I'm Nathan Hagar, and this is Bloomberg. This is Bloomberg

235
00:12:46,400 --> 00:12:49,160
Speaker 2: Daybreak Weekend, our global look ahead at the top stories

236
00:12:49,200 --> 00:12:52,280
Speaker 2: for investors in the coming week. I'm Nathan Hager in Washington.

237
00:12:52,520 --> 00:12:54,440
Speaker 2: Up later in our program we'll look ahead for what

238
00:12:54,480 --> 00:12:57,360
Speaker 2: to expect during the nine day Lunar New Year holiday

239
00:12:57,400 --> 00:13:01,440
Speaker 2: in China. But first, the UK is facing a tricky

240
00:13:01,520 --> 00:13:05,000
Speaker 2: mix of slowing growth, stubbornly high on employment, and mounting

241
00:13:05,040 --> 00:13:09,000
Speaker 2: global uncertainty from trade tensions to tariffs and political turmoil.

242
00:13:09,400 --> 00:13:11,520
Speaker 2: But amid the gloom, there is a growing debate over

243
00:13:11,520 --> 00:13:15,640
Speaker 2: whether artificial intelligence could help lift productivity and offset some

244
00:13:15,679 --> 00:13:18,600
Speaker 2: of the weakness in Britain's labor market, even as questions

245
00:13:18,640 --> 00:13:22,480
Speaker 2: mount about whether the technology is already displacing workers. After

246
00:13:22,559 --> 00:13:25,720
Speaker 2: recent GDP data out of the UK showed sluggish growth.

247
00:13:25,840 --> 00:13:29,200
Speaker 2: We get fresh jobs data from Britain next week. Let's

248
00:13:29,240 --> 00:13:32,360
Speaker 2: get more now from Bloomberg Daybreak Europe banker Caroline Hepger

249
00:13:32,520 --> 00:13:33,439
Speaker 2: in London.

250
00:13:33,400 --> 00:13:36,720
Speaker 3: Nathan AI is talked about as both a coming storm

251
00:13:36,760 --> 00:13:40,440
Speaker 3: but also a potential solution to Britain's growth woes. The

252
00:13:40,520 --> 00:13:44,360
Speaker 3: UK's unemployment rate has climbed to near COVID levels since

253
00:13:44,520 --> 00:13:47,960
Speaker 3: Labour took power in twenty twenty four, but head of

254
00:13:48,080 --> 00:13:50,720
Speaker 3: the UK jobs data in the next few days, there

255
00:13:50,840 --> 00:13:55,080
Speaker 3: is a new quirk in recent data. Some economists increasingly

256
00:13:55,160 --> 00:13:59,040
Speaker 3: think that productivity may actually be improving, and they wonder

257
00:13:59,120 --> 00:14:02,960
Speaker 3: if artificial intelligence adoption maybe playing a part. The Bank

258
00:14:03,000 --> 00:14:05,640
Speaker 3: of England Governor Andrew Bailey is one of them.

259
00:14:05,920 --> 00:14:08,760
Speaker 7: I'm an optimist on the potential for AI and robotics

260
00:14:08,800 --> 00:14:11,840
Speaker 7: to move the dial on productivity and thus on economic growth.

261
00:14:12,240 --> 00:14:14,800
Speaker 7: I'd like to think, though, that I'm a realistic optimist.

262
00:14:15,280 --> 00:14:18,280
Speaker 7: My impression is that we've made more progress so far

263
00:14:18,440 --> 00:14:22,640
Speaker 7: applying AI to well defined task based work rather than

264
00:14:22,640 --> 00:14:25,920
Speaker 7: some of the more ambitious goals. But I'd also say

265
00:14:26,000 --> 00:14:27,520
Speaker 7: I don't find that at all surprising.

266
00:14:28,400 --> 00:14:31,520
Speaker 3: So is AI a panacea and what impact is it

267
00:14:31,680 --> 00:14:35,200
Speaker 3: actually having on the UK economy. Joining us now in

268
00:14:35,240 --> 00:14:39,080
Speaker 3: studio is Bloomberg's UK economy reporter Arena Angel and our

269
00:14:39,080 --> 00:14:43,400
Speaker 3: Bloomberg Opinion colonist covering technology, Pamey Olson. Welcome to both

270
00:14:43,440 --> 00:14:45,640
Speaker 3: of you. Thanks for being with me, Erna. Can I

271
00:14:45,640 --> 00:14:48,320
Speaker 3: start with you just on the actual figures. What are

272
00:14:48,320 --> 00:14:51,680
Speaker 3: we expecting from the UK job's numbers in the next

273
00:14:51,720 --> 00:14:52,320
Speaker 3: few days.

274
00:14:53,240 --> 00:14:57,560
Speaker 8: So next week we'll get the jobs report for December

275
00:14:57,840 --> 00:15:00,520
Speaker 8: and the unemployment rate is actually expected to edge up again.

276
00:15:01,200 --> 00:15:03,920
Speaker 8: It's now at five point one percent. Some economists for

277
00:15:03,960 --> 00:15:06,520
Speaker 8: survey by Bloomberg think it will go up to five

278
00:15:06,560 --> 00:15:09,640
Speaker 8: point two percent. And this is just so you have

279
00:15:09,680 --> 00:15:12,760
Speaker 8: a sense of how important this is. It's the highest

280
00:15:12,800 --> 00:15:15,360
Speaker 8: since sort of COVID time. It's twenty twenty one, twenty

281
00:15:15,440 --> 00:15:19,000
Speaker 8: twenty and it will get worse in the next month,

282
00:15:19,160 --> 00:15:21,880
Speaker 8: but perhaps not for much longer. The Bank of England

283
00:15:22,000 --> 00:15:24,680
Speaker 8: kind of sees unemployment peaking at five point three percent

284
00:15:24,760 --> 00:15:27,960
Speaker 8: in spring, and you know, now this is starting to

285
00:15:28,040 --> 00:15:32,040
Speaker 8: raise important questions about the job's costs of their you know,

286
00:15:32,080 --> 00:15:34,320
Speaker 8: fight to bring inflation back to the two percent target.

