WEBVTT 1 00:00:00.440 --> 00:00:04.719 Zero zero five nine five one seven six nine zero 2 00:00:05.080 --> 00:00:09.679 zero zero five. A popular and local Medicare plan is improving. 3 00:00:09.880 --> 00:00:14.000 Others are raising copays and adding deductibles, biggest changes in 4 00:00:14.039 --> 00:00:18.679 the Medicare drug program in fifteen years. We thank George 5 00:00:18.719 --> 00:00:22.079 Letzfield and Let's Field Insurance for their generous support of 6 00:00:22.160 --> 00:00:23.120 this radio. 7 00:00:22.839 --> 00:00:29.320 Station, Lustina KCAA Lowlinda at one oh six point five 8 00:00:29.480 --> 00:00:31.879 FM K two ninety three c F Brino Valley. 9 00:00:32.600 --> 00:00:36.119 The information economy has a rod. The world is teeming 10 00:00:36.240 --> 00:00:39.320 with innovation as new business models reinvent. 11 00:00:39.079 --> 00:00:40.439 Every industry industry. 12 00:00:40.520 --> 00:00:44.880 Inside Analysis is your source of information and insight about 13 00:00:44.880 --> 00:00:47.439 how to make the most of this exciting new era. 14 00:00:47.679 --> 00:00:51.880 Learn more at inside Analysis dot insideanalysis dot com. And 15 00:00:52.000 --> 00:00:55.359 now here's your host, through Eric Kavanaugh. 16 00:00:57.880 --> 00:00:58.200 Field. 17 00:00:59.359 --> 00:01:01.560 All right, folks, hello to welcome back once again to 18 00:01:01.640 --> 00:01:04.000 the only coast to coast radio show all about the 19 00:01:04.040 --> 00:01:07.920 information economy. It's called Inside Analysis. You're truly Eric Kavanaugh 20 00:01:08.000 --> 00:01:11.519 here with a couple old friends and true visionaries in 21 00:01:11.560 --> 00:01:15.280 the fields of marketing and analyst relations and public relations 22 00:01:15.319 --> 00:01:18.840 and strategy. We've got a Misha Gandhi who got me 23 00:01:18.879 --> 00:01:21.680 into the whole influencer marketing thing years ago, about six 24 00:01:21.760 --> 00:01:24.079 years ago. I guess time flas and have fun and 25 00:01:24.200 --> 00:01:26.879 tom Ogen Taylor as well, and folks, we're going to 26 00:01:26.879 --> 00:01:30.159 talk about Ai jenai and how it is changing the 27 00:01:30.200 --> 00:01:34.359 game across the board. It's changing business, it's changing workflows, 28 00:01:34.680 --> 00:01:37.560 it's changing our priorities and what does it all mean. 29 00:01:37.840 --> 00:01:39.159 We're going to get to the bottom of it in 30 00:01:39.319 --> 00:01:42.040 this show, and I'll give you my thoughts to start 31 00:01:42.079 --> 00:01:46.079 us off here. Jenii in particular has opened up the portal. 32 00:01:46.359 --> 00:01:49.959 Everyone now understands. This stuff is powerful, it's real, it's amazing. 33 00:01:50.239 --> 00:01:53.920 It does have flaws. Jenai is probabilistic, so it's wrong 34 00:01:53.959 --> 00:01:56.000 about twenty percent of the time. If it does a 35 00:01:56.000 --> 00:01:57.799 good job, it's wrong with twenty percent of the time. 36 00:01:58.200 --> 00:01:59.879 So you have to use it at a certain con 37 00:02:00.120 --> 00:02:02.640 text and we'll talk about that. It's great for getting 38 00:02:02.680 --> 00:02:06.359 you eighty percent of the way there with copywriting for articles, 39 00:02:06.400 --> 00:02:09.240 for ads. It writes haiku for crying out loud, it 40 00:02:09.319 --> 00:02:11.599 writes all kinds of stuff, but you have to fine 41 00:02:11.639 --> 00:02:13.479 tune it. You have to pay attention and use it. 42 00:02:13.919 --> 00:02:17.680 And general Ai, not Jenai, but old Ai, let's call 43 00:02:17.680 --> 00:02:21.560 it is everywhere as well. That's building models, deep learning 44 00:02:21.680 --> 00:02:25.360 models that will optimize some part of your business. Think 45 00:02:25.439 --> 00:02:30.199 ab testing or think churn customer churn, watching out for that, 46 00:02:30.520 --> 00:02:32.439 lots of different models. They're going to be everywhere. They're 47 00:02:32.439 --> 00:02:36.039 already everywhere, but this really is a new era in business. 