1 00:00:00,000 --> 00:00:03,280 Ever wondered how AI can transform business strategy? 2 00:00:03,280 --> 00:00:05,760 In this episode, we dive into the fascinating world 3 00:00:05,760 --> 00:00:08,120 of AI-powered SWOT analysis. 4 00:00:08,120 --> 00:00:12,580 So we are tackling an old problem using a new approach. 5 00:00:13,720 --> 00:00:16,480 Welcome to Data, AI, Productivity, and Business 6 00:00:16,480 --> 00:00:18,520 with a little personality broadcast. 7 00:00:18,520 --> 00:00:20,760 It's a show where we explore the cutting edge 8 00:00:20,760 --> 00:00:24,400 of business strategy, technology, data, 9 00:00:24,400 --> 00:00:26,160 and everything in between. 10 00:00:26,160 --> 00:00:28,440 I'm your host, Mukundan Sankar. 11 00:00:28,440 --> 00:00:30,240 I'm an experienced data professional 12 00:00:30,240 --> 00:00:32,800 who loves researching about AI 13 00:00:32,800 --> 00:00:35,720 and demonstrating how they can be practically applied 14 00:00:35,720 --> 00:00:37,480 to our everyday world. 15 00:00:37,480 --> 00:00:39,920 If you ever wondered how AI is changing the game 16 00:00:39,920 --> 00:00:43,960 for companies or how to leverage data for your own use 17 00:00:43,960 --> 00:00:46,720 in general to make smarter decision-making, 18 00:00:46,720 --> 00:00:49,080 you're in the right place, my friend. 19 00:00:49,080 --> 00:00:50,680 Today, we're diving into something 20 00:00:50,680 --> 00:00:52,400 that's shaking up the business world, 21 00:00:52,400 --> 00:00:54,960 which is AI-powered SWOT analysis. 22 00:00:54,960 --> 00:00:57,360 We'll explore how we can use AI 23 00:00:57,360 --> 00:01:00,080 to break down the top-performing companies 24 00:01:00,080 --> 00:01:03,560 by their strengths, weaknesses, opportunities, and threats, 25 00:01:03,560 --> 00:01:05,400 which is what SWOT analysis is. 26 00:01:06,520 --> 00:01:09,640 And we want to be able to do this faster 27 00:01:09,640 --> 00:01:11,800 and more accurately than ever before. 28 00:01:13,520 --> 00:01:16,280 So we also got some exciting real-world examples 29 00:01:16,280 --> 00:01:18,720 from companies like Google and Meta 30 00:01:18,720 --> 00:01:21,900 that'll show you how exactly this works in action. 31 00:01:21,900 --> 00:01:24,600 So whether you're an entrepreneur, business leader, 32 00:01:24,600 --> 00:01:29,600 or just someone who's just curious to know more about AI, 33 00:01:30,160 --> 00:01:33,160 stick around because this episode is packed with insights 34 00:01:33,160 --> 00:01:35,440 that can help you get ahead of the curve. 35 00:01:36,960 --> 00:01:40,840 So I don't know about you, but when I was in school, 36 00:01:40,840 --> 00:01:44,600 I had taken a business school course, 37 00:01:44,600 --> 00:01:48,040 which was about policy and strategy. 38 00:01:48,040 --> 00:01:50,840 And specifically, they were involved about companies 39 00:01:51,920 --> 00:01:54,120 and what policies they've undertaken, 40 00:01:54,120 --> 00:01:55,360 what was the strategy. 41 00:01:56,400 --> 00:01:59,160 So I had to research about companies a lot 42 00:01:59,160 --> 00:02:00,300 during my time there. 43 00:02:01,580 --> 00:02:04,580 So I had to research about all the top companies. 44 00:02:04,580 --> 00:02:07,880 And one of the kind of analysis that I did 45 00:02:07,880 --> 00:02:10,960 during one of my assignments was the SWOT analysis. 