287
00:15:35,120 --> 00:15:38,240
Speaker 3: The policy has been quite difficult for the labor market

288
00:15:38,280 --> 00:15:41,240
Speaker 3: in the UK. What's your analysis about why that is?

289
00:15:41,920 --> 00:15:44,280
Speaker 8: Well, it's it's all pointing to one thing. It's the

290
00:15:44,800 --> 00:15:49,600
Speaker 8: the payroll tax rises. Chancellor Rachel Reeves' is twenty six

291
00:15:49,640 --> 00:15:52,080
Speaker 8: billion payroll tax rises and you know those came on

292
00:15:52,160 --> 00:15:57,120
Speaker 8: top of large consecutive increases in the minimum wage. And

293
00:15:57,240 --> 00:15:59,360
Speaker 8: you know the country has lost almost a quarter of

294
00:15:59,720 --> 00:16:03,920
Speaker 8: a min jobs after these payroll costs were increased in

295
00:16:03,960 --> 00:16:08,560
Speaker 8: Reeves's first budget in October twenty twenty four. And since then,

296
00:16:08,640 --> 00:16:11,400
Speaker 8: you know, employers have blamed them for job cuts and

297
00:16:11,480 --> 00:16:14,840
Speaker 8: hiring freezes and key sectors like retail and manufacturing.

298
00:16:15,600 --> 00:16:17,840
Speaker 3: There's been a lot of talk about the number of

299
00:16:17,920 --> 00:16:21,160
Speaker 3: young people who are not in work or employment or

300
00:16:21,240 --> 00:16:23,680
Speaker 3: training of any kind. That's got quite a lot of attentionion,

301
00:16:24,360 --> 00:16:29,040
Speaker 3: But how isolated is the issue with jobs when you

302
00:16:29,200 --> 00:16:32,720
Speaker 3: segment things by age or gender or skill set.

303
00:16:33,800 --> 00:16:36,320
Speaker 8: Well, most of this increase in unemployment that I was

304
00:16:36,360 --> 00:16:38,840
Speaker 8: just talking about has been due to a lack of

305
00:16:38,960 --> 00:16:42,280
Speaker 8: hiring so far, rather than mass layoffs. So of course

306
00:16:42,320 --> 00:16:44,960
Speaker 8: you know this impacts young pickper looking for their first job,

307
00:16:45,080 --> 00:16:47,000
Speaker 8: or just other people you know, moving out of economic

308
00:16:47,040 --> 00:16:52,000
Speaker 8: and activities trade into unemployment. And it's actually very interesting

309
00:16:52,040 --> 00:16:55,000
Speaker 8: that because men are becoming unemployed at a faster rate

310
00:16:55,080 --> 00:16:57,760
Speaker 8: than women, and you know, of course in particular young

311
00:16:57,800 --> 00:17:00,440
Speaker 8: men that's a big problem, but men in general. And

312
00:17:00,480 --> 00:17:04,800
Speaker 8: it seems like that hiring freezes and layoffs felt particularly

313
00:17:04,840 --> 00:17:08,480
Speaker 8: hard in male dominated sectors, so you know, construction, manufacturing,

314
00:17:08,520 --> 00:17:13,439
Speaker 8: but also it And this is all kind of helping

315
00:17:13,560 --> 00:17:17,680
Speaker 8: Reform because while Reform did not stand out among unemployed

316
00:17:17,720 --> 00:17:20,560
Speaker 8: voters at the general election, it has become the dominant

317
00:17:20,560 --> 00:17:23,600
Speaker 8: party for this group over the past six months, and

318
00:17:23,920 --> 00:17:27,080
Speaker 8: it's particularly unemployed in men who turned to reform. We

319
00:17:27,160 --> 00:17:29,840
Speaker 8: have data from More in Common that showed that more

320
00:17:29,840 --> 00:17:32,040
Speaker 8: than forty percent of men who are out of work

321
00:17:32,080 --> 00:17:35,359
Speaker 8: support reform, and that's double the level in July twenty

322
00:17:35,440 --> 00:17:38,080
Speaker 8: twenty four and ten points more than women.

323
00:17:38,440 --> 00:17:42,200
Speaker 3: Gosh, that's interesting, isn't it. So the political ramifications then

324
00:17:42,240 --> 00:17:47,080
Speaker 3: from the data I want to layer into that outlook

325
00:17:47,320 --> 00:17:51,520
Speaker 3: what AI might mean, because I know that the technology sectually.

326
00:17:51,520 --> 00:17:55,080
Speaker 3: Liz Kendall was speaking at Bluemberg's headquarters right here in London,

327
00:17:55,359 --> 00:17:57,560
Speaker 3: talking about how the government's going to use AI to

328
00:17:57,760 --> 00:18:02,359
Speaker 3: turbocharge different industry in Britain. And pledging this idea that

329
00:18:02,400 --> 00:18:07,280
Speaker 3: there will be AI training for all UK employees. PALMEI,

330
00:18:07,320 --> 00:18:10,159
Speaker 3: you've been covering AI companies and how their tools are

331
00:18:10,200 --> 00:18:13,359
Speaker 3: really starting to unsettle the world of business, the world

332
00:18:13,400 --> 00:18:16,920
Speaker 3: of work. What kinds of products I suppose, first of all,

333
00:18:16,960 --> 00:18:19,920
Speaker 3: are we actually starting to see being used and then

334
00:18:19,960 --> 00:18:21,399
Speaker 3: you know, maybe we'll think about what that means for

335
00:18:21,440 --> 00:18:22,359
Speaker 3: employment in a minute.

336
00:18:22,520 --> 00:18:25,200
Speaker 9: Well, most people are using chatbots already, right, I think

337
00:18:25,200 --> 00:18:27,520
Speaker 9: it's something like eight hundred million to nine hundred million

338
00:18:27,560 --> 00:18:29,960
Speaker 9: people use chat GPT on a weekly basis. That's something

339
00:18:30,000 --> 00:18:32,640
Speaker 9: like ten percent of the global population every week are

340
00:18:32,720 --> 00:18:36,480
Speaker 9: using these tools. But the most recent updates have been

341
00:18:36,680 --> 00:18:39,879
Speaker 9: agentic AI. Of course, you might have heard that term

342
00:18:40,040 --> 00:18:43,679
Speaker 9: agent a lot last year. It was very much hyped.

