1 00:00:00,000 --> 00:00:02,320 ready to decode the future of business. 2 00:00:02,320 --> 00:00:03,280 I'm in. 3 00:00:03,280 --> 00:00:06,520 Today's deep dive is all about AI in the enterprise, 4 00:00:06,520 --> 00:00:09,320 and we're going deep on this iconic Q report you sent. 5 00:00:09,320 --> 00:00:10,280 It's a good one. 6 00:00:10,280 --> 00:00:12,560 Trust me, it's packed with insights. 7 00:00:12,560 --> 00:00:14,320 You'll be sounding like a total rock star 8 00:00:14,320 --> 00:00:15,240 in your next meeting. 9 00:00:15,240 --> 00:00:16,720 Love it, let's get into it. 10 00:00:16,720 --> 00:00:19,040 It really seems like everyone and their mother 11 00:00:19,040 --> 00:00:20,680 is buzzing about AI. 12 00:00:20,680 --> 00:00:23,160 Yeah, it's definitely the buzzword of the year. 13 00:00:23,160 --> 00:00:26,800 But this report, it cuts through all the hype. 14 00:00:26,800 --> 00:00:27,640 Totally. 15 00:00:27,640 --> 00:00:29,380 It shows how the big players, 16 00:00:29,380 --> 00:00:31,560 the ones who actually put their money where their algorithms 17 00:00:31,560 --> 00:00:33,760 are, are using AI. 18 00:00:33,760 --> 00:00:35,880 They're not just dipping their toes in the water anymore. 19 00:00:35,880 --> 00:00:37,920 Exactly, it's not just talk anymore. 20 00:00:37,920 --> 00:00:41,800 Get this, the report says 89%, a massive 89%, 21 00:00:41,800 --> 00:00:45,220 of C-suite execs believe that integrating AI, 22 00:00:45,220 --> 00:00:47,740 this type of AI, generative AI, 23 00:00:47,740 --> 00:00:49,520 is absolutely crucial for their business. 24 00:00:49,520 --> 00:00:51,280 It's a complete game changer. 25 00:00:51,280 --> 00:00:54,480 It's not just about keeping up with the competition anymore. 26 00:00:54,480 --> 00:00:56,440 They're saying that it's completely changing 27 00:00:56,440 --> 00:00:57,880 how they operate. 28 00:00:57,880 --> 00:00:58,700 And that's the thing, 29 00:00:58,700 --> 00:01:00,760 it's not just another tech trend. 30 00:01:00,760 --> 00:01:05,320 Generative AI can create content, automate tasks. 31 00:01:05,320 --> 00:01:06,680 And really anything you can think of. 32 00:01:06,680 --> 00:01:08,760 Even mimic human creativity 33 00:01:08,760 --> 00:01:10,880 in a way we haven't really seen before. 34 00:01:10,880 --> 00:01:12,760 It's pretty mind blowing when you think about it. 35 00:01:12,760 --> 00:01:15,500 No wonder executives are sitting up and taking notice. 36 00:01:15,500 --> 00:01:17,040 Okay, so they're convinced, 37 00:01:17,040 --> 00:01:19,120 but here's what's so fascinating. 38 00:01:19,120 --> 00:01:21,520 The report found that most of these companies 39 00:01:21,520 --> 00:01:24,840 are dipping into their existing R&D budgets 40 00:01:24,840 --> 00:01:27,120 to fund these AI initiatives. 41 00:01:27,120 --> 00:01:28,040 Interesting. 42 00:01:28,040 --> 00:01:29,320 They're not quite ready to create 43 00:01:29,320 --> 00:01:33,000 a whole separate budget line just for AI yet. 44 00:01:33,000 --> 00:01:36,520 It's like they're cautiously wading into the pool, 45 00:01:36,520 --> 00:01:37,680 just testing the temperature 46 00:01:37,680 --> 00:01:39,720 before they take the full plunge. 47 00:01:39,720 --> 00:01:40,880 I like that analogy. 48 00:01:40,880 --> 00:01:43,020 Which makes sense, there's still a lot to figure out. 49 00:01:43,020 --> 00:01:45,480 For sure, and speaking of figuring things out, 50 00:01:45,480 --> 00:01:47,440 a lot of this early investment seems to be focused 51 00:01:47,440 --> 00:01:50,480 on just boosting internal productivity. 52 00:01:50,480 --> 00:01:53,040 Just things that can make their operations smoother, 53 00:01:53,040 --> 00:01:53,860 more efficient. 54 00:01:53,860 --> 00:01:54,700 Absolutely. 55 00:01:54,700 --> 00:01:57,640 So we're talking things like using AI 56 00:01:57,640 --> 00:02:00,400 to let's say speed up coding. 57 00:02:00,400 --> 00:02:01,440 Which is already happening. 58 00:02:01,440 --> 00:02:03,900 Like what software developers are already seeing 59 00:02:03,900 --> 00:02:05,880 with tools like GitHub Copilot. 60 00:02:05,880 --> 00:02:06,720 Right, fine. 61 00:02:06,720 --> 00:02:10,440 Or imagine streamlining IT support tickets, 62 00:02:10,440 --> 00:02:12,960 even automating some of those marketing campaigns. 