46 00:02:10,960 --> 00:02:14,400 And that brings me to today's episode. 47 00:02:14,400 --> 00:02:17,080 So what analysis basically is 48 00:02:17,080 --> 00:02:19,720 you're looking at strengths of the company, 49 00:02:19,720 --> 00:02:22,400 what are the opportunities that the company has, 50 00:02:22,400 --> 00:02:25,560 what are its weaknesses and what are its 51 00:02:25,560 --> 00:02:27,920 the potential threats it faces. 52 00:02:27,920 --> 00:02:30,560 So it helps you look at the company at an overview. 53 00:02:31,640 --> 00:02:34,960 And that is something that will help you 54 00:02:34,960 --> 00:02:36,880 to understand the company better. 55 00:02:38,200 --> 00:02:40,480 So I've also written a blog about it, 56 00:02:40,480 --> 00:02:42,200 which I'll link in the show notes 57 00:02:42,200 --> 00:02:44,240 of how to do SWOT analysis using AI. 58 00:02:44,240 --> 00:02:45,560 So that's my blog. 59 00:02:45,560 --> 00:02:48,760 But today, especially I will be exploring how AI 60 00:02:48,760 --> 00:02:53,760 specifically 3.5 Turbo GPT can help 61 00:02:54,640 --> 00:02:57,600 in analyzing companies in the S&P 500 space 62 00:02:58,600 --> 00:03:01,520 and deliver those valuable strategic insights 63 00:03:01,520 --> 00:03:03,360 faster than ever before. 64 00:03:03,360 --> 00:03:05,360 It's mind blowing to see how this technology 65 00:03:05,360 --> 00:03:08,320 is shaking up traditional SWOT analysis. 66 00:03:08,320 --> 00:03:12,020 So one of the reasons also doing this is, 67 00:03:13,640 --> 00:03:18,220 back in my time is I had to spend like a couple of days 68 00:03:18,220 --> 00:03:19,680 doing this kind of work. 69 00:03:20,640 --> 00:03:22,220 Like researching about the companies, 70 00:03:22,220 --> 00:03:24,920 finding the strengths, weaknesses, opportunities and threats. 71 00:03:24,920 --> 00:03:27,200 It takes a while to find that information 72 00:03:28,080 --> 00:03:29,960 using like a regular Google search, 73 00:03:29,960 --> 00:03:33,300 or whatever other kind of search methods you used. 74 00:03:34,880 --> 00:03:36,680 So, or you have to watch YouTube videos. 75 00:03:36,680 --> 00:03:38,960 So as a combination of everything that you're doing, 76 00:03:38,960 --> 00:03:40,960 and it takes a while to do that research. 77 00:03:42,120 --> 00:03:46,800 So what I've gathered with my recent knowledge 78 00:03:46,800 --> 00:03:50,680 and my research with AI is that, 79 00:03:50,680 --> 00:03:54,000 well, let me apply AI to other fields. 80 00:03:54,000 --> 00:03:56,080 And I just keep thinking of more and more areas 81 00:03:56,080 --> 00:03:57,760 where I can apply AI. 82 00:03:57,760 --> 00:04:00,680 And the other day, something like SWOT analysis 83 00:04:00,680 --> 00:04:03,840 just struck my mind. 84 00:04:03,840 --> 00:04:08,560 So I was just thinking, well, what new project can I do? 85 00:04:08,560 --> 00:04:11,800 So SWOT analysis was something that came in my mind. 86 00:04:11,800 --> 00:04:16,800 And with AI, so what kind of AI large language model 87 00:04:18,720 --> 00:04:19,720 can I apply, right? 88 00:04:19,720 --> 00:04:23,800 And GPT 3.5 is relatively inexpensive. 89 00:04:23,800 --> 00:04:27,560 Then like the latest one, which is GPT 4 and 4.0. 