343
00:18:44,600 --> 00:18:47,760
Speaker 9: Unfortunately that didn't have much to show for it. Only

344
00:18:47,800 --> 00:18:50,160
Speaker 9: a few companies actually released anything. They were a little

345
00:18:50,200 --> 00:18:53,080
Speaker 9: bit unreliable. But actually just in the last few weeks

346
00:18:53,200 --> 00:18:56,360
Speaker 9: we've seen a couple of product launches of these AI agents.

347
00:18:56,400 --> 00:18:58,960
Speaker 9: And this is different to a chatbot. This is AI

348
00:18:59,119 --> 00:19:02,680
Speaker 9: that can not just give you information but carry out

349
00:19:02,760 --> 00:19:05,960
Speaker 9: tasks for you. So the one that the market really

350
00:19:06,000 --> 00:19:10,760
Speaker 9: got spooked by was a product called claud Cowork, which

351
00:19:10,800 --> 00:19:12,879
Speaker 9: came from a company called Anthropic. They were spun out

352
00:19:12,880 --> 00:19:16,040
Speaker 9: of open Ai a few years ago, and I've used

353
00:19:16,040 --> 00:19:19,159
Speaker 9: it myself. I pointed it at some files on my

354
00:19:19,200 --> 00:19:22,280
Speaker 9: computer and got it to create a PowerPoint presentation out

355
00:19:22,280 --> 00:19:24,600
Speaker 9: of it. Create a spreadsheet of all the people and

356
00:19:24,640 --> 00:19:27,560
Speaker 9: all my interviews with all their areas of expertise, you know,

357
00:19:27,600 --> 00:19:29,480
Speaker 9: stuff I'd been wanting to do for years but just

358
00:19:29,520 --> 00:19:31,639
Speaker 9: didn't have the time to do. It was even answering

359
00:19:31,640 --> 00:19:33,439
Speaker 9: my LinkedIn messages. I didn't even have to go to

360
00:19:33,480 --> 00:19:36,879
Speaker 9: LinkedIn and it would just answer them for me. So

361
00:19:37,160 --> 00:19:39,000
Speaker 9: those are just some examples of the kinds of things

362
00:19:39,160 --> 00:19:42,119
Speaker 9: they can do. And this is what I think is

363
00:19:42,200 --> 00:19:44,440
Speaker 9: kind of rattling the markets a little bit, is this

364
00:19:44,600 --> 00:19:49,359
Speaker 9: sense that, Okay, some of these tasks that certain jobs

365
00:19:49,400 --> 00:19:51,280
Speaker 9: are doing could well be under threat.

366
00:19:52,080 --> 00:19:54,960
Speaker 3: The thing is, trade is and investors of reacting pretty

367
00:19:55,000 --> 00:19:58,240
Speaker 3: strongly to the idea of these products, but they've not

368
00:19:58,560 --> 00:20:01,320
Speaker 3: been fully adopted. Yeah, as you say, lots of people

369
00:20:01,320 --> 00:20:04,280
Speaker 3: are testing them out, lots of businesses are trying them out,

370
00:20:04,760 --> 00:20:09,000
Speaker 3: and they haven't really claim market share yet. But I

371
00:20:09,000 --> 00:20:12,000
Speaker 3: suppose people are wired about whether that's coming or why

372
00:20:12,040 --> 00:20:12,439
Speaker 3: that is.

373
00:20:12,560 --> 00:20:14,080
Speaker 10: I think so, I think, I think you're right.

374
00:20:14,119 --> 00:20:16,600
Speaker 9: I think people just kind of want to get ahead

375
00:20:16,600 --> 00:20:20,520
Speaker 9: of whatever disruption is coming and ride that wave. But

376
00:20:20,600 --> 00:20:22,960
Speaker 9: this is so typical of the market, right, Like just

377
00:20:23,040 --> 00:20:25,440
Speaker 9: a few months ago, everybody was freaking out that we're

378
00:20:25,440 --> 00:20:28,560
Speaker 9: in an AI bubble, and now the sentiment, the narrative

379
00:20:28,560 --> 00:20:31,440
Speaker 9: has totally shifted to we're practically in the AI singularity.

380
00:20:31,520 --> 00:20:33,600
Speaker 9: You know, it's like, maybe not to that extent, but

381
00:20:34,400 --> 00:20:37,240
Speaker 9: it is funny how the pendulum has swung so far

382
00:20:37,359 --> 00:20:41,000
Speaker 9: the other way. And if you remember, in January last year,

383
00:20:41,320 --> 00:20:43,840
Speaker 9: there was a huge drop in the share price of

384
00:20:43,840 --> 00:20:47,320
Speaker 9: big tech companies when China's deep Seat came out because

385
00:20:47,359 --> 00:20:49,480
Speaker 9: there was a belief that that was going to threaten

386
00:20:49,560 --> 00:20:52,200
Speaker 9: the status quo of all the infrastructure and data centers

387
00:20:52,200 --> 00:20:54,640
Speaker 9: that was being spent by big tech. Now, of course

388
00:20:54,680 --> 00:20:56,920
Speaker 9: that was an overreaction. I think we're seeing the same

389
00:20:57,000 --> 00:20:59,400
Speaker 9: thing here, a little bit of an overreaction, but there's

390
00:20:59,440 --> 00:21:02,280
Speaker 9: truth to it. But when people are selling off stocks

391
00:21:02,320 --> 00:21:04,960
Speaker 9: like Salesforce or some of these other enterprise software makers,

392
00:21:06,040 --> 00:21:09,520
Speaker 9: there is some truth that the application layer that those

393
00:21:09,560 --> 00:21:13,640
Speaker 9: software makers have, that bit of their business is under

394
00:21:13,680 --> 00:21:16,679
Speaker 9: threat I think from these new AI agents that are

395
00:21:16,680 --> 00:21:17,320
Speaker 9: coming to market.