63 00:02:12,960 --> 00:02:14,920 I mean, who wants to spend hours on that? 64 00:02:14,920 --> 00:02:16,000 Nobody. 65 00:02:16,000 --> 00:02:18,600 It's all about working smarter, not harder. 66 00:02:18,600 --> 00:02:19,620 I love that. 67 00:02:19,620 --> 00:02:23,840 But more importantly, it frees up employees, right? 68 00:02:23,840 --> 00:02:24,680 Yes. 69 00:02:24,680 --> 00:02:27,360 To focus on the things that AI, at least for now, 70 00:02:27,360 --> 00:02:28,240 can't replicate. 71 00:02:28,240 --> 00:02:29,400 Right, that human touch. 72 00:02:29,400 --> 00:02:31,480 That creative spark, the strategic thinking. 73 00:02:31,480 --> 00:02:32,640 Precisely. 74 00:02:32,640 --> 00:02:34,320 And that's where companies are already 75 00:02:34,320 --> 00:02:38,080 seeing those early wins with AI cutting costs 76 00:02:38,080 --> 00:02:41,040 and freeing up their most valuable asset. 77 00:02:41,040 --> 00:02:41,720 They're people. 78 00:02:41,720 --> 00:02:42,760 They're people, for sure. 79 00:02:42,760 --> 00:02:44,160 For higher level tasks. 80 00:02:44,160 --> 00:02:45,440 Sounds like a win-win. 81 00:02:45,440 --> 00:02:46,040 Definitely. 82 00:02:46,040 --> 00:02:49,080 But surely it's not all smooth sailing, right? 83 00:02:49,080 --> 00:02:51,040 What about the challenges companies are facing 84 00:02:51,040 --> 00:02:52,800 as they try to integrate AI? 85 00:02:52,800 --> 00:02:54,260 Well, you hit the nail on the head. 86 00:02:54,260 --> 00:02:55,360 Oh no, what is it? 87 00:02:55,360 --> 00:02:59,160 The report highlights a big one, just finding, hiring 88 00:02:59,160 --> 00:03:00,440 those AI experts. 89 00:03:00,440 --> 00:03:01,920 Got to be so competitive. 90 00:03:01,920 --> 00:03:03,040 It's incredibly competitive. 91 00:03:03,040 --> 00:03:05,800 It's a real seller's market for talent. 92 00:03:05,800 --> 00:03:06,640 I can only imagine. 93 00:03:06,640 --> 00:03:08,920 It seems like everyone wants to be an AI whisperer 94 00:03:08,920 --> 00:03:09,520 these days. 95 00:03:09,520 --> 00:03:10,640 That's a good way to put it. 96 00:03:10,640 --> 00:03:13,040 So what are companies doing to combat that? 97 00:03:13,040 --> 00:03:14,760 Well, some are getting creative. 98 00:03:14,760 --> 00:03:15,400 How so? 99 00:03:15,400 --> 00:03:18,080 We're seeing companies launch their own internal AI 100 00:03:18,080 --> 00:03:21,200 academies, upskilling their current workforce. 101 00:03:21,200 --> 00:03:23,520 Others are partnering with universities, 102 00:03:23,520 --> 00:03:25,960 trying to nurture a pipeline of future talent. 103 00:03:25,960 --> 00:03:26,760 Makes sense. 104 00:03:26,760 --> 00:03:28,360 You've got to build what you can't buy. 105 00:03:28,360 --> 00:03:29,320 Exactly. 106 00:03:29,320 --> 00:03:32,280 But aside from that whole talent crunch, 107 00:03:32,280 --> 00:03:36,440 I'd imagine there are concerns about security, privacy, 108 00:03:36,440 --> 00:03:36,940 right? 109 00:03:36,940 --> 00:03:37,440 I appreciate it. 110 00:03:37,440 --> 00:03:39,760 Especially in fields like HR or law. 111 00:03:39,760 --> 00:03:40,360 Very true. 112 00:03:40,360 --> 00:03:42,720 Where sensitive information is everything. 113 00:03:42,720 --> 00:03:43,480 It's paramount. 114 00:03:43,480 --> 00:03:44,600 You don't want to mess around with that. 115 00:03:44,600 --> 00:03:45,600 You're absolutely right. 116 00:03:45,600 --> 00:03:47,360 And the report acknowledges that. 117 00:03:47,360 --> 00:03:47,860 OK, good. 118 00:03:47,860 --> 00:03:49,800 There's definitely this sense of caution, 119 00:03:49,800 --> 00:03:53,000 especially with the regulations around data privacy still 120 00:03:53,000 --> 00:03:53,480 evolving. 121 00:03:53,480 --> 00:03:55,440 I mean, it's a bit of a wild west out there. 122 00:03:55,440 --> 00:03:56,640 It really is. 123 00:03:56,640 --> 00:03:59,800 So with all this in mind, are companies 124 00:03:59,800 --> 00:04:04,320 leaning towards building their own AI solutions from scratch? 125 00:04:04,320 --> 00:04:06,680 Or are they more comfortable buying from those already 126 00:04:06,680 --> 00:04:07,720 established players? 