1 00:00:00,840 --> 00:00:03,800 Speaker 1: If you're a leader who's rolled out an AI tool 2 00:00:03,920 --> 00:00:07,840 Speaker 1: like co pilot or chat GPT and wonder Light hasn't 3 00:00:07,920 --> 00:00:11,360 Speaker 1: led to the big productivity gains you were promised, or worse, 4 00:00:11,480 --> 00:00:15,000 Speaker 1: it feels like you've created more mess. You are not 5 00:00:15,360 --> 00:00:19,079 Speaker 1: alone because on paper, this stuff should be easy. Give 6 00:00:19,120 --> 00:00:22,239 Speaker 1: people access, maybe run a short demo and let them 7 00:00:22,239 --> 00:00:26,000 Speaker 1: figure it out. But in reality that approach often leads 8 00:00:26,040 --> 00:00:30,920 Speaker 1: to confusion, resistance, and a lot of wasted time. And 9 00:00:31,120 --> 00:00:34,479 Speaker 1: it's not because your people are unwilling or slow to adapt. 10 00:00:34,720 --> 00:00:38,840 Speaker 1: It's because AI adoption isn't really a tech problem, it's 11 00:00:38,880 --> 00:00:42,720 Speaker 1: a people one. So in this episode, Neo and I 12 00:00:43,080 --> 00:00:47,479 Speaker 1: unpack the single most important question every leader should be 13 00:00:47,479 --> 00:00:50,800 Speaker 1: asking about AI and what to do once you've asked it. 14 00:00:51,360 --> 00:00:54,840 Speaker 1: We're going to talk through why giving people licenses without 15 00:00:54,880 --> 00:01:00,000 Speaker 1: support backfires, how poor AI use can actually reduce productivity, 16 00:01:00,520 --> 00:01:04,399 Speaker 1: and three things leaders need to get right from day one. 17 00:01:05,200 --> 00:01:07,240 Speaker 1: By the end, you're going to have a much clearer 18 00:01:07,280 --> 00:01:11,199 Speaker 1: sense of how to bring AI into your organization without 19 00:01:11,319 --> 00:01:22,000 Speaker 1: losing trust, time, or momentum. Welcome to how IAI with Me, 20 00:01:22,160 --> 00:01:26,440 Speaker 1: Doctor Amantha Imba and Neo Applan, head of Inventium, AI. 21 00:01:27,040 --> 00:01:30,119 Speaker 1: Each episode we share one practical way to use AI 22 00:01:30,280 --> 00:01:34,440 Speaker 1: better at work and in life. No fluff, no tech jargon, 23 00:01:34,800 --> 00:01:38,399 Speaker 1: just things you can use straight away. So, Neo at 24 00:01:38,520 --> 00:01:46,480 Speaker 1: Inventium AI, we work with so many different teams and 25 00:01:46,959 --> 00:01:49,840 Speaker 1: we've probably worked with hundreds and hundreds of different leaders 26 00:01:49,880 --> 00:01:54,720 Speaker 1: at this point in time, and they have got a 27 00:01:54,800 --> 00:01:58,040 Speaker 1: lot of questions for us. But today we want to 28 00:01:58,080 --> 00:02:02,120 Speaker 1: talk about the one question that we think every leader 29 00:02:02,280 --> 00:02:05,880 Speaker 1: should be asking about AI. So tell me, Neo, what 30 00:02:06,040 --> 00:02:08,720 Speaker 1: is this one question that every single leader should ask 31 00:02:08,760 --> 00:02:09,480 Speaker 1: about AI. 32 00:02:10,200 --> 00:02:13,720 Speaker 2: It's about how can I help my people be ready 33 00:02:13,720 --> 00:02:17,720 Speaker 2: for AI? Because it's a people problem, not a technology problem. 