48 00:02:36.080 --> 00:02:38.000 And so on today's show, we're to talk about some 49 00:02:38.080 --> 00:02:41.000 ideas for how you can map out your plan and 50 00:02:41.039 --> 00:02:45.439 your strategy to leverage these technologies responsibly and change the game. 51 00:02:45.719 --> 00:02:47.680 And with that, Amisha Gandhi, I'll. 52 00:02:47.479 --> 00:02:47.960 Bring you in. 53 00:02:48.000 --> 00:02:49.479 You know, you were way ahead of the game with 54 00:02:49.719 --> 00:02:53.039 influencer marketing, as was Tom. And now you and I 55 00:02:53.080 --> 00:02:56.120 are talking about what's happening in the workplace and things 56 00:02:56.159 --> 00:02:59.319 are changing dramatically. There's a story, oh jobs are going 57 00:02:59.360 --> 00:03:02.199 to go away. I think jobs are going to change fundamentally, 58 00:03:02.599 --> 00:03:04.759 and so we have to change org charts, we have 59 00:03:04.840 --> 00:03:08.000 to change how we structure our organizations and how we 60 00:03:08.080 --> 00:03:10.199 divide up the work. And it's all still kind of 61 00:03:10.240 --> 00:03:11.800 in flux, right, yeah. 62 00:03:11.840 --> 00:03:13.919 I mean we're two years in, right, So everyone was 63 00:03:13.960 --> 00:03:16.560 freaking out first about Genai L's going to lose their job, 64 00:03:16.960 --> 00:03:19.280 and now the shift is really it's a tool, right, 65 00:03:19.319 --> 00:03:21.560 and things are happening with the announcements all the time 66 00:03:21.560 --> 00:03:26.719 of new tools making it and kind of democratic, democratizing 67 00:03:26.840 --> 00:03:30.439 content and other things. Right, But AI has always been around. 68 00:03:30.439 --> 00:03:32.919 Now there's Geni, it's jenai, and it's. 69 00:03:32.719 --> 00:03:34.240 Like really accelerating. 70 00:03:34.599 --> 00:03:37.199 So we're seeing a lot of new roles that have emerged, 71 00:03:37.280 --> 00:03:41.560 right that people are now becoming prompt engineers. Right, no 72 00:03:41.599 --> 00:03:44.560 one will ever have a first bad draft. There's a 73 00:03:44.560 --> 00:03:47.719 lot of things around governance and like the language model, 74 00:03:47.719 --> 00:03:50.199 where is it pulling the information from? So there's a 75 00:03:50.240 --> 00:03:52.719 lot to talk about, a lot to look out for, 76 00:03:53.120 --> 00:03:56.360 But you're really looking for people who have strategy around 77 00:03:56.360 --> 00:03:59.759 AI who can be prompt engineers. How you're bringing it 78 00:03:59.800 --> 00:04:02.199 into your you know, it's in your marketing stack already, 79 00:04:02.240 --> 00:04:04.599 Like you said, AI is already built in. How you're 80 00:04:04.599 --> 00:04:07.439 building jen ai in as part of your workflow, right, 81 00:04:07.680 --> 00:04:11.280 So not really replacing jobs, it's really allowing marketers to 82 00:04:11.319 --> 00:04:15.080 focus on strategy while AI handles some of the execution 83 00:04:15.319 --> 00:04:16.319 and data crunching. 84 00:04:16.439 --> 00:04:16.639 Right. 85 00:04:17.199 --> 00:04:20.160 And then you are also looking at teams you need 86 00:04:20.199 --> 00:04:23.639 to upscale and get people trained right to use them 87 00:04:23.680 --> 00:04:26.600 as tools rather than just hiring AI specialists. 88 00:04:26.639 --> 00:04:28.439 On going to be so many people, right, And then 89 00:04:28.480 --> 00:04:29.480 you have a junior team. 90 00:04:30.439 --> 00:04:32.399 You're going to people coming in that are alrea, you're 91 00:04:32.399 --> 00:04:33.959 going to be trained. You have you know, an older 92 00:04:33.959 --> 00:04:36.279 workforce that's training, so you have to really think about 93 00:04:36.319 --> 00:04:39.600 that things other things like you know, you can really 94 00:04:39.680 --> 00:04:42.519 hyper personalize. We've always talked about that marketing and you know, 95 00:04:42.560 --> 00:04:44.360 we'll get into that in a little bit. But you're 96 00:04:44.399 --> 00:04:48.759 looking at a velocity and content being created, and I 97 00:04:48.800 --> 00:04:50.959 think now people are really thinking about what is a 98 00:04:51.079 --> 00:04:55.360 quality balance? How do you create high quality differentiate storytelling 99 00:04:55.839 --> 00:04:56.480 using AI? 100 00:04:56.759 --> 00:04:57.639 Right, you can use. 101 00:04:57.560 --> 00:05:00.720 It for ideation and drafting, but you still need that 102 00:05:00.839 --> 00:05:05.120 strong human oversight layer to make