127 00:04:07,720 --> 00:04:08,280 Right. 128 00:04:08,280 --> 00:04:09,360 What's the trend? 129 00:04:09,360 --> 00:04:11,080 The report actually found it really 130 00:04:11,080 --> 00:04:12,440 depends on the industry. 131 00:04:12,440 --> 00:04:13,280 OK, interesting. 132 00:04:13,280 --> 00:04:15,000 Tech companies, as you might expect, 133 00:04:15,000 --> 00:04:18,320 are all about building their own solutions in-house. 134 00:04:18,320 --> 00:04:19,400 Of course, makes sense. 135 00:04:19,400 --> 00:04:21,200 It's about staying ahead of the curve, 136 00:04:21,200 --> 00:04:22,400 owning that technology. 137 00:04:22,400 --> 00:04:23,720 Keeping their finger on the post. 138 00:04:23,720 --> 00:04:25,120 Yeah, innovating constantly. 139 00:04:25,120 --> 00:04:26,520 Right, right. 140 00:04:26,520 --> 00:04:29,800 But what about industries like finance or health care? 141 00:04:29,800 --> 00:04:34,520 They tend to favor buying ready-made solutions. 142 00:04:34,520 --> 00:04:35,480 Does that make sense? 143 00:04:35,480 --> 00:04:36,980 And it does when you think about it. 144 00:04:36,980 --> 00:04:39,560 Building in-house, it's incredibly complex. 145 00:04:39,560 --> 00:04:40,080 Yeah. 146 00:04:40,080 --> 00:04:43,280 Especially with the added pressure of regulations. 147 00:04:43,280 --> 00:04:43,780 Sure. 148 00:04:43,780 --> 00:04:45,280 Like, high paya in health care. 149 00:04:45,280 --> 00:04:46,600 You definitely don't want to be messing around 150 00:04:46,600 --> 00:04:49,640 with compliance when it comes to medical records. 151 00:04:49,640 --> 00:04:50,520 Absolutely not. 152 00:04:50,520 --> 00:04:51,040 Wow. 153 00:04:51,040 --> 00:04:53,520 So it seems like there's no one-size-fits-all approach 154 00:04:53,520 --> 00:04:54,720 when it comes to AI. 155 00:04:54,720 --> 00:04:55,480 Exactly. 156 00:04:55,480 --> 00:04:57,800 And that leads us to another fascinating point. 157 00:04:57,800 --> 00:04:59,080 OK, I'm listening. 158 00:04:59,080 --> 00:05:02,120 The current state of the AI market itself. 159 00:05:02,120 --> 00:05:04,800 So we've talked about companies dipping their toes 160 00:05:04,800 --> 00:05:06,320 into the AI pool. 161 00:05:06,320 --> 00:05:08,720 It's more like diving in headfirst at this point. 162 00:05:08,720 --> 00:05:09,720 True. 163 00:05:09,720 --> 00:05:12,320 But who's making the biggest splash in all of this? 164 00:05:12,320 --> 00:05:14,040 That's the question, isn't it? 165 00:05:14,040 --> 00:05:17,120 Is it all about those big jack-of-all-trades AI 166 00:05:17,120 --> 00:05:18,560 models we keep hearing about? 167 00:05:18,560 --> 00:05:20,800 Well, that's where things get really interesting. 168 00:05:20,800 --> 00:05:21,360 Oh. 169 00:05:21,360 --> 00:05:22,840 While those large language models 170 00:05:22,840 --> 00:05:24,400 are definitely impressive, the report 171 00:05:24,400 --> 00:05:26,640 suggests we might see a shift in the future. 172 00:05:26,640 --> 00:05:27,280 A shift. 173 00:05:27,280 --> 00:05:27,920 What do you mean? 174 00:05:27,920 --> 00:05:30,400 Towards more specialized AI tools. 175 00:05:30,400 --> 00:05:30,920 Specialized. 176 00:05:30,920 --> 00:05:35,600 So instead of one giant AI brain trying to do it all, 177 00:05:35,600 --> 00:05:40,000 you're saying we might see more targeted AI, each 178 00:05:40,000 --> 00:05:42,880 with their own kind of area of expertise. 179 00:05:42,880 --> 00:05:43,400 Exactly. 180 00:05:43,400 --> 00:05:45,840 It's like using the right tool for the job. 181 00:05:45,840 --> 00:05:46,560 Makes sense. 182 00:05:46,560 --> 00:05:49,120 You wouldn't use a hammer to tighten a screw, would you? 183 00:05:49,120 --> 00:05:50,360 Definitely not. 184 00:05:50,360 --> 00:05:54,080 Companies are realizing that smaller, more focused AI 185 00:05:54,080 --> 00:05:57,520 models, the ones tailored for specific tasks, 186 00:05:57,520 --> 00:05:59,800 can actually be even more powerful. 187 00:05:59,800 --> 00:06:05,480 OK, so instead of one AI trying to analyze legal documents, 188 00:06:05,480 --> 00:06:07,000 and do you write marketing copy? 189 00:06:07,000 --> 00:06:07,500 Right. 