34 00:02:17,760 --> 00:02:20,800 Speaker 2: We found this every single step along the way, where 35 00:02:21,000 --> 00:02:23,880 Speaker 2: simply giving someone here's an AI, go for it. You've 36 00:02:23,919 --> 00:02:27,920 Speaker 2: got CHPT, you've got clawed, you've got Gemini go is 37 00:02:27,960 --> 00:02:30,840 Speaker 2: actually a recipe for disaster. They've shown this in so 38 00:02:30,919 --> 00:02:35,920 Speaker 2: many studies of implementations globally. There've been cases where people 39 00:02:35,919 --> 00:02:39,919 Speaker 2: have effectively demigrated, which is the staff have risen up 40 00:02:39,960 --> 00:02:43,680 Speaker 2: and said, take this damn thing off my computer now. 41 00:02:44,400 --> 00:02:47,359 Speaker 2: And so that's an expensive problem to have. It's an 42 00:02:47,360 --> 00:02:50,040 Speaker 2: expensive mistake to have, and not just that you've got 43 00:02:50,040 --> 00:02:52,760 Speaker 2: a whole bunch of staff members who are then disenfranchised, 44 00:02:52,760 --> 00:02:54,799 Speaker 2: don't feel like they we listen to and things like that. 45 00:02:54,840 --> 00:02:57,440 Speaker 2: So this is very much a people dimension. So how 46 00:02:57,440 --> 00:02:59,519 Speaker 2: do we get our people ready for AI? 47 00:03:01,200 --> 00:03:06,360 Speaker 1: I am personally surprised at how many organizations we encounter 48 00:03:06,880 --> 00:03:11,160 Speaker 1: that have given people a paid license for whatever their 49 00:03:11,160 --> 00:03:16,120 Speaker 1: AI tool of choice is and they haven't done anything 50 00:03:16,320 --> 00:03:20,080 Speaker 1: in terms of building capability. They think, oh, it's just 51 00:03:20,200 --> 00:03:23,080 Speaker 1: like Google. You just you know, speak to it in 52 00:03:23,120 --> 00:03:28,919 Speaker 1: your caveman, you know, best restaurants, Melbourne speak, and it's 53 00:03:28,960 --> 00:03:30,760 Speaker 1: just intuitive how to get the best out of it. 54 00:03:31,080 --> 00:03:33,920 Speaker 1: But for you and I I think, because we're deep 55 00:03:33,919 --> 00:03:37,480 Speaker 1: in this space and we have been using it every day, 56 00:03:37,560 --> 00:03:41,920 Speaker 1: multiple times a day, for gosh like about three years now, 57 00:03:43,240 --> 00:03:46,600 Speaker 1: to get the best out of it, it's not actually intuitive. 58 00:03:46,960 --> 00:03:50,240 Speaker 1: So what are some of the things that leaders can 59 00:03:50,480 --> 00:03:54,800 Speaker 1: practically do to set their teams up for success assuming 60 00:03:55,080 --> 00:03:59,120 Speaker 1: they have just implemented or rolled out a paid version 61 00:03:59,480 --> 00:04:01,880 Speaker 1: paid licence since the it's a their AI tool of choice, 62 00:04:01,920 --> 00:04:04,440 Speaker 1: or they're thinking about doing that in the coming months. 63 00:04:05,000 --> 00:04:08,800 Speaker 2: First off, telling people why why you will think that 64 00:04:08,840 --> 00:04:11,120 Speaker 2: AI is a good thing. Now, we found the most 65 00:04:11,120 --> 00:04:14,760 Speaker 2: successful organizations give the why, not that we're going to 66 00:04:14,760 --> 00:04:18,040 Speaker 2: replace people and get bitter people in their jobs. That's 67 00:04:18,080 --> 00:04:22,599 Speaker 2: going to make people scared. The why often we've found 68 00:04:22,600 --> 00:04:26,720 Speaker 2: from organizations is we've got people who are already overloaded. 69 00:04:27,320 --> 00:04:29,360 Speaker 2: They're already feeling like they've got to work seventy out 70 00:04:29,400 --> 00:04:31,440 Speaker 2: of hours a week. How do we get people so 71 00:04:31,480 --> 00:04:34,279 Speaker 2: they can reliably do their forty hours a week to 72 00:04:34,320 --> 00:04:36,520 Speaker 2: be able to get more done and also to do 73 00:04:36,600 --> 00:04:39,600 Speaker 2: more important things. So you're doing a ministrivia, I'm doing 74 00:04:39,600 --> 00:04:41,720 Speaker 2: everyone's doing a minister via. Why don't we get AI 75 00:04:41,800 --> 00:04:43,520 Speaker 2: to do some of that in