sure it's creative, authentic, 103 00:05:05.199 --> 00:05:08.480 and it adheres to your brand voice. Right, So where 104 00:05:08.480 --> 00:05:10.639 are you pulling this content from? Can you just pull 105 00:05:10.680 --> 00:05:13.439 from your own content so you can make sure there's 106 00:05:13.480 --> 00:05:16.439 cases where people are getting content from their competitors and 107 00:05:16.439 --> 00:05:18.959 point on their website for their blog post, right, So 108 00:05:18.959 --> 00:05:21.600 you really want to prevent against that. Right, you have 109 00:05:21.680 --> 00:05:25.839 analytics and decision making. You are not just collecting data now, 110 00:05:25.959 --> 00:05:28.160 you're actually going to get AI first insights from the 111 00:05:28.199 --> 00:05:32.040 tools that you can create and have your marketing stack. Right, 112 00:05:32.120 --> 00:05:35.639 So you're just getting a first party data enrichment, and 113 00:05:35.680 --> 00:05:39.439 now you can get even more advanced audience segmentation. 114 00:05:39.240 --> 00:05:40.040 Data back to you. 115 00:05:40.120 --> 00:05:43.319 Right, So AI can synthesize all this Now you used 116 00:05:43.319 --> 00:05:44.759 to have to synthesize this all myself. 117 00:05:45.560 --> 00:05:46.279 Now you have AI. 118 00:05:46.399 --> 00:05:48.120 They can do it for you, right, And that can 119 00:05:48.199 --> 00:05:50.480 really not just give you back your data and your 120 00:05:50.519 --> 00:05:53.279 demand gen, but it can inform your messaging you're positioning, 121 00:05:53.360 --> 00:05:57.040 how well it's doing, what's resonating, right, And then you 122 00:05:57.079 --> 00:05:59.199 know how people are structuring their teams. 123 00:05:59.480 --> 00:06:00.920 That's also really interesting. 124 00:06:00.959 --> 00:06:02.439 So let's you know, I want to hear what Tom 125 00:06:02.439 --> 00:06:04.040 has to say, and then we can talk a little 126 00:06:04.040 --> 00:06:07.720 bit about reschooling, retooling and how people are structuring their teams. 127 00:06:08.079 --> 00:06:08.279 Yeah. 128 00:06:08.399 --> 00:06:10.319 No, you made a whole bunch of really good points there. 129 00:06:10.319 --> 00:06:12.160 The one line I'm going to pull out is no 130 00:06:12.240 --> 00:06:15.480 one will have a bad first draft. That's a really 131 00:06:15.519 --> 00:06:19.360 good point because again, Jennai is good and people have 132 00:06:19.439 --> 00:06:23.360 to understand these are consensus engines more than anything because 133 00:06:23.360 --> 00:06:26.399 of how the AI, the Jenai works, It's been trained 134 00:06:26.399 --> 00:06:29.079 on all this text, this giant corpus of texts, and 135 00:06:29.160 --> 00:06:32.000 it's just pattern matching. So when you give it a prompt, 136 00:06:32.199 --> 00:06:34.759 it pattern matches and goes, oh, this person is talking 137 00:06:34.800 --> 00:06:38.759 about a marketing strategy for a fortune five hundred company. 138 00:06:38.920 --> 00:06:40.959 What are the key components. It'll be very good at 139 00:06:41.000 --> 00:06:43.600 that because it's very well published. But it is just 140 00:06:43.639 --> 00:06:46.399 giving you the average of things because it's mathematical. It's 141 00:06:46.439 --> 00:06:49.439 probabilistic in nature, which is also why it's wrong sebtimes. 142 00:06:49.439 --> 00:06:51.800 So those are really really good points, Tom, I'll bring 143 00:06:51.839 --> 00:06:53.959 you in. I mean, you are the influenced marketer. You've 144 00:06:53.959 --> 00:06:56.199 been doing this stuff for a long time, so you 145 00:06:56.279 --> 00:06:59.480 realized a long time ago that there's real value in 146 00:06:59.519 --> 00:07:04.399 connecting brands with key influencers for a variety of reasons, 147 00:07:04.399 --> 00:07:07.720 for content, but also for advice, for consulting, for awareness, 148 00:07:07.920 --> 00:07:11.800 and for just kind of triggering ideas and the idea flow. 149 00:07:12.120 --> 00:07:13.839 And that's kind of what you use jen Ai for 150 00:07:13.920 --> 00:07:15.240 these days, right Tom, What do you think? 