190 00:06:07,500 --> 00:06:08,000 It's too much. 191 00:06:08,000 --> 00:06:11,360 You might have one that's a whiz at legal jargon, 192 00:06:11,360 --> 00:06:13,600 and another one that crafts amazing ad copy. 193 00:06:13,600 --> 00:06:14,880 Precisely. 194 00:06:14,880 --> 00:06:17,080 And this shift towards specialization 195 00:06:17,080 --> 00:06:18,640 could really be a game changer. 196 00:06:18,640 --> 00:06:19,400 How so? 197 00:06:19,400 --> 00:06:22,160 Well, for one, it could mean less reliance 198 00:06:22,160 --> 00:06:23,720 on those big AI providers. 199 00:06:23,720 --> 00:06:25,760 Ah, so it gives companies more flexibility. 200 00:06:25,760 --> 00:06:26,320 Exactly. 201 00:06:26,320 --> 00:06:27,880 More flexibility and control. 202 00:06:27,880 --> 00:06:30,360 And I bet smaller businesses are breathing a sigh of relief. 203 00:06:30,360 --> 00:06:31,040 Absolutely. 204 00:06:31,040 --> 00:06:33,400 These smaller models are often much more 205 00:06:33,400 --> 00:06:34,640 cost effective to implement. 206 00:06:34,640 --> 00:06:36,920 Which is huge when you're working with a tighter budget. 207 00:06:36,920 --> 00:06:37,520 Huge. 208 00:06:37,520 --> 00:06:39,000 It levels the playing field in a way 209 00:06:39,000 --> 00:06:40,240 we haven't really seen before. 210 00:06:40,240 --> 00:06:41,400 That's exciting. 211 00:06:41,400 --> 00:06:43,960 So many possibilities, especially for businesses 212 00:06:43,960 --> 00:06:46,560 with those very niche needs. 213 00:06:46,560 --> 00:06:47,080 Absolutely. 214 00:06:47,080 --> 00:06:50,840 But even with all the best AI tools in the world, 215 00:06:50,840 --> 00:06:54,280 isn't data still a major, major factor? 216 00:06:54,280 --> 00:06:57,200 It's like, you can't build a house without solid foundations. 217 00:06:57,200 --> 00:06:58,400 Yes, spot on. 218 00:06:58,400 --> 00:07:00,960 The report really stresses the importance of data 219 00:07:00,960 --> 00:07:02,560 infrastructure and readiness. 220 00:07:02,560 --> 00:07:03,320 Oh, true. 221 00:07:03,320 --> 00:07:05,360 Companies need to get their data houses in order 222 00:07:05,360 --> 00:07:08,760 before they even think about AI implementation. 223 00:07:08,760 --> 00:07:09,840 It's like baking a cake. 224 00:07:09,840 --> 00:07:11,400 You can have the best recipe. 225 00:07:11,400 --> 00:07:12,960 But if your ingredients are spoiled. 226 00:07:12,960 --> 00:07:13,640 Exactly. 227 00:07:13,640 --> 00:07:14,800 The cake's not going to turn out right. 228 00:07:14,800 --> 00:07:15,440 Disaster. 229 00:07:15,440 --> 00:07:15,960 Yeah. 230 00:07:15,960 --> 00:07:19,480 So data cleaning, organizing, securing, 231 00:07:19,480 --> 00:07:23,120 it's the less glamorous side of the AI revolution. 232 00:07:23,120 --> 00:07:24,640 It's the essential side. 233 00:07:24,640 --> 00:07:26,400 Investing in robust data management 234 00:07:26,400 --> 00:07:27,840 isn't really optional. 235 00:07:27,840 --> 00:07:30,120 It's the foundation for AI success. 236 00:07:30,120 --> 00:07:32,640 OK, so we've got the trends, the challenges, 237 00:07:32,640 --> 00:07:34,280 the importance of data. 238 00:07:34,280 --> 00:07:36,240 But what I really want to know is, 239 00:07:36,240 --> 00:07:40,160 are we seeing a return on all this AI investment? 240 00:07:40,160 --> 00:07:41,600 The million dollar question. 241 00:07:41,600 --> 00:07:44,800 Is it actually making a difference for businesses? 242 00:07:44,800 --> 00:07:45,640 It is. 243 00:07:45,640 --> 00:07:48,160 And the report digs into some specific examples. 244 00:07:48,160 --> 00:07:48,800 What's the carrot? 245 00:07:48,800 --> 00:07:52,560 Where companies are seeing some pretty impressive ROI. 246 00:07:52,560 --> 00:07:53,880 OK, I'm all ears. 247 00:07:53,880 --> 00:07:56,040 One area that's consistently delivering 248 00:07:56,040 --> 00:07:58,120 is customer service. 249 00:07:58,120 --> 00:08:01,000 Those AI powered chat bots popping up everywhere. 250 00:08:01,000 --> 00:08:01,720 Exactly. 251 00:08:01,720 --> 00:08:03,480 But they're not just a novelty anymore. 252 00:08:03,480 --> 00:08:04,640 They're getting really good. 253 00:08:04,640 --> 00:08:07,160 We're talking sophisticated virtual assistance. 