90 00:04:29,040 --> 00:04:31,720 So those ones would be more expensive to run. 91 00:04:31,720 --> 00:04:34,400 So GPT 3.5 gives me the right amount of insights 92 00:04:34,400 --> 00:04:35,240 that I need. 93 00:04:36,200 --> 00:04:38,120 And it also does this quicker. 94 00:04:38,120 --> 00:04:41,200 Yes, I'm sure GPT 4.0 is quicker. 95 00:04:41,200 --> 00:04:45,760 But I mean, I also wanted to just get it something 96 00:04:45,760 --> 00:04:47,040 cost efficient, right? 97 00:04:47,040 --> 00:04:49,720 Like this is just something I like to do on the side. 98 00:04:49,720 --> 00:04:51,320 So this is for me. 99 00:04:51,320 --> 00:04:53,720 And if you're listening, 100 00:04:53,720 --> 00:04:55,720 you can obviously experiment around it. 101 00:04:57,480 --> 00:05:02,120 If AI excites you, that's awesome. 102 00:05:02,120 --> 00:05:04,560 I look forward to seeing your projects. 103 00:05:04,560 --> 00:05:07,120 So basically, yes, you can use GPT 104 00:05:07,120 --> 00:05:10,120 to analyze this massive amount of information. 105 00:05:10,120 --> 00:05:13,440 So what's happening essentially in my project 106 00:05:13,440 --> 00:05:16,880 is that you have these different companies. 107 00:05:16,880 --> 00:05:18,720 And in my particular use case, 108 00:05:18,720 --> 00:05:23,720 I am comparing two companies in the SMP 500 space. 109 00:05:24,040 --> 00:05:25,600 Why SMP 500? 110 00:05:25,600 --> 00:05:29,800 It's because when these are the top 500 companies, 111 00:05:29,800 --> 00:05:31,360 the standard and poor index, right? 112 00:05:31,360 --> 00:05:35,760 So that's something which would give understanding 113 00:05:35,760 --> 00:05:37,160 of the top performing companies. 114 00:05:37,160 --> 00:05:40,200 So that's why I chose these two. 115 00:05:40,200 --> 00:05:43,280 I mean, this space. 116 00:05:43,280 --> 00:05:46,720 And looking at two companies specifically, 117 00:05:46,720 --> 00:05:48,560 it gives a nice comparison. 118 00:05:49,640 --> 00:05:52,600 So in my use case, I'm just like comparing 119 00:05:52,600 --> 00:05:54,720 strengths, weaknesses, opportunities and threats, 120 00:05:54,720 --> 00:05:58,640 but it's not line by line comparison. 121 00:05:59,560 --> 00:06:01,800 You can obviously ask AI to do that. 122 00:06:01,800 --> 00:06:05,280 So AI is very powerful and capable to do 123 00:06:05,280 --> 00:06:08,680 line by line comparison between the two companies. 124 00:06:08,680 --> 00:06:12,840 So in my use case, I've used Google and Meta 125 00:06:12,840 --> 00:06:15,360 as the two companies I wanted to compare. 126 00:06:15,360 --> 00:06:18,800 So I got the strengths of Google, 127 00:06:18,800 --> 00:06:20,560 the weaknesses, opportunities, threats, 128 00:06:20,560 --> 00:06:23,040 and same thing for Meta. 129 00:06:23,040 --> 00:06:26,280 So basically it helped me understand 130 00:06:26,280 --> 00:06:29,680 what could be strengths and the weaknesses 131 00:06:29,680 --> 00:06:32,760 was some of the interesting insights that came from it. 132 00:06:32,760 --> 00:06:35,440 And Facebook was data privacy. 133 00:06:35,440 --> 00:06:38,720 We all know the whole Cambridge Analytica thing 134 00:06:38,720 --> 00:06:40,240 which happened in 2016. 