151 00:07:16.160 --> 00:07:18.439 Yeah? I think that you know, for a long time, 152 00:07:18.600 --> 00:07:22.360 companies have struggled with producing content which is actually going 153 00:07:22.439 --> 00:07:27.800 to be engaging and actually grab the attention of their constituents, 154 00:07:27.839 --> 00:07:31.800 their their ideal buyers. And the problem is is that 155 00:07:31.920 --> 00:07:36.000 most companies really just don't have a lot of budget, 156 00:07:36.199 --> 00:07:38.920 or they don't have a lot of will, and they 157 00:07:39.160 --> 00:07:41.600 just end up doing more of the same, right, So 158 00:07:41.639 --> 00:07:45.319 it's oh, our budget got cut this quarter, Well do 159 00:07:45.480 --> 00:07:48.759 more with less. Okay, Well that's only going to get 160 00:07:48.800 --> 00:07:53.120 you so far. And because of that, influencers have actually 161 00:07:53.199 --> 00:07:55.920 risen to you know, the rising up to the top 162 00:07:55.959 --> 00:07:58.920 of the of the awareness level, if you want to 163 00:07:58.920 --> 00:08:01.120 call it, that somewhere were people are noticing them now 164 00:08:01.120 --> 00:08:04.040 more than ever. And that's not just in the consumer space, 165 00:08:04.079 --> 00:08:08.000 but that's in the B to B space. And the 166 00:08:08.079 --> 00:08:11.040 reason for that is that, well, they have audiences, is 167 00:08:11.079 --> 00:08:15.079 they've generated over time because of the condo quality of 168 00:08:15.120 --> 00:08:18.240 content that they produce. And you know, some of them 169 00:08:18.240 --> 00:08:21.160 are independent analysts, some act as consultants, some are pure 170 00:08:21.199 --> 00:08:23.600 content creators. It's sort of a mixed bag all over 171 00:08:23.600 --> 00:08:27.720 the place. But the fact is that by engaging the influencers, 172 00:08:27.800 --> 00:08:32.120 you can actually engage ultimately your ideal buyers a lot better. 173 00:08:32.600 --> 00:08:35.240 Now the GENI stuff is really kind of coming into 174 00:08:35.320 --> 00:08:39.399 the four because again, I think a lot of companies 175 00:08:39.440 --> 00:08:41.240 will be like, wow, great, we can have blog posts 176 00:08:41.320 --> 00:08:46.759 generated seconds. Well, again, you know, the first draft will 177 00:08:46.799 --> 00:08:49.799 be better as a result of GENI. But you really 178 00:08:49.840 --> 00:08:51.639 have to go in there and edit that. So that's 179 00:08:51.679 --> 00:08:55.799 a human function, that's not that's not really a GENAI 180 00:08:56.000 --> 00:08:59.480 function just yet. And then if you really wanted to 181 00:08:59.519 --> 00:09:04.120 do it even better, you'd sort of direct the GENI 182 00:09:04.559 --> 00:09:08.240 AI engine, like whether chat, GPT or perplexity or whatever else, 183 00:09:08.679 --> 00:09:11.960 you direct it to sort of mimic a voice. So, 184 00:09:12.039 --> 00:09:15.159 for instance, that's what I do. I direct chat GPT 185 00:09:15.440 --> 00:09:18.840 to go to my website, to my LinkedIn profile, and 186 00:09:18.879 --> 00:09:23.120 I train it to start seeing the patterns of my 187 00:09:23.200 --> 00:09:25.600 own speech. So then when I get a first draft, 188 00:09:26.240 --> 00:09:29.720 it's even better than it would be normally, right, because 189 00:09:29.720 --> 00:09:34.200 it's using my nomenclature, my acronyms, you know, it's using 190 00:09:34.519 --> 00:09:37.720 the patterns of speech which I exhibit in my own writing. 191 00:09:38.320 --> 00:09:40.360 Right, you're talking about patterns and language models. 192 00:09:40.440 --> 00:09:40.559 Right. 193 00:09:40.600 --> 00:09:43.000 That's why I think a lot of companies are looking 194 00:09:43.039 --> 00:09:46.399 at they have a ton of content already, is can 195 00:09:46.440 --> 00:09:48.720 you pull from what we already have, right? 196 00:09:49.279 --> 00:09:49.879 Or you know? 197 00:09:49.960 --> 00:09:52.120 And it's Tom makes a really good point. What you 198 00:09:52.159 --> 00:09:54.440 put in is going to determine the outcome you get 199 00:09:54.480 --> 00:09:57.000 back from that AI no matter what you're using. 200 00:09:57.120 --> 00:09:57.360 Right. 