254 00:08:07,160 --> 00:08:07,680 Wow. 255 00:08:07,680 --> 00:08:10,400 That can handle a wide range of customer queries, 256 00:08:10,400 --> 00:08:13,320 which frees up those human agents to deal 257 00:08:13,320 --> 00:08:14,800 with the more complex issues. 258 00:08:14,800 --> 00:08:17,120 Right, the stuff that really requires that human touch. 259 00:08:17,120 --> 00:08:17,960 Exactly. 260 00:08:17,960 --> 00:08:20,200 Companies are seeing reduced resolution times, 261 00:08:20,200 --> 00:08:21,520 happier customers. 262 00:08:21,520 --> 00:08:24,120 Happy customers, happy life, that's what they say. 263 00:08:24,120 --> 00:08:24,800 That's right. 264 00:08:24,800 --> 00:08:27,000 And even lower operating costs. 265 00:08:27,000 --> 00:08:29,480 So it's not about replacing humans altogether. 266 00:08:29,480 --> 00:08:29,980 No. 267 00:08:29,980 --> 00:08:33,960 It's about making those human interactions even better. 268 00:08:33,960 --> 00:08:34,840 Precisely. 269 00:08:34,840 --> 00:08:37,400 And it's not just customer service. 270 00:08:37,400 --> 00:08:41,400 The report also highlights how AI is transforming those IT 271 00:08:41,400 --> 00:08:42,360 departments. 272 00:08:42,360 --> 00:08:43,080 Oh, interesting. 273 00:08:43,080 --> 00:08:45,960 We're talking about automating tasks like ticket routing. 274 00:08:45,960 --> 00:08:47,080 Oh, that would be amazing. 275 00:08:47,080 --> 00:08:49,520 Even bug detection and code. 276 00:08:49,520 --> 00:08:50,120 Wow. 277 00:08:50,120 --> 00:08:52,920 This frees up those IT professionals 278 00:08:52,920 --> 00:08:55,040 to focus on more strategic projects. 279 00:08:55,040 --> 00:08:56,640 Instead of putting out fires all day. 280 00:08:56,640 --> 00:08:57,640 Exactly. 281 00:08:57,640 --> 00:09:00,520 Leading to increased efficiency, cost saving. 282 00:09:00,520 --> 00:09:02,960 It's like giving those IT departments a much needed 283 00:09:02,960 --> 00:09:04,040 extra pair of hands. 284 00:09:04,040 --> 00:09:05,000 At least. 285 00:09:05,000 --> 00:09:06,120 Or maybe an extra brain. 286 00:09:06,120 --> 00:09:06,760 Right. 287 00:09:06,760 --> 00:09:09,120 And let's not forget about software development itself. 288 00:09:09,120 --> 00:09:09,840 Of course not. 289 00:09:09,840 --> 00:09:12,760 Tools like GitHub Copilot, which we talked about earlier. 290 00:09:12,760 --> 00:09:13,400 Yeah. 291 00:09:13,400 --> 00:09:15,840 They're already boosting developer productivity. 292 00:09:15,840 --> 00:09:17,200 Huge time saver. 293 00:09:17,200 --> 00:09:18,720 It's like having an AI assistant that 294 00:09:18,720 --> 00:09:22,400 helps you write code faster, debug more efficiently. 295 00:09:22,400 --> 00:09:25,800 It even suggests improvements, sometimes in real time. 296 00:09:25,800 --> 00:09:26,320 Incredible. 297 00:09:26,320 --> 00:09:29,560 So instead of replacing developers altogether, 298 00:09:29,560 --> 00:09:32,320 AI is actually making them even better at what they do. 299 00:09:32,320 --> 00:09:33,320 Absolutely. 300 00:09:33,320 --> 00:09:35,640 The report found companies using these tools 301 00:09:35,640 --> 00:09:39,000 see significant increases in development speed and code 302 00:09:39,000 --> 00:09:39,600 quality. 303 00:09:39,600 --> 00:09:40,320 That's amazing. 304 00:09:40,320 --> 00:09:41,600 And it doesn't stop there. 305 00:09:41,600 --> 00:09:42,400 There's more. 306 00:09:42,400 --> 00:09:45,960 AI is also making waves in, for example, sales and marketing. 307 00:09:45,960 --> 00:09:46,720 No way. 308 00:09:46,720 --> 00:09:48,880 Personalizing customer interactions, 309 00:09:48,880 --> 00:09:51,040 generating targeted content. 310 00:09:51,040 --> 00:09:52,960 How is it doing all of this? 311 00:09:52,960 --> 00:09:55,920 Even predicting which leads are most likely to convert. 312 00:09:55,920 --> 00:09:58,380 It's like having an army of virtual marketing assistants 313 00:09:58,380 --> 00:09:59,380 working around the clock. 314 00:09:59,380 --> 00:10:00,320 Something like that. 315 00:10:00,320 --> 00:10:04,340 But with all this talk of AI revolutionizing businesses, 316 00:10:04,340 --> 00:10:07,040 I have to ask, what about the costs? 317 00:10:07,040 --> 00:10:07,720 Yes. 318 00:10:07,720 --> 00:10:11,380 Implementing and scaling these solutions can't be cheap. 