135 00:06:42,120 --> 00:06:44,480 Yeah, I mean, I'm sure the privacy took a hit. 136 00:06:46,840 --> 00:06:49,800 Something similar to Google as well, 137 00:06:49,800 --> 00:06:51,680 like the regulatory standards, 138 00:06:51,680 --> 00:06:55,240 a lot of things happening with regulations these days. 139 00:06:55,240 --> 00:07:00,240 So Google is, I mean, everybody's, 140 00:07:00,600 --> 00:07:02,320 all these big companies, we don't know 141 00:07:02,320 --> 00:07:03,800 what they're tracking. 142 00:07:03,800 --> 00:07:07,480 So that's something we need to be mindful of. 143 00:07:07,480 --> 00:07:09,800 So I mean, just like that's something 144 00:07:09,800 --> 00:07:11,920 the SWOT analysis gives you, right? 145 00:07:11,920 --> 00:07:14,240 It gives you that understanding of the company 146 00:07:14,240 --> 00:07:15,240 at a higher level. 147 00:07:18,320 --> 00:07:22,640 So my application, which I had pasted screenshots 148 00:07:22,640 --> 00:07:26,520 for in my blog, you can see that in the show notes. 149 00:07:27,680 --> 00:07:30,480 So you're able to understand that what kind of insights 150 00:07:30,480 --> 00:07:31,560 are being provided. 151 00:07:31,560 --> 00:07:33,280 So yeah, in addition to the SWOT, 152 00:07:33,280 --> 00:07:35,280 there's also something called as insights, 153 00:07:35,280 --> 00:07:39,360 additional insights, which I gave for each of the companies. 154 00:07:39,360 --> 00:07:42,480 So that will also tell you like what kind of upcoming things 155 00:07:42,480 --> 00:07:45,560 you need to watch out for, which can go in the, 156 00:07:45,560 --> 00:07:50,680 each of the, in any of the SWOT blog. 157 00:07:50,680 --> 00:07:55,680 So what I had used for this project was using Python 158 00:07:56,720 --> 00:07:59,680 programming and there's like a front end library 159 00:07:59,680 --> 00:08:01,000 called Streamlit. 160 00:08:01,000 --> 00:08:02,720 You can obviously use Flask. 161 00:08:02,720 --> 00:08:04,240 So that's something up to you. 162 00:08:05,920 --> 00:08:07,840 But on the more AI side, 163 00:08:09,360 --> 00:08:14,360 ask GPT specifically like to build a data model around this, 164 00:08:16,360 --> 00:08:20,240 basically asking like, can you do a strength comparison? 165 00:08:20,240 --> 00:08:22,040 Can you do weaknesses? 166 00:08:22,040 --> 00:08:26,160 Can you do, can you get opportunity and threats? 167 00:08:26,160 --> 00:08:29,040 So that would give you like the complete number, 168 00:08:29,040 --> 00:08:30,240 the complete picture essentially. 169 00:08:30,240 --> 00:08:35,240 And what was most exciting about this project 170 00:08:36,240 --> 00:08:40,000 was how we can use AI to do something 171 00:08:40,000 --> 00:08:44,600 which we were doing traditionally by like random, 172 00:08:44,600 --> 00:08:46,880 by just like research, right? 173 00:08:46,880 --> 00:08:50,480 Like by doing a lot of Google searches, 174 00:08:50,480 --> 00:08:52,280 by doing a lot of YouTube. 175 00:08:53,160 --> 00:08:55,560 That's what I used to do, but like, 176 00:08:55,560 --> 00:08:56,560 anything that you would do. 177 00:08:56,560 --> 00:09:00,360 So with that all was really time consuming 178 00:09:00,360 --> 00:09:03,360 and AI is really making all of this really efficient. 179 00:09:04,280 --> 00:09:07,800 So the response time for this was, I think, 180 00:09:07,800 --> 00:09:09,560 just maybe a few seconds, I would say, 181 00:09:09,560 --> 00:09:11,720 maybe five or 10 seconds. 