201 00:09:57.879 --> 00:09:59.720 And so one of the points that we were talking 202 00:09:59.720 --> 00:10:02.279 about earlier before this call was or before this chat 203 00:10:02.360 --> 00:10:04.279 is Tom was saying, you know, we can get like 204 00:10:04.320 --> 00:10:06.879 we put everything into chat GPT or you know, Gemini 205 00:10:06.960 --> 00:10:09.320 or whatever it is. Then you can put it into 206 00:10:09.480 --> 00:10:12.840 other language models like Hemingway or like copywriter GPT or 207 00:10:12.879 --> 00:10:15.120 whatever it is, and you can get a much more 208 00:10:15.159 --> 00:10:16.919 curated But if you ask it to put it in 209 00:10:16.960 --> 00:10:20.639 the voice word count, make it similar to this, but 210 00:10:20.720 --> 00:10:22.919 have this voice, but only pull from these articles and 211 00:10:22.919 --> 00:10:25.679 pull from these notes. You're going to end up with 212 00:10:25.799 --> 00:10:28.399 a really amazing first draft. And then you take it 213 00:10:28.480 --> 00:10:31.600 and you put you know, you curate it yourself, right. 214 00:10:33.120 --> 00:10:35.399 Well, and this is actullently that right. Well, this is 215 00:10:35.600 --> 00:10:38.360 a good point is that there are multiple models and 216 00:10:38.399 --> 00:10:41.879 they do different things in different ways, and they specialize 217 00:10:41.879 --> 00:10:43.600 in certain things, and so that's going to be an 218 00:10:43.639 --> 00:10:47.200 evolving landscape over time as you'll learn that perplexity is 219 00:10:47.240 --> 00:10:49.799 really good for this kind of workload, Gemini is good 220 00:10:49.799 --> 00:10:51.720 for that one, and then all the other sort of 221 00:10:51.759 --> 00:10:54.639 traditional EI models we talked about, like a B testing 222 00:10:55.000 --> 00:10:59.039 or customer churn or pattern recognition, you know, any number 223 00:10:59.039 --> 00:11:01.559 of things, and they is going to be figuring out 224 00:11:01.600 --> 00:11:05.600 where in the workflow you insert some bit of AI 225 00:11:05.840 --> 00:11:09.200 or JENAI, and there are lots of options for doing that, 226 00:11:09.600 --> 00:11:11.840 and I think that what you're going to see, because Amisha, 227 00:11:11.879 --> 00:11:14.559 you hinted at this earlier. What you want is for 228 00:11:14.600 --> 00:11:18.799 there to be this continuous, virtuous cycle of getting insight 229 00:11:18.879 --> 00:11:21.799 from the engines, using that insight, getting insight from the engines, 230 00:11:21.879 --> 00:11:24.519 using that insight. And my prediction has been for a 231 00:11:24.519 --> 00:11:27.600 while now that most of the value from GENAI and 232 00:11:27.639 --> 00:11:30.799 even traditionally I will come in the form of suggestions 233 00:11:31.159 --> 00:11:34.600 where you're getting ideas and you can just actively do that, 234 00:11:34.799 --> 00:11:36.519 or you can set it up to passively do that, 235 00:11:37.000 --> 00:11:40.519 but you can put these engines into workflows. And let's 236 00:11:40.559 --> 00:11:44.159 face it, I was always joking with myself about OPS 237 00:11:44.200 --> 00:11:47.000 and we was talking about marketing OPS and data OPS 238 00:11:47.120 --> 00:11:49.440 and dev ops and all this stuff. Well, what is ops. 239 00:11:49.480 --> 00:11:52.600 It's the actual work only that's operations is the stuff 240 00:11:52.639 --> 00:11:55.600 that humans still have to do. Right, So marketing OPS 241 00:11:55.679 --> 00:12:00.120 is changing dramatically, and that's top of mind for cmos, right. 242 00:12:00.919 --> 00:12:03.279 Yeah, I mean, look, when we had marketing OPS, they're 243 00:12:03.320 --> 00:12:05.360 pulling together all the data from all these different sources 244 00:12:05.360 --> 00:12:07.840 and you dump into something else, then you'd get analysis 245 00:12:07.879 --> 00:12:09.279 and then you have to go back because what you 246 00:12:09.320 --> 00:12:12.279 really need to do is if you really want to 247 00:12:12.440 --> 00:12:14.320 drive the business, you have to be able to go 248 00:12:14.399 --> 00:12:17.159 back in that business meeting with your colleagues, right, the 249 00:12:17.279 --> 00:12:20.919 other sort of heads at the company, product, customer, sales, 250 00:12:21.000 --> 00:12:23.320 everyone else, and be able to say, this is what 251 00:12:23.320 --> 00:12:25.200 we're driving, this is why we drove it, this is 252 00:12:25.200 --> 00:12:28.639 what's working to drive the actual business and bottom line, right, 253 00:12:28.679 --> 00:12:30.240 because that's what they're really interested in. 254 00:12:30.320 --> 00:12:30.440 Right. 