319 00:10:11,380 --> 00:10:12,040 You're right. 320 00:10:12,040 --> 00:10:14,000 There's no such thing as a free lunch. 321 00:10:14,000 --> 00:10:15,000 Definitely not. 322 00:10:15,000 --> 00:10:18,000 The reports vary up front about the investment required 323 00:10:18,000 --> 00:10:19,560 to make AI a success. 324 00:10:19,560 --> 00:10:21,160 OK, so break it down for us. 325 00:10:21,160 --> 00:10:24,640 Well, for starters, there's the cost of the technology itself, 326 00:10:24,640 --> 00:10:26,120 whether you're building or buying. 327 00:10:26,120 --> 00:10:26,620 Right. 328 00:10:26,620 --> 00:10:29,680 Software licenses, hardware, all the behind the scenes stuff. 329 00:10:29,680 --> 00:10:30,480 Exactly. 330 00:10:30,480 --> 00:10:32,520 Then you've got the human side of the equation. 331 00:10:32,520 --> 00:10:34,020 Right, because we're not obsolete yet. 332 00:10:34,020 --> 00:10:34,840 Not even close. 333 00:10:34,840 --> 00:10:37,920 Companies need to invest in training their workforce, 334 00:10:37,920 --> 00:10:41,360 helping them adapt to this AI-powered future. 335 00:10:41,360 --> 00:10:42,960 Because even with the smartest AI, 336 00:10:42,960 --> 00:10:45,560 you still need people who know how to use it effectively. 337 00:10:45,560 --> 00:10:46,400 Absolutely. 338 00:10:46,400 --> 00:10:49,080 That means upskilling existing employees 339 00:10:49,080 --> 00:10:52,520 and attracting new talent with those specialized skills. 340 00:10:52,520 --> 00:10:55,320 Which, as we mentioned, isn't easy in this competitive market. 341 00:10:55,320 --> 00:10:56,440 Very difficult. 342 00:10:56,440 --> 00:10:58,860 And we can't forget about those data infrastructure upgrades 343 00:10:58,860 --> 00:10:59,480 we talked about. 344 00:10:59,480 --> 00:11:00,000 Essential. 345 00:11:00,000 --> 00:11:03,000 Getting that data in tip top shape for the AI 346 00:11:03,000 --> 00:11:04,240 to work its magic. 347 00:11:04,240 --> 00:11:05,240 It all adds up. 348 00:11:05,240 --> 00:11:05,840 Really does. 349 00:11:05,840 --> 00:11:08,400 But the key takeaway here is this. 350 00:11:08,400 --> 00:11:13,360 While AI requires that significant upfront investment, 351 00:11:13,360 --> 00:11:16,760 the potential ROI can be substantial. 352 00:11:16,760 --> 00:11:17,680 That's good to know. 353 00:11:17,680 --> 00:11:20,560 But, and this is important, only if it's implemented 354 00:11:20,560 --> 00:11:22,240 strategically and thoughtfully. 355 00:11:22,240 --> 00:11:25,520 So it's not just about chasing the latest shiny AI object. 356 00:11:25,520 --> 00:11:27,920 It's about identifying the right use cases. 357 00:11:27,920 --> 00:11:28,480 Makes sense. 358 00:11:28,480 --> 00:11:30,760 And being smart about implementation. 359 00:11:30,760 --> 00:11:33,960 So no get-rich-quick schemes in the AI world. 360 00:11:33,960 --> 00:11:34,880 Definitely not. 361 00:11:34,880 --> 00:11:38,120 It's about approaching AI as a long-term investment. 362 00:11:38,120 --> 00:11:40,880 Understanding it's a journey, not a destination. 363 00:11:40,880 --> 00:11:42,000 Exactly. 364 00:11:42,000 --> 00:11:43,360 So much to think about. 365 00:11:43,360 --> 00:11:43,720 Yeah. 366 00:11:43,720 --> 00:11:45,760 I feel like we've covered a ton of ground here today. 367 00:11:45,760 --> 00:11:46,480 We really have. 368 00:11:46,480 --> 00:11:50,720 The excitement around AI, the very real challenges, the costs. 369 00:11:50,720 --> 00:11:52,640 Well, forget the ROI. 370 00:11:52,640 --> 00:11:53,560 Oh, right. 371 00:11:53,560 --> 00:11:55,960 That tantalizing potential ROI. 372 00:11:55,960 --> 00:11:56,480 Right. 373 00:11:56,480 --> 00:11:57,920 It feels like, I don't know, we're 374 00:11:57,920 --> 00:11:59,240 on the cusp of something big. 375 00:11:59,240 --> 00:11:59,760 We are. 376 00:11:59,760 --> 00:12:02,960 But for our listeners out there, what does it all actually mean? 377 00:12:02,960 --> 00:12:04,320 It's a lot to take in. 378 00:12:04,320 --> 00:12:08,360 But I think the main takeaway here is pretty clear. 379 00:12:08,360 --> 00:12:11,080 Genitive AI, it's not going anywhere. 