Most organizations measuring their AI progress and measuring the wrong theme. They're tracking how many people have a license, how many you have done the onboarding training, what percentage are using AI? In some form? And on paper it looks like progress, but in practice it often isn't because using AI and using AI well are two completely different things. One can actually make your team less productive because you get buried in mediocre output, drowning in AI slop, and none of
it's moving the needle. So in this episode, Neo and I get into what actually separates high performing AI augmented teams from the average ones. We cover why adoption metrics are almost always vanity metrics, the difference between AI literacy and AI leverage, and why most teams nail the first
and never get to the second. We also talk through what it looks like to truly re engineer your workflows, not just slot AI into the ones that you already have, and by the end you will have a much clearer picture of where your team sits and what it would take to close the gap. Welcome to how IAI with me Doctor Amantha Imber and Neo Applin, head of Inventium AI. Each episode we share one practical way to use AI better at work and in life. No fluff, no deech jargon,
just things you can use straight away. So at inventium AI, we have worked with one hundreds and hundreds of different teams and many organizations around building AI capability, and I think there's still a really big difference between what a high performing AI augmented team looks like like and what an average team looks like. Neo, what are you noticing are the biggest difference is because most teams are using AI in some shape or form, but how are they really high performing ones different.
They've embedded it within the workday core, so other people are using it a little bit, and the poor performing teams are actually over using it poorly. So maybe we'll start there. So the poor performing teams are the ones who are doing AI slop, So they're the ones who are looking really efficient. They're creating lots of documents and we're creating lots of packs of blah blah blah. They're just getting AI to do the lot, and unfortunately they're
just getting buried in information. So a little bit of training, which is basically here's AI, you've got it now, go, is actually the worst part of training you can do showing people how to correctly use it. Then you're actually getting some benefits, but then generally it becomes I make a joke where it's my dad brought my grandma when you're still alive, a microwave and she for one thing only,
which was defrosting soup. AI is being used the same people know how to use it that one way, and so therefore it's being used that one way every single time, every single week, so they're not opening up the breadth. The big changes that happen when you actually embed it in your work date where you're using it in different ways to be able to solve problems, to do things better, to do things faster, and that's where you get the benefits.
But that's where everyone needs to be using it for similar kind of things and so that everyone is using AI to all get better, to get stronger, to get a better result. And that's where the higher performing teams work. It's not just about using the tool, it's using it well so that you're delivering for your team and for your customers and clients.
And this is where I see leaders getting their metrics around AAI a little bit wrong. A little bit kind of vanity metrics as I would think of them, where I would say a lot of organizations that we encounter will say we've got an adoption target. So for example, we want you know, eighty percent of our workforce to have adopted AI, which basically means using AI or maybe you know, put through some internally created perhaps not that useful training in how to use AI, certainly using it responsibly.
And if that is your target around how well you are going with AI that people are using it, that target is just so way off because you can easily actually get a whole lot worse when it comes to productivity. Let alone, just keep your productivity the same as Neo was saying, So Neo, can you share how with inventim AI's clients where we take quite a different approach because we see this in two parts in terms of first, yes,
there absolutely is literacy, but then there's leverage. Can you talk a little bit about that.
Yeah, literacy first off is what are these tools, how they are different, how do we get the best out of those things, and how do we avoid things like aislop And that is really important. That is your foundation. You need to have a solid foundation on what is
this thing? And then how's it going to work? And some of these things are different for leadership teams, and we run leadership teams and boards through this, So like if you're setting policies, then you need to know what these tools are, how they work, so you can then create the policy. But also for knowledge workers, which is the bulk of our work, to know how and when to use it is really caught. The leverage comes in where it's how do I embed this in my day job?
How do I speed up the things that I'm doing? And how do I get a better result? Because sometimes speeding up isn't the most important thing. Sometimes better result, but slower is better, or maybe a more customer centric approach to things is better. So how do I use this brand new tool. We've got to be able to get the benefit. And it's not about let's get the same process we've always had and then get AI to step into one of those steps. Yep, that's an interim step.
That's where a lot of organizations go. It's more about now we've got this tool, now we understand what it is, how do we reinvent how we do our work, how we deliver our services, now we've got this amazing tool, and that's where the organizations really go better, and that's using the leverage of AI in a new way, because this is a new tool we've never had before.
Can you give an example maybe of a team that you've worked with where you've really couldn't double down on going, okay, this is how you leave reach AI in things like you're doing every day.