255 00:12:30.720 --> 00:12:33.919 It's people talk about brand and colors and website, that's 256 00:12:33.960 --> 00:12:36.480 all plays in. But the end of the day, we're 257 00:12:36.519 --> 00:12:38.600 really on the hook for a number in marketing, right 258 00:12:38.639 --> 00:12:41.960 as a leader, And so when you're thinking about that, 259 00:12:42.039 --> 00:12:44.480 you want to show up with that insight the more 260 00:12:44.639 --> 00:12:47.840 because sometimes you can bring back insight to the company 261 00:12:48.080 --> 00:12:50.240 and say this is what's actually happening, this is what 262 00:12:50.279 --> 00:12:52.799 we're finding. And then when you're working with sales together, 263 00:12:52.960 --> 00:12:56.200 you're kind of having a reality check of it's working 264 00:12:56.200 --> 00:12:59.639 and what's not based on real data and real insights 265 00:13:00.039 --> 00:13:02.279 and have all the data. There's so much data out there, 266 00:13:02.480 --> 00:13:06.120 it's overwhelming. You really need that layer of analysis, right. 267 00:13:06.519 --> 00:13:09.039 And then so you know, one of the things that 268 00:13:09.039 --> 00:13:11.080 we were just talking about, how is everybody going to 269 00:13:11.120 --> 00:13:13.320 structure their teams now, right, Like, when you really think 270 00:13:13.360 --> 00:13:15.720 about it, we're two years in, so a lot of 271 00:13:15.759 --> 00:13:17.559 people are doing you know, in the beginning, they were 272 00:13:17.600 --> 00:13:18.240 doing kind. 273 00:13:18.039 --> 00:13:20.840 Of pods and they still are and this seems to. 274 00:13:20.759 --> 00:13:24.519 Work really well where you have cross functional teams that 275 00:13:24.720 --> 00:13:28.639 bring in someone who knows AI right with content creators, 276 00:13:28.679 --> 00:13:31.480 data analysts, and campaign strategists and you're kind of all 277 00:13:31.480 --> 00:13:35.039 sitting there together in this pod, and that pod can 278 00:13:35.120 --> 00:13:37.679 kind of inform the rest of marketing, right, but they're 279 00:13:37.720 --> 00:13:42.159 really the content, data and campaign coming together. And you 280 00:13:42.279 --> 00:13:45.960 have a pod so that is really focused and dedicated, 281 00:13:45.960 --> 00:13:49.240 and then you have someone who's trained and knowledgeable right 282 00:13:49.519 --> 00:13:51.759 in this kind of new era. But now we're two 283 00:13:51.799 --> 00:13:53.200 years in, so you're going to be able to find 284 00:13:53.240 --> 00:13:55.480 people who've done it and be able to hire them 285 00:13:55.559 --> 00:13:58.120 or hire a consultant and bring them in. And then 286 00:13:58.159 --> 00:14:00.440 you have you're talking about ops teams going to have 287 00:14:00.480 --> 00:14:03.320 now AI ops teams. You have revops DevOps, right, but 288 00:14:03.360 --> 00:14:06.960 you have revops in between marketing and sales. You're going 289 00:14:07.000 --> 00:14:09.480 to have someone on that team that are going to 290 00:14:09.480 --> 00:14:13.840 be managing implementation, tool selection compliance. That still has to 291 00:14:13.919 --> 00:14:16.639 happen because you're going to be You're still building out 292 00:14:16.639 --> 00:14:19.360 your marketing stack, right, You're going to bring in some 293 00:14:19.440 --> 00:14:21.279 AI tools. What what are you going to bring in? 294 00:14:21.320 --> 00:14:23.279 How are you going to integrate what you already have? 295 00:14:23.799 --> 00:14:26.320 So you kind of need in your marketing ops rev 296 00:14:26.360 --> 00:14:29.200 op you need that or you need that there, and 297 00:14:29.240 --> 00:14:30.639 then you really have to take a look at your 298 00:14:30.720 --> 00:14:33.519 strategy for the year and think about, Okay, how am 299 00:14:33.559 --> 00:14:35.320 I going to make because there's a lot of heat 300 00:14:35.440 --> 00:14:37.799 like do more with less that we have like. 301 00:14:37.840 --> 00:14:40.360 Hybrid human and AI collaboration. 