380 00:12:11,080 --> 00:12:11,880 It's here to stay. 381 00:12:11,880 --> 00:12:14,600 This isn't some passing tech trend. 382 00:12:14,600 --> 00:12:15,120 Right. 383 00:12:15,120 --> 00:12:18,400 This is a fundamental shift in how businesses operate, 384 00:12:18,400 --> 00:12:20,040 how they think, how they work. 385 00:12:20,040 --> 00:12:22,000 It feels like one of those moments in history. 386 00:12:22,000 --> 00:12:22,480 Yeah. 387 00:12:22,480 --> 00:12:24,000 Like the arrival of the internet. 388 00:12:24,000 --> 00:12:24,560 Absolutely. 389 00:12:24,560 --> 00:12:25,560 Or smartphones. 390 00:12:25,560 --> 00:12:27,080 Things will never be the same. 391 00:12:27,080 --> 00:12:29,640 And just like with those previous revolutions, 392 00:12:29,640 --> 00:12:32,240 the companies that will thrive, they're not 393 00:12:32,240 --> 00:12:34,080 going to be the ones standing still. 394 00:12:34,080 --> 00:12:34,920 So true. 395 00:12:34,920 --> 00:12:37,320 It's all about adapting and adapting quickly. 396 00:12:37,320 --> 00:12:39,920 What does that actually look like in practice, though? 397 00:12:39,920 --> 00:12:41,520 Well, think about it this way. 398 00:12:41,520 --> 00:12:44,000 If you're a business leader listening to this, 399 00:12:44,000 --> 00:12:47,120 what are the keys to not just surviving, 400 00:12:47,120 --> 00:12:50,640 but actually really thriving in this new world? 401 00:12:50,640 --> 00:12:52,560 That's the million dollar question right there. 402 00:12:52,560 --> 00:12:54,440 I think it starts with just fostering 403 00:12:54,440 --> 00:12:59,160 a culture of constant learning, experimentation. 404 00:12:59,160 --> 00:13:00,000 Staying curious. 405 00:13:00,000 --> 00:13:00,600 Exactly. 406 00:13:00,600 --> 00:13:02,880 Because the AI landscape is constantly changing. 407 00:13:02,880 --> 00:13:03,400 Every day. 408 00:13:03,400 --> 00:13:06,600 New tools, new techniques, they're popping up all the time. 409 00:13:06,600 --> 00:13:09,640 Companies need to be willing to try new things, 410 00:13:09,640 --> 00:13:11,720 embrace a little risk. 411 00:13:11,720 --> 00:13:13,160 Be OK with failing sometimes. 412 00:13:13,160 --> 00:13:14,600 It's all part of the learning curve. 413 00:13:14,600 --> 00:13:17,280 You've got to break a few eggs to make it online. 414 00:13:17,280 --> 00:13:18,000 Exactly. 415 00:13:18,000 --> 00:13:19,000 So agility is key. 416 00:13:19,000 --> 00:13:20,520 Being able to pivot and adapt. 417 00:13:20,520 --> 00:13:22,240 Not being afraid to course correct. 418 00:13:22,240 --> 00:13:25,440 And all of that ties directly into another critical factor, 419 00:13:25,440 --> 00:13:26,200 talent. 420 00:13:26,200 --> 00:13:28,600 Finding and keeping those AI gurus. 421 00:13:28,600 --> 00:13:30,840 It's not just about technical skills, either. 422 00:13:30,840 --> 00:13:34,200 You need people who are creative, who are adaptable. 423 00:13:34,200 --> 00:13:35,480 Who can think outside the box. 424 00:13:35,480 --> 00:13:37,840 People who approach AI development 425 00:13:37,840 --> 00:13:40,200 with a strong ethical compass. 426 00:13:40,200 --> 00:13:42,240 Because AI is powerful stuff. 427 00:13:42,240 --> 00:13:43,000 It is. 428 00:13:43,000 --> 00:13:46,240 And with great power comes great responsibility. 429 00:13:46,240 --> 00:13:47,400 100%. 430 00:13:47,400 --> 00:13:50,160 Companies need to bake those ethical considerations 431 00:13:50,160 --> 00:13:52,360 into their AI strategies from day one. 432 00:13:52,360 --> 00:13:54,280 Right from the very beginning. 433 00:13:54,280 --> 00:13:55,720 It's about building trust. 434 00:13:55,720 --> 00:13:56,720 With your customers. 435 00:13:56,720 --> 00:13:58,320 With your employees. 436 00:13:58,320 --> 00:14:00,280 With society as a whole. 437 00:14:00,280 --> 00:14:02,200 And transparency is key here. 438 00:14:02,200 --> 00:14:03,840 It's not just about the bottom line. 439 00:14:03,840 --> 00:14:06,000 No, it's about doing business the right way. 440 00:14:06,000 --> 00:14:06,640 Absolutely. 441 00:14:06,640 --> 00:14:08,320 And that brings us back to data. 442 00:14:08,320 --> 00:14:09,000 Full circle. 443 00:14:09,000 --> 00:14:10,400 Which we've touched on a lot today. 