396
00:21:17,560 --> 00:21:20,520
Speaker 3: Okay, so let's bring that together then with the idea

397
00:21:20,520 --> 00:21:23,760
Speaker 3: of jobs here in the UK. How far away is

398
00:21:23,800 --> 00:21:28,560
Speaker 3: the future where artificial intelligence does actually make workers redundant,

399
00:21:28,560 --> 00:21:31,840
Speaker 3: because we're starting to see bits of reporting around that

400
00:21:32,119 --> 00:21:34,080
Speaker 3: and bits of data in Britain.

401
00:21:34,359 --> 00:21:37,800
Speaker 9: Well, the obvious casualty for now, maybe it's not quite

402
00:21:37,880 --> 00:21:41,560
Speaker 9: showing up in the data yet, is the graduates, entry

403
00:21:41,640 --> 00:21:44,639
Speaker 9: level workers whose companies are told treat your AI like

404
00:21:44,680 --> 00:21:47,520
Speaker 9: an intern, so they do and that works really well,

405
00:21:47,560 --> 00:21:49,520
Speaker 9: and then they don't need to hire interns or junior

406
00:21:49,520 --> 00:21:53,000
Speaker 9: analysts or junior researchers. And I think that might just

407
00:21:53,040 --> 00:21:55,800
Speaker 9: be the starting point, but I think it's very I

408
00:21:55,800 --> 00:21:57,399
Speaker 9: don't think it's going to be as simple as just

409
00:21:57,560 --> 00:22:00,800
Speaker 9: jobs get replaced. I think jobs are going to change. So,

410
00:22:01,000 --> 00:22:04,480
Speaker 9: for example, I was talking to the head of Zapier,

411
00:22:04,480 --> 00:22:07,199
Speaker 9: which is a big software company in the US, and

412
00:22:07,240 --> 00:22:10,480
Speaker 9: he was saying that the way they build product now,

413
00:22:10,520 --> 00:22:12,679
Speaker 9: they used to have three people who would be on

414
00:22:12,720 --> 00:22:15,639
Speaker 9: a team and it's a very classic structure called EDP

415
00:22:16,600 --> 00:22:19,600
Speaker 9: or EDMS as the engineer, the product marketer, and then

416
00:22:19,600 --> 00:22:22,720
Speaker 9: the designer. Now instead of three people, they just have one,

417
00:22:23,040 --> 00:22:25,480
Speaker 9: but that one person has to cover all those three

418
00:22:25,560 --> 00:22:28,760
Speaker 9: different areas, so the titles have been squished together into

419
00:22:28,760 --> 00:22:31,800
Speaker 9: one person who's using AI to kind of augment themselves.

420
00:22:32,119 --> 00:22:34,280
Speaker 9: It doesn't mean the other two people have been fired.

421
00:22:35,160 --> 00:22:37,760
Speaker 9: They're just doing different things. So I think we're going

422
00:22:37,800 --> 00:22:41,000
Speaker 9: to see a mixture of that of roles just changing

423
00:22:41,119 --> 00:22:46,320
Speaker 9: and morphing and blending together, but perhaps a certainly elements

424
00:22:46,320 --> 00:22:48,760
Speaker 9: of hiring freezes. I mean, there are some people who've

425
00:22:48,760 --> 00:22:53,000
Speaker 9: been using this new clawed plug in for legal work,

426
00:22:53,520 --> 00:22:56,280
Speaker 9: and one person told me that they weren't using their

427
00:22:56,280 --> 00:22:59,320
Speaker 9: fractional lawyer anymore. For anything up to a commercial contract

428
00:22:59,400 --> 00:23:02,439
Speaker 9: worth fifty you know, anything higher than that, you do

429
00:23:02,520 --> 00:23:04,360
Speaker 9: need a human. But if it's kind of low stakes,

430
00:23:04,400 --> 00:23:07,239
Speaker 9: they were using the AI now, so of course that

431
00:23:07,480 --> 00:23:10,399
Speaker 9: is job, a job not going to a human. So

432
00:23:10,440 --> 00:23:12,520
Speaker 9: we're seeing I think a kind of mixture of those

433
00:23:12,560 --> 00:23:13,199
Speaker 9: things happening.

434
00:23:13,480 --> 00:23:16,520
Speaker 3: Yeah, anecdotally, I've certainly seen it with people I speak

435
00:23:16,560 --> 00:23:19,919
Speaker 3: to that that they are feeling that change. And I

436
00:23:19,960 --> 00:23:23,080
Speaker 3: will point to one bit of data. Morgan Stanley in

437
00:23:23,119 --> 00:23:25,399
Speaker 3: the last few weeks has talked about AI leading to

438
00:23:25,440 --> 00:23:28,359
Speaker 3: an eight percent net job loss over the last twelve

439
00:23:28,359 --> 00:23:31,280
Speaker 3: months in the UK. So there's some tiny bits of

440
00:23:31,760 --> 00:23:36,119
Speaker 3: research out there, arena, are we seeing any size that

441
00:23:36,160 --> 00:23:39,399
Speaker 3: AI is starting to affect the UK labor market? Is

442
00:23:39,440 --> 00:23:44,040
Speaker 3: it's you know, people recently graduating what sorts of jobs

443
00:23:44,119 --> 00:23:44,960
Speaker 3: might be affected.

444
00:23:45,000 --> 00:23:48,560
Speaker 8: First, I think the problem is not necessarily job cuts,

445
00:23:48,600 --> 00:23:51,560
Speaker 8: but the lack of job creation in the UK. So

446
00:23:51,720 --> 00:23:53,960
Speaker 8: you know that Morgan Standy research. You know, it's showing

447
00:23:54,000 --> 00:23:56,800
Speaker 8: the UK is losing more jobs than it's creating because

448
00:23:56,800 --> 00:23:58,959
Speaker 8: of AI, and it's doing sort of faster race than

449
00:23:59,600 --> 00:24:02,240
Speaker 8: you know, tries like the US or Japan or Germany.