302 00:14:39.879 --> 00:14:42.000 Model, because now you have to think of AI as 303 00:14:42.039 --> 00:14:44.600 a team member, right, You're not replacing, but as a 304 00:14:44.639 --> 00:14:47.879 team member. So your team is focused on strategy, creativity, 305 00:14:47.879 --> 00:14:51.759 emotional intelligence, and the AI is handling execution, automation and 306 00:14:51.840 --> 00:14:54.679 data crunching. Right, So you really have to think about 307 00:14:55.000 --> 00:14:58.519 when you're structuring your team. It's now the tools become 308 00:14:58.679 --> 00:15:01.559 not just your marketing stack, but it's almost like it's 309 00:15:01.600 --> 00:15:02.840 a factor and a team member. 310 00:15:02.840 --> 00:15:03.480 Almost. 311 00:15:03.720 --> 00:15:06.799 Yeah, that's an excellent point. And I love this concept 312 00:15:06.799 --> 00:15:10.320 of pods. And I'll share something that I learned gosh 313 00:15:10.360 --> 00:15:13.919 twenty years ago almost at a conference at TDWI conference 314 00:15:13.960 --> 00:15:16.679 in fact, with Maureen Clary and Kelly Gilmore, and they 315 00:15:16.679 --> 00:15:21.519 did this session called something like Power and Politics or something, 316 00:15:21.559 --> 00:15:24.080 and it was role playing, and so you'd come in 317 00:15:24.159 --> 00:15:26.240 for this session. It's like an all day session and 318 00:15:26.279 --> 00:15:28.360 they'd like hand out cards and you'd find out what 319 00:15:28.480 --> 00:15:30.600 role you're supposed to play, and it would be like, 320 00:15:30.840 --> 00:15:33.799 you know, junior associat or director or VP or whatever, 321 00:15:33.879 --> 00:15:36.759 and you had to tackle projects and just see what 322 00:15:36.840 --> 00:15:39.960 life was like from that different world. It was incredibly 323 00:15:40.039 --> 00:15:43.559 elucidating because all of a sudden, senior executives remembered what 324 00:15:43.600 --> 00:15:45.519 it's like to be a junior analyst, you know, to 325 00:15:45.679 --> 00:15:49.120 just offering ideas and getting ignored, that whole thing. But 326 00:15:49.240 --> 00:15:51.159 what I learned there, I MG, here, we could pick 327 00:15:51.200 --> 00:15:53.039 this up a little bit in this segment and then 328 00:15:53.080 --> 00:15:55.279 in the next epic maybe is and I'll throw this 329 00:15:55.320 --> 00:15:58.200 out to Tom maybe first or and then a Michigan comment. 330 00:15:58.440 --> 00:16:01.639 I learned the ideal team side is four. And the 331 00:16:01.679 --> 00:16:04.080 reason I say four is because at three it's two 332 00:16:04.159 --> 00:16:06.240 to one, At five, it's kind of three to two. 333 00:16:06.559 --> 00:16:09.080 At four it's always even, and it's not often going 334 00:16:09.159 --> 00:16:11.840 to be three to one. So it's like it seems 335 00:16:11.919 --> 00:16:14.360 easier to come to consensus when there are four people 336 00:16:14.399 --> 00:16:16.960 talking about something and you have to decide, because let's 337 00:16:16.960 --> 00:16:18.679 basically the business, you have to decide. You have to 338 00:16:18.679 --> 00:16:21.559 make decisions and then monitor how well that works and 339 00:16:21.600 --> 00:16:23.519 then adjust. But Tom, what do you think about that? 340 00:16:24.639 --> 00:16:27.480 That's interesting. I've never heard about the number four being 341 00:16:27.559 --> 00:16:31.039 the optimum size of a team, but you heard it here. 342 00:16:31.039 --> 00:16:36.159 F I've noticed that smaller teams three to three people 343 00:16:36.200 --> 00:16:39.159 on up you know, four or five, six, seven. I 344 00:16:39.159 --> 00:16:42.320 mean that works. I see it with my own clients 345 00:16:43.080 --> 00:16:47.720 on the team meetings that I attend with them. Conversations 346 00:16:47.720 --> 00:16:50.600 can flow, ideas can flow, and we can come to 347 00:16:50.720 --> 00:16:53.919 a consensus about pretty quickly about what we want to do. 348 00:16:54.559 --> 00:16:57.039 So I think that that there's probably a lot of 349 00:16:57.080 --> 00:17:00.039 legitimacy to that. I love the idea of pods. I 350 00:17:00.039 --> 00:17:02.519 think that's really neat. I think one thing that a 351 00:17:02.600 --> 00:17:05.880 lot of companies still struggle with is well, how do 352 00:17:05.920 --> 00:17:10.400 they organize themselves these days? Because still many companies, in 353 00:17:10.480 --> 00:17:16.039 my experience, don't have a direct line of communication with 354 00:17:16.079 --> 00:17:19.960 the sales team. And as somebody who works with influencers, 355 00:17:20.359 --> 00:17:25.119 I hear from influencers about feedback about a company that's 356 00:17:25.200 --> 00:17:29.119 not always favorable about the company, right, but they need 357 00:17:29.160 --> 00:17:32.920 to hear it, and I bring it back to them 358 00:17:32.920 --> 00:17:36.359 and I bring back from the form of constructive criticism. 