misterrivia so we can 76 00:04:43,520 --> 00:04:46,719 Speaker 2: focus on the important stuff. The leaders that I've spoken to, 77 00:04:47,240 --> 00:04:49,200 Speaker 2: most of them recognize that this is the thing that 78 00:04:49,360 --> 00:04:52,600 Speaker 2: really is going to drive their business forward, rather than 79 00:04:52,920 --> 00:04:56,920 Speaker 2: get AI to replace people, because particularly with these kinds 80 00:04:56,960 --> 00:04:59,760 Speaker 2: of AI, this is very much a knowledge worker AI. 81 00:05:00,040 --> 00:05:03,320 Speaker 2: It's plucked into your applications, your emails and things like 82 00:05:03,360 --> 00:05:05,719 Speaker 2: that to help you to do your day. Because, of course, 83 00:05:05,760 --> 00:05:08,320 Speaker 2: the other AI, which is like full on automation and 84 00:05:09,240 --> 00:05:13,479 Speaker 2: things like that, so that's a completely different type of 85 00:05:13,480 --> 00:05:16,120 Speaker 2: AI and also different kind of human question. But getting 86 00:05:16,120 --> 00:05:20,000 Speaker 2: copilot on your desktop very much a human problem. So 87 00:05:20,400 --> 00:05:23,080 Speaker 2: saying the why and really making sure that people understand that, 88 00:05:23,200 --> 00:05:26,960 Speaker 2: I mean understand viscerally understand, like we actually care about 89 00:05:26,960 --> 00:05:30,080 Speaker 2: our staff, we care about your job, and you're doing 90 00:05:30,080 --> 00:05:33,480 Speaker 2: a lot of you know, standard stuff that could be 91 00:05:33,520 --> 00:05:37,000 Speaker 2: done better by AI. Let's get you doing the smarter things. 92 00:05:37,920 --> 00:05:40,039 Speaker 2: So yeah, when that's actually framed as a people problem, 93 00:05:40,279 --> 00:05:43,760 Speaker 2: then people do resonate and they go, yes, this is good. 94 00:05:43,839 --> 00:05:47,400 Speaker 2: I am actually on board with this. The other thing is, 95 00:05:47,839 --> 00:05:49,720 Speaker 2: don't just give the tools and say that's good enough. 96 00:05:50,240 --> 00:05:54,280 Speaker 2: We've had quite a few teams who when it's got 97 00:05:54,320 --> 00:05:58,320 Speaker 2: a wonderful interface, this chatbot gonna interface where there's a 98 00:05:58,360 --> 00:06:01,599 Speaker 2: prompt spot and a go button and a plus buttoned 99 00:06:01,640 --> 00:06:04,080 Speaker 2: upload a couple of files, like, it's wonderful and simple, 100 00:06:04,240 --> 00:06:06,160 Speaker 2: but it doesn't tell you how it's actually going to 101 00:06:06,240 --> 00:06:09,560 Speaker 2: work and how you should work with it. I'm sure 102 00:06:09,560 --> 00:06:12,640 Speaker 2: you've heard of people who have a microwave, but all 103 00:06:12,640 --> 00:06:15,480 Speaker 2: they do in the microwave is they use it for defrosting, 104 00:06:15,640 --> 00:06:19,040 Speaker 2: or people with expensive thermo mixers who only make smoothies 105 00:06:19,080 --> 00:06:21,279 Speaker 2: out of it, and things like that. Ais are just 106 00:06:21,400 --> 00:06:23,279 Speaker 2: the same. There are quite a few people out there 107 00:06:23,360 --> 00:06:25,400 Speaker 2: who know two or three things to do an AI 108 00:06:25,440 --> 00:06:27,599 Speaker 2: and that continue doing those two or three things. But 109 00:06:27,640 --> 00:06:30,520 Speaker 2: it's onthing touching the surface of what it can achieve. 