182 00:09:11,720 --> 00:09:16,720 And if you're into that, like if you're into speed versus, 183 00:09:18,680 --> 00:09:21,720 you know, a deeper research, 184 00:09:21,720 --> 00:09:23,000 which obviously means more accuracy. 185 00:09:23,000 --> 00:09:26,960 I think the speed was, and this model is pretty accurate, 186 00:09:26,960 --> 00:09:27,800 I believe. 187 00:09:29,040 --> 00:09:32,400 You can obviously use more modern 188 00:09:32,400 --> 00:09:36,160 and more faster last language models. 189 00:09:36,160 --> 00:09:39,400 That's up to you, but I think this one was fine 190 00:09:39,400 --> 00:09:40,560 for my use case. 191 00:09:42,480 --> 00:09:44,200 So I would encourage you to go ahead 192 00:09:44,200 --> 00:09:46,080 and try something like this as well, 193 00:09:47,040 --> 00:09:51,240 especially if you're in maybe like in your company 194 00:09:51,240 --> 00:09:55,400 and you do a SWOT analysis to understand your competitors. 195 00:09:56,560 --> 00:10:01,440 And it would benefit you to maybe use a tool like this. 196 00:10:01,440 --> 00:10:06,440 And also, if you would like me to actually make this live 197 00:10:06,760 --> 00:10:09,280 versus you building it out yourself, 198 00:10:09,280 --> 00:10:10,680 please let me know. 199 00:10:10,680 --> 00:10:14,040 Feel free to just respond to me on my Subscribe channel 200 00:10:14,040 --> 00:10:17,200 or podcast, wherever you find it, 201 00:10:17,200 --> 00:10:19,160 Apple Podcasts, Spotify. 202 00:10:19,160 --> 00:10:21,960 So I'm available, just reach out to me in the comment section 203 00:10:21,960 --> 00:10:25,280 and I'm happy to help make this live. 204 00:10:26,800 --> 00:10:30,760 And yeah, I just think using AI for different applications 205 00:10:30,760 --> 00:10:32,840 is a total game changer. 206 00:10:34,800 --> 00:10:36,560 So this was just SWOT analysis, 207 00:10:36,560 --> 00:10:39,040 but everything and anything under the sun 208 00:10:39,040 --> 00:10:40,880 can now be under AI. 209 00:10:40,880 --> 00:10:42,360 Obviously there's a trust issue 210 00:10:42,360 --> 00:10:46,160 and ethics and privacy issue, but that's separate. 211 00:10:46,160 --> 00:10:51,160 But for me, AI is something that I'm completely embracing. 212 00:10:53,160 --> 00:10:57,600 I just want our future to be completely shaped by it. 213 00:10:57,600 --> 00:10:59,440 Thank you for this. 214 00:10:59,440 --> 00:11:01,600 Again, that's a wrap for today. 215 00:11:01,600 --> 00:11:06,440 I look forward to seeing more of you in the next episode 216 00:11:06,440 --> 00:11:08,640 and thanks for tuning in and until next time, 217 00:11:08,640 --> 00:11:09,960 keep learning, keep growing, 218 00:11:09,960 --> 00:11:12,760 and keep pushing the boundaries of what's possible. 219 00:11:12,760 --> 00:11:16,440 Thanks everyone. 220 00:11:16,440 --> 00:11:20,520 If you like this episode, please subscribe to my channel. 221 00:11:20,520 --> 00:11:25,000 It means a lot to build out the next episodes, 222 00:11:25,000 --> 00:11:26,440 to create more content for you 223 00:11:26,440 --> 00:11:31,440 and I can definitely come up with more content. 224 00:11:31,440 --> 00:11:33,360 All I need is just your support at this time. 225 00:11:33,360 --> 00:11:35,160 Thanks so much for tuning in 226 00:11:35,160 --> 00:11:37,720 and I look forward to seeing you in the next one. 227 00:11:37,720 --> 00:11:42,720 Thank you.