359 00:17:36.759 --> 00:17:40.680 But the sales team is also out there hearing things too, right, 360 00:17:40.759 --> 00:17:43.920 So when you're pitching somebody, you're going to get feedback 361 00:17:43.960 --> 00:17:46.480 pretty quickly about you. 362 00:17:46.960 --> 00:17:48.519 You're reminding me of something, I'm going to throw us 363 00:17:48.519 --> 00:17:50.000 out as the segment it's coming to a close. 364 00:17:50.079 --> 00:17:50.279 Though. 365 00:17:50.640 --> 00:17:52.640 We use read AI and a lot of people are 366 00:17:52.680 --> 00:17:54.640 using these tools otter. There's a whole bunch of them, 367 00:17:54.799 --> 00:17:57.319 and they capture all the notes, they do transcripts, they 368 00:17:57.359 --> 00:18:00.559 give you talking points, they give you next steps actions, 369 00:18:00.559 --> 00:18:02.559 all that stuff comes right out of the box. And 370 00:18:02.640 --> 00:18:05.400 so now as an individual you can use that to 371 00:18:05.480 --> 00:18:08.440 kind of manage your own workflow. But managers, if they 372 00:18:08.480 --> 00:18:11.839 get access to all those individual ones, can summarize all that. 373 00:18:11.839 --> 00:18:14.039 That's what I made was hinting at earlier. The demver 374 00:18:14.119 --> 00:18:16.640 crunching in the summarization can be done by AI, by 375 00:18:16.680 --> 00:18:19.839 jen AI. So what happens is the senior directors can 376 00:18:19.920 --> 00:18:23.319 see what's happening and they'll get little prompts that say, hmm, 377 00:18:23.359 --> 00:18:25.799 things are starting to fall apart. In the East Coast division. 378 00:18:26.000 --> 00:18:28.480 Call those people now, well, folks, don't touch that. That'll 379 00:18:28.519 --> 00:18:30.880 be right back. You're listening to Inside Analysis. 380 00:18:31.519 --> 00:18:43.359 Expected, welcome back to Inside Analysis. Here's your host, Eric Tabanaugh. 381 00:18:43.720 --> 00:18:47.680 To show all right, folks back here on Inside Analysis 382 00:18:47.759 --> 00:18:51.279 talking all about jen Ai and ai and automation and 383 00:18:51.319 --> 00:18:54.640 how they're changing the game in business writ large, but 384 00:18:54.839 --> 00:18:56.559 a lot of us here in this coll we focus 385 00:18:56.640 --> 00:19:02.799 on marketing and messaging articularly vision value knowing what to do, 386 00:19:02.880 --> 00:19:05.200 and that's one of the big issues. And you know, 387 00:19:05.440 --> 00:19:07.319 we picked up I'll pick up on the end of 388 00:19:07.400 --> 00:19:10.279 last segment. We were talking about read Ai and otter 389 00:19:10.400 --> 00:19:12.519 and even zoom has its own thing and teams has 390 00:19:12.519 --> 00:19:14.039 its own things. So there are all these tools you 391 00:19:14.039 --> 00:19:16.480 can choose, pick and choose from. But the point is 392 00:19:16.799 --> 00:19:19.599 one of the most powerful aspects of jennai is this 393 00:19:19.720 --> 00:19:23.160 summarization components where you can take a big chunk of 394 00:19:23.160 --> 00:19:25.200 texts and say, summarize this for me. It does that 395 00:19:25.480 --> 00:19:27.960 very very well. You know, I've heard some concerns that 396 00:19:28.000 --> 00:19:30.319 it tends for in long documents. It pulls from the 397 00:19:30.319 --> 00:19:32.079 front of the end, not so much from the middle. 398 00:19:32.359 --> 00:19:34.359 So there are some interesting issues to kind of watch 399 00:19:34.400 --> 00:19:38.039 out for. But that is incredibly useful. And when you 400 00:19:38.079 --> 00:19:41.000 think about the time you used to have to spend okay, 401 00:19:41.039 --> 00:19:43.400