110 00:06:31,440 --> 00:06:34,440 Speaker 1: I find that the most common thing I hear from 111 00:06:34,680 --> 00:06:37,680 Speaker 1: leaders that I meet with is you know, people are 112 00:06:37,760 --> 00:06:41,160 Speaker 1: using it for their emails and stuff, and I just think, 113 00:06:41,839 --> 00:06:45,800 Speaker 1: oh gosh, like that's that's not good. And then I 114 00:06:45,880 --> 00:06:50,640 Speaker 1: also find that it can also actually reduce productivity when 115 00:06:50,720 --> 00:06:54,120 Speaker 1: people are doing that, because inevitably they're just putting in, oh, 116 00:06:54,240 --> 00:06:57,320 Speaker 1: communicate this these three dot points, and then they'll get 117 00:06:57,360 --> 00:07:01,080 Speaker 1: a really lengthy and wordy email that is clearly written 118 00:07:01,120 --> 00:07:05,120 Speaker 1: by AI, and then the recipe recipient or the recipients 119 00:07:05,640 --> 00:07:08,880 Speaker 1: then have to waste their time reading a potentially quite 120 00:07:08,880 --> 00:07:11,640 Speaker 1: a long email just to get the three bullet points 121 00:07:11,680 --> 00:07:14,720 Speaker 1: that were originally put in. So, I mean, it's just 122 00:07:14,760 --> 00:07:17,960 Speaker 1: another example of how if people are not trained in AI, 123 00:07:18,560 --> 00:07:24,040 Speaker 1: you're actually going to pretty much kill off any productivity 124 00:07:24,160 --> 00:07:27,080 Speaker 1: benefit that you think AI is going to give you. 125 00:07:27,840 --> 00:07:31,800 Speaker 2: And the other problem with AI being overused, particularly with productivity, 126 00:07:31,920 --> 00:07:33,880 Speaker 2: is if I just get my AI to write three 127 00:07:33,920 --> 00:07:35,600 Speaker 2: dot points and it writes a big document or a 128 00:07:35,600 --> 00:07:38,240 Speaker 2: big email, you'll then use AI to summarize it, and 129 00:07:38,280 --> 00:07:42,040 Speaker 2: so then it's going to be organizational Chinese whispers where 130 00:07:42,280 --> 00:07:45,000 Speaker 2: no one's really going to understand what everyone's talking about, 131 00:07:45,040 --> 00:07:48,280 Speaker 2: and so you will not get productivity with that. So 132 00:07:48,760 --> 00:07:50,840 Speaker 2: then the next part is showing people how they can 133 00:07:50,880 --> 00:07:53,600 Speaker 2: actually use AI in a productive way. So how it 134 00:07:53,640 --> 00:07:56,080 Speaker 2: can help you to ID eight, how to be more creative, 135 00:07:56,200 --> 00:07:58,640 Speaker 2: how you can get it to review your work and 136 00:07:58,680 --> 00:08:03,400 Speaker 2: make your work better, How you can help it with 137 00:08:03,440 --> 00:08:06,640 Speaker 2: your problem solving, or as we've talked about before, organize 138 00:08:06,680 --> 00:08:09,000 Speaker 2: and plan your day and break down your tasks and 139 00:08:09,040 --> 00:08:11,520 Speaker 2: things like that. So using there's a buddy and an 140 00:08:11,600 --> 00:08:15,240 Speaker 2: expert rather than just your email running slave is so 141 00:08:15,520 --> 00:08:18,960 Speaker 2: much more productive organizationally. But people need to be shown this. 142 00:08:20,680 --> 00:08:23,960 Speaker 1: What else deleters need to do to get their teams 143 00:08:24,040 --> 00:08:25,640 Speaker 1: ready for AI? 144 00:08:26,800 --> 00:08:32,360 Speaker 2: One is technology, So just simply buying take copile it 145 00:08:32,400 --> 00:08:35,280 Speaker 2: as an example, which a lot of companies do. Buying 146 00:08:35,280 --> 00:08:37,720 Speaker 2: copelet throwing it in into saying you go and now 147 00:08:38,200 --> 00:08:40,920 Speaker 2: maybe some training, which is great. Absolutely yes, do the training, 148 00:08:41,960 --> 00:08:44,800 Speaker 2: but technology wise is not alone, particularly if you're going 149 00:08:44,840 --> 00:08:47,600 Speaker 2: to plug it into your systems, your email and your data. 150 00:08:48,160 --> 00:08:52,400 Speaker 2: So if you are going to allow your AI to 151 00:08:52,440 --> 00:08:55,720 Speaker 2: be able to search documents, you get massive productivity benefits. 