444 00:14:10,400 --> 00:14:11,200 We have. 445 00:14:11,200 --> 00:14:12,960 It can't be overstated, though. 446 00:14:12,960 --> 00:14:15,560 Data is the lifeblood of AI. 447 00:14:15,560 --> 00:14:16,400 It really is. 448 00:14:16,400 --> 00:14:18,880 If you want your AI initiatives to succeed, 449 00:14:18,880 --> 00:14:21,920 you need a rock solid data strategy. 450 00:14:21,920 --> 00:14:24,440 It's that old saying, garbage in, garbage out. 451 00:14:24,440 --> 00:14:25,280 100%. 452 00:14:25,280 --> 00:14:27,560 Data governance, security, privacy. 453 00:14:27,560 --> 00:14:28,800 Those aren't just buzzwords. 454 00:14:28,800 --> 00:14:31,600 They're the foundation upon which successful AI is built. 455 00:14:31,600 --> 00:14:32,960 They really are. 456 00:14:32,960 --> 00:14:34,840 So we've talked about a lot of exciting stuff, 457 00:14:34,840 --> 00:14:39,680 but I want to end on a note of, I don't know, maybe realism. 458 00:14:39,680 --> 00:14:43,240 While that potential ROI of AI is huge, 459 00:14:43,240 --> 00:14:44,560 it's not a magic bullet. 460 00:14:44,560 --> 00:14:45,960 It's not going to happen overnight. 461 00:14:45,960 --> 00:14:49,240 It's going to take time, effort, planning to implement 462 00:14:49,240 --> 00:14:50,720 these solutions effectively. 463 00:14:50,720 --> 00:14:52,960 The companies that see those really big returns, 464 00:14:52,960 --> 00:14:54,880 they won't be the ones just trying to sprinkle 465 00:14:54,880 --> 00:14:56,520 AI magic dust on everything. 466 00:14:56,520 --> 00:14:57,880 It's about being strategic. 467 00:14:57,880 --> 00:14:59,360 Right, picking your battles. 468 00:14:59,360 --> 00:15:03,480 Identifying the right use cases, setting realistic expectations. 469 00:15:03,480 --> 00:15:06,240 So no get rich quick schemes in the AI world. 470 00:15:06,240 --> 00:15:08,000 No, none here. 471 00:15:08,000 --> 00:15:10,920 It's about approaching AI as a long-term investment. 472 00:15:10,920 --> 00:15:11,760 Playing the long game. 473 00:15:11,760 --> 00:15:15,000 Understanding that it's a journey, not a destination. 474 00:15:15,000 --> 00:15:16,560 And maybe most importantly, never 475 00:15:16,560 --> 00:15:19,000 losing sight of that human element in all of this. 476 00:15:19,000 --> 00:15:20,280 Couldn't agree more. 477 00:15:20,280 --> 00:15:22,480 AI should be a tool that empowers us. 478 00:15:22,480 --> 00:15:23,120 Absolutely. 479 00:15:23,120 --> 00:15:24,600 That helps us do our jobs better. 480 00:15:24,600 --> 00:15:25,600 Not the other way around. 481 00:15:25,600 --> 00:15:26,120 Right. 482 00:15:26,120 --> 00:15:28,360 That unlocks our creativity, not something that 483 00:15:28,360 --> 00:15:30,000 replaces us altogether. 484 00:15:30,000 --> 00:15:31,160 I love that. 485 00:15:31,160 --> 00:15:33,920 AI has the potential to make our work lives 486 00:15:33,920 --> 00:15:37,520 a more efficient, more productive, and maybe even, 487 00:15:37,520 --> 00:15:39,560 dare I say, more fulfilling. 488 00:15:39,560 --> 00:15:41,040 But it's up to us. 489 00:15:41,040 --> 00:15:42,280 It's up to us humans. 490 00:15:42,280 --> 00:15:44,360 The humans in this equation to steer it 491 00:15:44,360 --> 00:15:45,640 in the right direction. 492 00:15:45,640 --> 00:15:46,960 Could have said it better myself. 493 00:15:46,960 --> 00:15:47,480 Yeah. 494 00:15:47,480 --> 00:15:49,040 Well, on that note, I think we've 495 00:15:49,040 --> 00:15:51,560 done a pretty great job unpacking the wild world 496 00:15:51,560 --> 00:15:52,920 of AI in the enterprise. 497 00:15:52,920 --> 00:15:53,920 We did it. 498 00:15:53,920 --> 00:15:58,280 But as always, we want to leave you with something to ponder. 499 00:15:58,280 --> 00:16:01,000 We've mainly focused on large companies in this deep dive. 500 00:16:01,000 --> 00:16:01,560 We did. 501 00:16:01,560 --> 00:16:03,320 But what about the little guys? 502 00:16:03,320 --> 00:16:04,880 Could smaller businesses actually 503 00:16:04,880 --> 00:16:08,160 be in a better position to innovate and move quickly 504 00:16:08,160 --> 00:16:09,600 with AI? 505 00:16:09,600 --> 00:16:11,840 Or will they get left behind? 506 00:16:11,840 --> 00:16:24,720 Something to think about until next time.