450
00:24:02,560 --> 00:24:05,040
Speaker 8: But if you actually look at the data, the UK

451
00:24:05,200 --> 00:24:07,240
Speaker 8: is sort of losing jobs at the same pace as

452
00:24:07,240 --> 00:24:09,120
Speaker 8: the other countries. So it's kind of like losing jobs

453
00:24:09,119 --> 00:24:11,920
Speaker 8: at the same rate as Germany. It's just creating way

454
00:24:11,960 --> 00:24:15,280
Speaker 8: fewer jobs thanks to AI. And some of that is

455
00:24:15,320 --> 00:24:18,720
Speaker 8: also due to higher employment costs here that you know

456
00:24:18,760 --> 00:24:22,600
Speaker 8: are not really like, it's not really AI is almost

457
00:24:22,760 --> 00:24:25,080
Speaker 8: coming in as a solution for companies to deal with

458
00:24:25,160 --> 00:24:28,119
Speaker 8: this increase in in in the cost of employing a

459
00:24:28,200 --> 00:24:32,199
Speaker 8: human and you know, to be to be sure, like

460
00:24:32,560 --> 00:24:35,280
Speaker 8: there's also some productivity gains that are coming as a

461
00:24:35,320 --> 00:24:39,080
Speaker 8: result of adopting AI, and there are you know, this

462
00:24:39,119 --> 00:24:41,240
Speaker 8: is you know, one for the AI optimists like the

463
00:24:41,440 --> 00:24:43,000
Speaker 8: Bank of England Governor Andrew Bailey.

464
00:24:43,040 --> 00:24:44,760
Speaker 10: The fact that you know, these companies.

465
00:24:44,359 --> 00:24:48,680
Speaker 8: Are actually changing how they do things after adopting AI.

466
00:24:48,840 --> 00:24:50,440
Speaker 10: And you know, maybe the UK.

467
00:24:50,520 --> 00:24:55,000
Speaker 8: Is is about to see a productivity like find to

468
00:24:55,000 --> 00:24:56,760
Speaker 8: finally escape it's productivity trapped.

469
00:24:56,760 --> 00:24:59,560
Speaker 10: But there the data does point.

470
00:24:59,320 --> 00:25:01,280
Speaker 8: To the fact that there are some job losses to

471
00:25:01,320 --> 00:25:03,080
Speaker 8: come and the cost of this may be a bit

472
00:25:03,119 --> 00:25:06,000
Speaker 8: too high or weren't already to deal with it yet.

473
00:25:06,560 --> 00:25:09,600
Speaker 3: My thanks to our UK economy reporter Arena Angel and

474
00:25:09,600 --> 00:25:13,720
Speaker 3: to our Bloomberg opinion columnists covering technology Pamey Olson. Thank

475
00:25:13,760 --> 00:25:16,600
Speaker 3: you so much, and we'll have full coverage and analysis

476
00:25:16,640 --> 00:25:19,919
Speaker 3: of the UK's jobs data. I'm Caline Hepga Here in London.

477
00:25:20,080 --> 00:25:23,040
Speaker 3: You can catch us every weekday morning for Bloomberg Daybreak Europe,

478
00:25:23,160 --> 00:25:25,800
Speaker 3: beginning at six am in London. That's one am on

479
00:25:25,960 --> 00:25:26,480
Speaker 3: Wall Street.

480
00:25:26,640 --> 00:25:30,639
Speaker 2: Nathan, Thanks Caroline, and coming up on Bloomberg day Break weekend,

481
00:25:30,680 --> 00:25:34,159
Speaker 2: we'll look ahead to lunar New Year festivities in China.

482
00:25:34,680 --> 00:25:49,560
Speaker 2: I'm Nathan Hagar and this is Bloomberg. This is Bloomberg

483
00:25:49,600 --> 00:25:52,160
Speaker 2: day Break weekend, our global look ahead at the top

484
00:25:52,200 --> 00:25:55,040
Speaker 2: stories for investors in the coming week. I'm Nathan Hager

485
00:25:55,160 --> 00:25:58,399
Speaker 2: in Washington. We go to China next, where Lunar New

486
00:25:58,480 --> 00:26:01,520
Speaker 2: Year festivities are set to take off. The nine day

487
00:26:01,560 --> 00:26:04,680
Speaker 2: holiday will drive spending on travel, dining, and gift giving.

488
00:26:04,920 --> 00:26:07,080
Speaker 2: For a look ahead, let's get to Doug Krisner, host

489
00:26:07,080 --> 00:26:09,199
Speaker 2: of the Bloomberg Daybreak Asia podcast.

490
00:26:09,720 --> 00:26:13,439
Speaker 4: Nathan. The Lunar New Year Holiday or Spring Festival, is

491
00:26:13,480 --> 00:26:16,800
Speaker 4: one of China's longest holidays, and this year it will

492
00:26:16,880 --> 00:26:20,440
Speaker 4: usher in the Year of the Horse. Festivities will run

493
00:26:20,480 --> 00:26:23,840
Speaker 4: for nine days from February fifteenth. That's a day longer

494
00:26:23,880 --> 00:26:27,600
Speaker 4: than usual, and as usual, the focus for markets will

495
00:26:27,640 --> 00:26:31,040
Speaker 4: be on consumer spending. Now we know the Chinese economy

496
00:26:31,080 --> 00:26:35,199
Speaker 4: continues to struggle, largely due to weak domestic demand. For

497
00:26:35,240 --> 00:26:37,560
Speaker 4: a closer look at the holiday mood, let's bring in

498
00:26:37,560 --> 00:26:41,679
Speaker 4: Bloomberg's Shirley Joo. Shirley covers consumer companies in the region

499
00:26:41,720 --> 00:26:45,119
Speaker 4: with a close eye on luxury goods, and she joins

500
00:26:45,160 --> 00:26:48,080
Speaker 4: from our studios in Hong Kong. Thank you for being here.

501
00:26:48,280 --> 00:26:50,480
Speaker 4: First of all, Shirley, I want to know about the

502
00:26:50,600 --> 00:26:53,119
Speaker 4: level of confidence among consumers.