152 00:08:55,800 --> 00:08:57,800 Speaker 2: So I can then say, hey, help me with these 153 00:08:57,800 --> 00:09:00,160 Speaker 2: three documents, will help me find that thing or tell 154 00:09:00,200 --> 00:09:03,120 Speaker 2: me about everything we've done with client X. So power 155 00:09:03,240 --> 00:09:06,560 Speaker 2: is amazing there. However, you don't lock some things away. 156 00:09:06,880 --> 00:09:09,400 Speaker 2: I could say how much is Amantha being paid? Or 157 00:09:10,000 --> 00:09:12,880 Speaker 2: where was the last HR problem last month? And things 158 00:09:13,160 --> 00:09:16,400 Speaker 2: Things you don't want to go public can go public 159 00:09:16,520 --> 00:09:19,640 Speaker 2: in all least within your organization. So when you get 160 00:09:19,640 --> 00:09:23,200 Speaker 2: to place these organizational tools in, make sure that your 161 00:09:23,320 --> 00:09:26,200 Speaker 2: data people have had a look through it and we're 162 00:09:26,360 --> 00:09:30,959 Speaker 2: protecting things like staff data, company data, customer data, privacy 163 00:09:31,000 --> 00:09:33,160 Speaker 2: and all those kind of things in the way that 164 00:09:33,200 --> 00:09:35,679 Speaker 2: we need to as for our company and policies. 165 00:09:36,760 --> 00:09:40,839 Speaker 1: So just a summarize for leaders, you really need to 166 00:09:40,880 --> 00:09:43,080 Speaker 1: be thinking about what do I need to do to 167 00:09:43,120 --> 00:09:46,480 Speaker 1: help my team be AI ready. We've talked about three 168 00:09:46,600 --> 00:09:50,839 Speaker 1: main things. Firstly, the why, make sure you and your 169 00:09:50,880 --> 00:09:55,679 Speaker 1: people are really clear on the why you are doing this. Secondly, 170 00:09:55,960 --> 00:09:59,160 Speaker 1: make sure you are building capability AI and getting the 171 00:09:59,240 --> 00:10:02,400 Speaker 1: best out of to augment your thinking and save hours 172 00:10:02,440 --> 00:10:06,240 Speaker 1: as well. On the productivity front, it's not necessarily intuitive 173 00:10:06,280 --> 00:10:09,880 Speaker 1: and in fact looks you can do some things, but 174 00:10:10,960 --> 00:10:14,080 Speaker 1: often when people just use it out of the box, 175 00:10:14,200 --> 00:10:17,760 Speaker 1: it's actually creating more work for other people due to 176 00:10:17,920 --> 00:10:21,520 Speaker 1: AI slop as opposed to saving time and hours and 177 00:10:21,559 --> 00:10:25,880 Speaker 1: improving your thinking. And then finally, make sure with whatever 178 00:10:25,880 --> 00:10:30,000 Speaker 1: you're connecting it into that you obviously are thinking these 179 00:10:30,040 --> 00:10:34,120 Speaker 1: things through and not releasing people's salary details for example. 180 00:10:34,880 --> 00:10:38,079 Speaker 2: And as a bonus point here, I'd say train your 181 00:10:38,240 --> 00:10:41,040 Speaker 2: changed leads, which might be your team leads, it might 182 00:10:41,120 --> 00:10:44,160 Speaker 2: be dedicated to change leads to be able to help 183 00:10:44,200 --> 00:10:48,640 Speaker 2: people to fit AI into their workday. So I'm writing 184 00:10:48,640 --> 00:10:51,000 Speaker 2: a report every week, get the change lead to help 185 00:10:51,040 --> 00:10:53,000 Speaker 2: me to figure out how I can get AI to 186 00:10:53,040 --> 00:10:56,240 Speaker 2: help me to make that report writing task a