Here's a really simple and we see this a lot of places. Back in the day, managers look at a spreadsheet and they'd go, I need to get some insights out of this. But maybe managers weren't the pivot table experts. Maybe they weren't great with Excel formulas because you didn't need to be because you'd have that awesome person in your department, let's call it. You go to Susie and say, hey, look, can you please do some analysis on this spreadsheet for me?
Now you could say, why don't we get Susie with AI so Susie can do it faster. That's one way to do it, and certainly a lot of people doing that. We're teaching a lot of Susie's and David's and Justin's to be able to do that as well, But wouldn't it be better if we could get AI to be there to be able to service the manager, so everyone
then can self service rather than going to Susie. It's then I can ask questions of the AI, so either I can get that information out or even better, I can get the report that I need in the way that I need every single time. So it's not so much me just ask questions of it. It's I can just feed it a spreadsheet. It knows exactly what I'm after in a particular way I'm after because I've either built a workflow or built an agent or a GPT or a GEM or a project that then deliver me
exactly what I need every single time. So it's an easy way to re envisage the way that we're doing things. But these are all embedded with so many different teams we've got, Like here's an example of like a hotel, you get lots of Q and A coming through to your concierge desk. You know what times a pool open and if I made a reservation, can I cancel it?
And how of far and all those kind of things, So you could have to have that information in your brain or you can get an agent to be able to craft those emails for you for your customer, or you can even build a workflow where AI can help you to do that kind of thing automatically and it drops out the hard ones that you need human to process. So maybe it's like eighty twenty eighty percent has been automated and twenty percent has been taken care of by people.
It's now what we've got with this tool, how do we solve that problem better and perhaps go closer to the source or closer to the person who needs to use it. And that's the real leverage.
And what we're certainly finding and recommending to our clients is that, yes, everyone needs a certain amount of literacy about AI so that they're getting good output rather than just proliferating the organization with aislop, which is going to have really detrimental impacts on productivity, reputation, all sorts of things.
But then what we're typically doing is we're working with AI champions and these are spread across different functional groups because you need to have that more advanced understanding of what AI is capable of in order to get those benefits, because most people are not like workflow architects where they know how to identify what are the different workflows that this individual or this group goes through daily or weekly, And then how do you even map out a workflow?
Like most people don't have those skills, and that is a really critical skill set to have in order to really leave reach AI. If you can't do that, it's really hard to access the gains.
And it's even harder to go mapping. It is one thing, one skill to then go how do I re envisage? That's a completely different skill as well, And that kind of takes a bit of a bit of a blue sky thinker, someone who understands the business and also can understand what the technology can do. And so yeah, we do definitely help these kind of people to build up those skills. We also build a bunch of tools to help them to help themselves with AI as well.
So I would say, if you are listening and relating to having some sort of a metric in your organization or maybe even just for yourself, to go, yes, have I got people using AI? Have I given them licenses? So have I put them through some basic training? I would say it's really problematic if you are stopping there so I would challenge any listener to think about how can you really leaverage AI? How can you unpack your workflows? How can you really think deeply around where AI is
best place to help you. Obviously, Neo and I are very biased because we do a lot of this training at Inventium AI, but by all means go anywhere, but make sure you are doing it to unlock the full benefits of AI whatever your job looks like.
And just kind of leveraging that. I've read some studies a couple of days ago. The minimum viable dose for AI training is five hours minimum viable. Anything less than that you're not going to get any benefit in the workplace. But that is not about leverage. That is just about baseline.
Can I use this tool? There are companies that spend up to believe it or not, eighty one hours on their teams, and what that's about is is what Amantha and I are talking about, which is using the skills in your workplace to re envisage your workflows and help your clients even better than you did before. That's where the benefit comes from.
And Neo, I'm going to do a shameless plug because we do have a new program that We've just launched an inventium called the AI Agent boot Camp, which is designed to solve this very problem where we will be taking people through how do you become a workflow architect and how do you really double down on understanding where can AI help you augment or streamline those workflows get massive productivity savings but also get far better output at the end of the day.
Yeah, it's a fun day. And also you bring one of your problems and we will help you solve those problems with agents during the day, so you've actually got us and a whole bunch of AI tools to be able to help you with that. So yeah, it's good fun day.
And there is a link to that in the show notes. How IAI was hosted by me, Amantha Imber and Neo Applan. A big thank you to Martin Imba who does our sound editing, and Jim Rubio for production support, and thank you to John Kilby who composed the theme music.