503
00:26:54,280 --> 00:27:00,800
Speaker 11: I think people are relatively optimistic because although China is

504
00:27:00,840 --> 00:27:05,919
Speaker 11: in an economic slowdown and people's spending power has not

505
00:27:06,000 --> 00:27:10,320
Speaker 11: been as strong as before, and people spending appetite has

506
00:27:10,359 --> 00:27:14,440
Speaker 11: been weakening, but Lunar New Year is one of China's

507
00:27:14,440 --> 00:27:19,240
Speaker 11: biggest holidays, and people tend to stay in the country

508
00:27:19,520 --> 00:27:24,040
Speaker 11: instead of traveling outside because the holiday is all about,

509
00:27:24,080 --> 00:27:27,560
Speaker 11: you know, spending time with your family. So it's like

510
00:27:27,800 --> 00:27:33,800
Speaker 11: Christmas in the US or in Europe. It's a big holiday,

511
00:27:34,119 --> 00:27:37,760
Speaker 11: and people tend to want to spend on food and drinks,

512
00:27:38,200 --> 00:27:43,040
Speaker 11: on you know, big meals outside. So people in the

513
00:27:43,040 --> 00:27:48,280
Speaker 11: food and drinks industry at least are relatively positive about

514
00:27:48,359 --> 00:27:53,320
Speaker 11: the outlook of Lunar New Year. But how much it

515
00:27:53,359 --> 00:27:56,440
Speaker 11: may grow from last year, or whether it will grow

516
00:27:56,480 --> 00:27:59,720
Speaker 11: at all, it remains to be seen, because, as I

517
00:27:59,760 --> 00:28:05,560
Speaker 11: said just now, people's spending appetite still remains relatively weak

518
00:28:05,720 --> 00:28:07,639
Speaker 11: in the broader economic slowdown.

519
00:28:07,840 --> 00:28:10,159
Speaker 4: So if a consumer, let's say, were to make the

520
00:28:10,280 --> 00:28:16,320
Speaker 4: choice to travel abroad or offshore somewhere, what destinations have

521
00:28:16,440 --> 00:28:19,720
Speaker 4: become popular. I'm thinking Korea, Japan is that likely. Maybe

522
00:28:19,720 --> 00:28:21,040
Speaker 4: even a place like Vietnam.

523
00:28:21,880 --> 00:28:25,680
Speaker 11: Yes, for people in mainland China, Korea has become one

524
00:28:25,680 --> 00:28:30,520
Speaker 11: of the hottest destinations for people to travel outside, maybe

525
00:28:30,880 --> 00:28:33,119
Speaker 11: in the latter part of the holiday, because at the

526
00:28:33,119 --> 00:28:36,560
Speaker 11: beginning of the holiday, everybody will stay home and stay

527
00:28:36,720 --> 00:28:39,640
Speaker 11: spend time with family, and then they will visit their

528
00:28:39,680 --> 00:28:42,440
Speaker 11: neighbors and relatives. So the first few days people tend

529
00:28:42,520 --> 00:28:47,080
Speaker 11: to stay within the country, but in the second half

530
00:28:47,120 --> 00:28:51,680
Speaker 11: of the holiday, some people may choose to travel outside.

531
00:28:51,760 --> 00:28:55,320
Speaker 11: And Korea has become a really hot destination, and Japan

532
00:28:55,520 --> 00:28:58,960
Speaker 11: used to be a hot destination as well, and especially

533
00:28:59,000 --> 00:29:05,360
Speaker 11: when yen is so keeap. Now people should have, you know,

534
00:29:06,520 --> 00:29:11,600
Speaker 11: chosen Japan. But unfortunately, since China and Japan got into

535
00:29:11,640 --> 00:29:16,040
Speaker 11: this big dispute over Taiwan late last year, China has

536
00:29:17,080 --> 00:29:20,440
Speaker 11: instructed airlines to cut their flights or even hold their

537
00:29:20,440 --> 00:29:23,320
Speaker 11: flights for a prolonged period of time.

538
00:29:23,680 --> 00:29:25,560
Speaker 10: So flights were.

539
00:29:25,440 --> 00:29:28,800
Speaker 11: Really limited in mainland China for people who want to

540
00:29:29,000 --> 00:29:33,520
Speaker 11: go to Japan. And you know, under this rising nationalism

541
00:29:33,880 --> 00:29:37,959
Speaker 11: and domestic pressure, a lot of people would choose to

542
00:29:38,040 --> 00:29:41,960
Speaker 11: go to other places than Japan, So we will say

543
00:29:42,040 --> 00:29:49,120
Speaker 11: Korea and definitely Southeast Asia, places like Thailand and Vietnam

544
00:29:49,320 --> 00:29:54,200
Speaker 11: would be preferred destinations for mainland Chinese travelers. For travelers

545
00:29:54,240 --> 00:29:58,960
Speaker 11: from Hong Kong, Japan remains a big destination, and other

546
00:29:59,040 --> 00:30:02,120
Speaker 11: places like Taiwan, in Korea and Southeast Asia.

547
00:30:02,200 --> 00:30:05,360
Speaker 4: In addition to eating lots of good food, gift giving

548
00:30:05,600 --> 00:30:08,600
Speaker 4: is a major part of the festivities, and red envelopes

549
00:30:08,640 --> 00:30:11,800
Speaker 4: in particular. Talk to me a little bit about the

550
00:30:11,840 --> 00:30:15,920
Speaker 4: red envelope and how some e commerce companies are trying

551
00:30:16,000 --> 00:30:20,400
Speaker 4: to convert that type of gift giving into online commerce.