lot faster, 187 00:10:56,360 --> 00:11:00,520 Speaker 2: a lot more simple. So that's the showing people how 188 00:11:00,520 --> 00:11:03,199 Speaker 2: to use every function on the firma mixed kind of problem. Now, 189 00:11:03,280 --> 00:11:05,640 Speaker 2: the thing is that often me is just a regular 190 00:11:05,679 --> 00:11:08,520 Speaker 2: staff member. I'm not tapped into all those things. So 191 00:11:09,080 --> 00:11:11,400 Speaker 2: as far as what the capabilities are, the best practice, 192 00:11:11,480 --> 00:11:13,600 Speaker 2: how to plug it into these tools and things like that. 193 00:11:13,800 --> 00:11:16,000 Speaker 2: So having the changed leads who have first off been 194 00:11:16,000 --> 00:11:19,439 Speaker 2: through training themselves and additional training, like we offer proper 195 00:11:19,640 --> 00:11:22,240 Speaker 2: change lead at training, but make sure that they know 196 00:11:22,480 --> 00:11:24,920 Speaker 2: more than just which button to press. It's more about 197 00:11:24,960 --> 00:11:28,640 Speaker 2: how this tool can help people in their workflow. That's 198 00:11:28,679 --> 00:11:31,200 Speaker 2: where the real benefits come in. Because simply saying you 199 00:11:31,240 --> 00:11:34,120 Speaker 2: can use it to help you write documents is great. 200 00:11:34,520 --> 00:11:37,600 Speaker 2: Showing them how that document can be written or changed, 201 00:11:37,720 --> 00:11:41,360 Speaker 2: or analyzed or or brought into a whole bunch of 202 00:11:41,360 --> 00:11:45,319 Speaker 2: things is the valuable part. So those change leads and 203 00:11:45,360 --> 00:11:48,040 Speaker 2: being able to work with people so so important to 204 00:11:48,080 --> 00:11:50,160 Speaker 2: be able to get productive in the organization, and also 205 00:11:50,200 --> 00:11:51,560 Speaker 2: in a way that people feel supported. 206 00:11:52,920 --> 00:11:55,600 Speaker 1: If you are listening to this and thinking, oh my goodness, 207 00:11:55,640 --> 00:11:58,400 Speaker 1: I've not done any of this yet, I am a leader. 208 00:11:59,360 --> 00:12:02,520 Speaker 1: Give me and I drop us a note. We are 209 00:12:02,520 --> 00:12:06,920 Speaker 1: helping companies with these kinds of challenges every single day. 210 00:12:07,000 --> 00:12:09,760 Speaker 1: There's an email address in the show notes and we 211 00:12:09,880 --> 00:12:14,600 Speaker 1: will see you next Monday. If you found this useful, 212 00:12:14,679 --> 00:12:17,679 Speaker 1: please help us spread the AI love and share it 213 00:12:17,720 --> 00:12:20,320 Speaker 1: with someone who you think would benefit from knowing what 214 00:12:20,559 --> 00:12:23,720 Speaker 1: you now know. And if you're ready to really start 215 00:12:23,800 --> 00:12:28,840 Speaker 1: mastering AI, check out Inventium dot ai. We help individuals, teams, 216 00:12:28,840 --> 00:12:34,160 Speaker 1: and organizations turn Jenai into a real work superpower, saving 217 00:12:34,400 --> 00:12:37,400 Speaker 1: ten plus hours a week and staying future ready without 218 00:12:37,440 --> 00:12:40,480 Speaker 1: the jargon or overwhelmed. Thanks so much for listening and 219 00:12:40,559 --> 00:12:44,959 Speaker 1: we'll see you next time on how IAI. How IAI 220 00:12:45,240 --> 00:12:48,280 Speaker 1: was hosted by me Amantha Imber and Neo Applan. A 221 00:12:48,360 --> 00:12:51,040 Speaker 1: big thank you to Martin Imba who does our sound editing, 222 00:12:51,160 --> 00:12:54,480 Speaker 1: and Jim Rubio for production support, and thank you to 223 00:12:54,600 --> 00:12:56,880 Speaker 1: John Kilby who composed the theme music.