552
00:30:21,360 --> 00:30:27,280
Speaker 11: Right. So it's interesting because Bloomberg Hong Kong actually so

553
00:30:27,360 --> 00:30:31,040
Speaker 11: we have a weekly newsletter and this week's newsletter is

554
00:30:31,120 --> 00:30:36,280
Speaker 11: actually a review of red envelopes by different brands and

555
00:30:36,520 --> 00:30:41,480
Speaker 11: financial institutions. So, for example, Hong Kong's flag carrier, Cathay

556
00:30:41,600 --> 00:30:49,760
Speaker 11: Pacific has issued a really fantastic set of red envelopes

557
00:30:49,880 --> 00:30:56,320
Speaker 11: featuring the company's history and their milestone plane models over

558
00:30:56,400 --> 00:31:01,240
Speaker 11: the eighty years of its history. So envelope is definitely

559
00:31:01,280 --> 00:31:07,400
Speaker 11: a huge tradition. And if you have children, or if

560
00:31:07,480 --> 00:31:11,280
Speaker 11: you will go to meet your friend's children, then you're

561
00:31:11,320 --> 00:31:14,880
Speaker 11: supposed to give red envelopes to well with money in

562
00:31:14,920 --> 00:31:20,040
Speaker 11: it to them because they are junior to you, but

563
00:31:20,120 --> 00:31:23,200
Speaker 11: your parents or people who are senior to you will

564
00:31:23,200 --> 00:31:27,120
Speaker 11: give you red envelopes with money. So that's been a

565
00:31:27,200 --> 00:31:31,320
Speaker 11: huge tradition in China and Hong Kong. But over the

566
00:31:31,360 --> 00:31:34,440
Speaker 11: past few years, you know, e commerce has developed so

567
00:31:34,640 --> 00:31:40,720
Speaker 11: fast in China, it's you know, so ubiqulous everywhere and everybody.

568
00:31:42,120 --> 00:31:44,200
Speaker 11: It's got to a point that if you go to

569
00:31:44,280 --> 00:31:47,400
Speaker 11: China today, if you want to use cash, it's very

570
00:31:47,440 --> 00:31:52,840
Speaker 11: difficult because very few places accept cash anymore or they

571
00:31:52,840 --> 00:31:57,120
Speaker 11: don't have changes for you. So everyone is paying online

572
00:31:57,240 --> 00:32:03,280
Speaker 11: using e commerce platforms. And in fact, my parents and

573
00:32:03,400 --> 00:32:11,360
Speaker 11: my relatives are giving me money via online envelopes, so

574
00:32:11,400 --> 00:32:14,280
Speaker 11: we can see, you know, there's a huge shift of

575
00:32:14,400 --> 00:32:19,560
Speaker 11: people know of this money gifting from offline to online.

576
00:32:19,720 --> 00:32:22,560
Speaker 4: I know you focus a lot on luxury goods, and

577
00:32:22,600 --> 00:32:26,120
Speaker 4: I'm wondering about the outlook for luxury sales given the

578
00:32:26,120 --> 00:32:28,840
Speaker 4: state of the economy and how consumers are feeling about

579
00:32:28,840 --> 00:32:32,560
Speaker 4: their finances. Is there, in your view a risk that's

580
00:32:32,560 --> 00:32:37,760
Speaker 4: spending on luxury items, particularly on those well known fashioned brands,

581
00:32:38,280 --> 00:32:39,840
Speaker 4: is a little on the soft side.

582
00:32:40,320 --> 00:32:44,200
Speaker 11: Yes, Over the past two years in China, the trend

583
00:32:44,320 --> 00:32:48,080
Speaker 11: is definitely that people are becoming more cautious and selective

584
00:32:48,200 --> 00:32:53,240
Speaker 11: when it comes to buying big ticket items, including like jewelry, watches,

585
00:32:53,640 --> 00:32:58,000
Speaker 11: and leather goods, you know, all those luxury brand items.

586
00:32:59,160 --> 00:33:02,400
Speaker 11: The trend in China is that people are now becoming

587
00:33:02,640 --> 00:33:06,560
Speaker 11: more aware of their own needs and their own lifestyle,

588
00:33:07,560 --> 00:33:11,960
Speaker 11: and they don't have much money or they don't feel

589
00:33:12,320 --> 00:33:15,200
Speaker 11: rich enough for them to buy a huge amount of

590
00:33:15,920 --> 00:33:20,400
Speaker 11: luxury stuff, so they're becoming more selective. They are not

591
00:33:20,480 --> 00:33:23,560
Speaker 11: only looking at brand names, they're also looking at whether

592
00:33:23,680 --> 00:33:28,800
Speaker 11: they identify with the brand stories, the brand philosophy, and

593
00:33:28,920 --> 00:33:33,240
Speaker 11: whether these brands can elevate their lifestyle, it can make

594
00:33:33,320 --> 00:33:36,480
Speaker 11: them feel better. So in the past, you could see

595
00:33:36,520 --> 00:33:40,120
Speaker 11: that people would just go to any luxury brand stores

596
00:33:40,440 --> 00:33:43,520
Speaker 11: because of the brand names. People thought that, you know,

597
00:33:44,040 --> 00:33:47,560
Speaker 11: if they bought luxury goods, it could elevate their status.

598
00:33:47,760 --> 00:33:52,200
Speaker 11: But now people are really choosing very carefully, so luxury

599
00:33:52,320 --> 00:33:59,200
Speaker 11: gift gifting could still become a bit subdued in China.

600
00:33:59,680 --> 00:34:04,440
Speaker 11: But this year, you know, everybody's going after gold like crazy,

601
00:34:04,680 --> 00:34:07,239
Speaker 11: so I won't be surprised to see that. You know,

602
00:34:07,320 --> 00:34:11,120
Speaker 11: gold gifting could become a big trend in China during

603
00:34:11,160 --> 00:34:13,720
Speaker 11: the Chinese New Year, because you know, the gold prices

604
00:34:13,760 --> 00:34:16,200
Speaker 11: have been going up and up and up right, and

605
00:34:16,239 --> 00:34:20,719
Speaker 11: in China, you know, everybody goes into this investment if

606
00:34:20,719 --> 00:34:24,200
Speaker 11: the prices keep going up, and you know, everybody pulled

607
00:34:24,239 --> 00:34:28,359
Speaker 11: out if the prices come down. So yeah, people are

608
00:34:28,440 --> 00:34:32,279
Speaker 11: there's a huge frenzy over gold in China right now.

609
00:34:32,320 --> 00:34:35,000
Speaker 4: We talk about the many ways the Chinese government has

610
00:34:35,040 --> 00:34:39,239
Speaker 4: tried to tackle the problem of weak domestic demand, and

611
00:34:39,320 --> 00:34:42,719
Speaker 4: since holiday spending has the potential to provide a bit

612
00:34:42,760 --> 00:34:46,280
Speaker 4: of a lift to the overall economy, I'm wondering about

613
00:34:46,280 --> 00:34:49,600
Speaker 4: what the government is doing to encourage consumers to spend

614
00:34:49,680 --> 00:34:51,160
Speaker 4: more than they would otherwise.

615
00:34:52,320 --> 00:34:56,440
Speaker 11: Yes, so the Chinese government has actually focused more on

616
00:34:56,520 --> 00:35:02,360
Speaker 11: consumption than before. So previously is focus was on you know,

617
00:35:02,440 --> 00:35:07,160
Speaker 11: heavy industries and new industries for example, like ev and

618
00:35:07,280 --> 00:35:12,440
Speaker 11: new energy sectors. But it has come to realization that

619
00:35:12,600 --> 00:35:18,200
Speaker 11: consumption is a big part of economic driver. So it

620
00:35:18,400 --> 00:35:24,919
Speaker 11: has been issuing, for example, consumption vouchers and has been

621
00:35:25,320 --> 00:35:31,399
Speaker 11: implementing policies to encourage people to buy things. So that's

622
00:35:31,480 --> 00:35:35,840
Speaker 11: a good shift and it's a you know, we have

623
00:35:35,960 --> 00:35:41,600
Speaker 11: seen the Chinese government doing more in encouraging people to spend.

624
00:35:41,719 --> 00:35:45,520
Speaker 4: In China, I've learned that much of the gift giving

625
00:35:45,719 --> 00:35:48,759
Speaker 4: during the Lunar New Year holiday has been described as

626
00:35:49,200 --> 00:35:54,440
Speaker 4: emotional consumption. We've also seen a tendency to favor experiences

627
00:35:54,560 --> 00:35:57,120
Speaker 4: rather than goods. Surely, I'm going to go out on

628
00:35:57,160 --> 00:35:59,319
Speaker 4: a limb here, so work with me, and I'm going

629
00:35:59,400 --> 00:36:03,319
Speaker 4: to ask whether their gifting stock is something that consumers

630
00:36:03,360 --> 00:36:04,400
Speaker 4: would ever consider.

631
00:36:05,360 --> 00:36:10,200
Speaker 11: Actually, that's a really interesting thought, and I definitely wouldn't

632
00:36:10,200 --> 00:36:15,880
Speaker 11: mind if people give me, you know, stocks in major

633
00:36:15,960 --> 00:36:19,279
Speaker 11: Hong Kong or mainland companies. But this is not a

634
00:36:19,320 --> 00:36:23,279
Speaker 11: trend that I have observed. In fact, in China, I

635
00:36:23,440 --> 00:36:27,760
Speaker 11: still think that the majority of people don't think stock

636
00:36:27,840 --> 00:36:31,919
Speaker 11: market being a safe way to put their money in

637
00:36:33,200 --> 00:36:38,640
Speaker 11: a lot of Chinese people still think that property is

638
00:36:38,680 --> 00:36:43,239
Speaker 11: their only way of investment because it's safe and the

639
00:36:43,320 --> 00:36:46,160
Speaker 11: prices would be bound to go up. And of course,

640
00:36:46,200 --> 00:36:48,680
Speaker 11: you know, that was up until a few years ago

641
00:36:49,440 --> 00:36:53,040
Speaker 11: when China's property markets started to crash. So a lot

642
00:36:53,080 --> 00:36:57,560
Speaker 11: of Chinese people's wealth because everybody invested in property before

643
00:36:57,600 --> 00:37:01,680
Speaker 11: the property market slowed down, so huge amount of Chinese

644
00:37:01,719 --> 00:37:05,760
Speaker 11: people's wealth was locked up in the property market. That's

645
00:37:05,840 --> 00:37:09,799
Speaker 11: why people are spending less now because their wealth is

646
00:37:09,880 --> 00:37:14,040
Speaker 11: locked up, and even though their income remains unchanged, they

647
00:37:14,080 --> 00:37:17,600
Speaker 11: still feel that they're not rich. They still feel poor.

648
00:37:17,920 --> 00:37:21,600
Speaker 11: So that's why people are not spending. Of course, you know,

649
00:37:21,640 --> 00:37:25,640
Speaker 11: I won't be surprised if China's stock market and China's

650
00:37:25,719 --> 00:37:32,720
Speaker 11: financial market become better regulated, and if China gives more

651
00:37:34,000 --> 00:37:40,680
Speaker 11: flexibility for people to invest in different financial tools. Stock

652
00:37:40,760 --> 00:37:45,200
Speaker 11: market could become a big investment for Chinese people, and

653
00:37:45,440 --> 00:37:48,759
Speaker 11: stop giving could become a trend. But at least for now,

654
00:37:48,800 --> 00:37:52,680
Speaker 11: I haven't observed this as a big trend right now.

655
00:37:53,040 --> 00:37:55,360
Speaker 4: Just a thought. Shirley, thank you so very much, and

656
00:37:55,400 --> 00:37:58,280
Speaker 4: happy New Year. By the way, Bloomberg Shirly Joao joining

657
00:37:58,280 --> 00:38:00,680
Speaker 4: from Hong Kong. I'm Doug Kristner. You can catch us

658
00:38:00,680 --> 00:38:04,600
Speaker 4: weekdays for the Daybreak Asia podcast. It's available wherever you

659
00:38:04,640 --> 00:38:06,360
Speaker 4: get your podcast. Nathan.

660
00:38:06,840 --> 00:38:09,239
Speaker 2: Thanks Doug, and that does it for this edition of

661
00:38:09,280 --> 00:38:12,919
Speaker 2: Bloomberg Daybreak Weekend. Join us again Tuesday morning at five

662
00:38:12,960 --> 00:38:15,799
Speaker 2: am Wall Street Time for the latest on markets overseas

663
00:38:15,880 --> 00:38:18,279
Speaker 2: and the news you need to start your day. I'm

664
00:38:18,360 --> 00:38:21,520
Speaker 2: Nathan Hager. Stay with us. Top stories and global business

665
00:38:21,520 --> 00:38:23,720
Speaker 2: headlines are coming up right now,