Greatest Hits #4 - The Implement AI Podcast with Piers Linney & Dr. Aalok Y. Shukla

Welcome to the Implement AI podcast. The podcast where we explore the impact of AI on your business. I'm Piers Linney and alongside my co host and co founder of Implement AI Dr. Alex Shukla. We cover the real world applications and impact how AI can be practically applied to drive growth and efficiency in your organization. We cut through the jargon to focus on actionable strategies and use cases to highlight the transformational power of AI. Let's dive into today's conversation. It needs a fundamental rethink of how we run our businesses and organizations and we're now launching sort of an accredited executive program at Henley Business School to help executives get their heads round this fundamental change. It's not an IT project. You fundamentally have to think about how organizations are going to change because startups AI first are going to disrupt their sectors. You need to have a primary owner within the business responsible for coordinating all of these different elements. This is a cross silo project which suddenly unlocks different possibilities and nobody before had the authority to even think or discuss things in that dimension. So having that primary owner can then help with that. Most companies say they're ready for AI, but structurally they're not. They jump to let's get an agent up and running without the alignment, the inputs or even the ownership needed to make it work. And because AI cuts across every function, projects are going to stall fast. At Implement AI, we fix that with a clear blueprint. We understand the current state, define the future state and use our ABCD framework to get an agent live in weeks, not months. We pre value in one workflow and then we scale into a blended team of humans. It was amazing how many people use ChatGPT and don't even know there's a shopping research mode. Next year you're going to see that this is the de facto way in which people search and browse the Internet and they start to do things like shopping. The innermost loop of technology is basically AI coding. Agents improving AI models which improve AI coding, agents which improve AI models. That has taken off a lot. You look at like the kind of the powerful models like Gemini or other ones, Claude code because it's the fastest. Innermost loop of technology has been exploding, but it's not taking off where agents are hitting human resource and friction of organizations. Yet there won't be a board or shouldn't be that isn't having a conversation whether they actually start implementing actively. But it's going to come up in every board meeting or at least one board meeting throughout the year about what are we doing when it comes to AI. And if that board's not having that conversation, not doing their job properly. Absolutely. Because essentially the key metrics are like revenue per employee, or if you're looking at, for example, what are competitors in a market space doing, how can we achieve our growth targets? All of those things have to involve leveraging AI. So that is a strategic imperative. And you've even seen examples where there's been firms which aren't using AI, or they've had their market cap cannibalized by AI, for example, like some language instruction or some other areas, or even translation businesses and stuff like this. If they're on the reactive foot, it's a problem. But then other ones, if they've got an AI structure strategy, their stock price can go up, basically, isn't it? So you've got people who say, I use AI, and I say, in events, put your hand over, how do you use it? Most people use it to write a poem for their mom's birthday. That's about as far as it's gone. Then you've got some power users like us, I suppose, especially yourself, power users that are really changing the way you do everything, everything using this technology. So I think what the government understands now, and I think all governments going forwards are going to have to be really. This is going to be key to all government strategy going forward, and policy needs to focus on this, is trying to not create lots of, you know, tech and coding experts, just normalize AI use, make it something everyone understands they're not afraid of. Absolutely. Steve Jobs used to say, like, the computer's like a bicycle for your mind right now. Think about AI. It's like a whole level of that upgraded way. The thing is, we're in a rapidly changing world, so the best thing you can do is upgrade your ideas, your levels to think. And who knows, you could unlock a new opportunity, a new business, a new job, new possibilities, basically. There's never been a better time to improve your personal prospects, honestly. So I think we think is that increasingly, especially with the announcement today, the access to skills and training and also other places, well, online, what was interesting and what we'll talk about is that 20% of workers aren't confident using AI, and I think one in six businesses are not using it at all, which is insane. One of the things I find is that by calling it AI and talking about AI, we often focus on the technology rather than the use. The fact that there are people right across this country using spellcheck, which is increasingly based on an AI Model people call it spellcheck rather than AI, but that's AI when people use Google Maps to get around the country and get around our communities. Underlying technology, AI. And so the thing I'm really keen on is instead of talking about the underlying models or the technology, we talk about the use case. I think the way to kind of reframe what's going on here is you're almost giving a cognitive amplifier. It gives you a lens to think through things first and also to see perspectives that you yourselves could not see. So for example, this morning I received a contract and I just put it straight into Plaud and I was like, look, is there any unfair clause in here? Is there anything I need to be aware of? And this stuff I work pairing my brain with Claude, right? And I'm like filtering it through and I think if somebody understands that, look, whatever thinking level you thought you had, that was like almost like engine was fixed but now it's like not fixed, right? You can actually see things you couldn't see before. We are big believers in the fact this is going to have an enormous effect on job skills, employment, the economy, business operations and the UK as a whole in terms of our competitiveness going forwards. The main reason I wanted to talk to you was because when I think about how AI will actually make a difference for the country at large and to people's day to day lives, it will not just be from getting the right, best, biggest models of the frontier, but fundamentally it will be through implementing, adopting, diffusing AI right across our lives and across our organizations. And so this is really the central thing that the government is focused on. Today's announcements are effectively saying if implementation is the biggest thing that will drive prosperity and dignity for people from AI, then the biggest driver of that implementation is the quality of our skills and the ability of our people to be able to do that implementation. Every single industry, whether you're, let's say a healthcare group or whether you're a professional services accounting firm or you're an E commerce company or you know, a HR or recruitment company, every business has its kind of like accepted operating profit. Now with AI here I'm talking about digital colleagues and digital departments. So if you've got digital workers, that's an entire new labor source that you don't plug into your business. There's also a gap sometimes between, you know, the technology is capability today it's evolving all the time. What we know it can do, what we know it's good at because it can do some things that it's, you know, exciting, but it's not always particularly reliable. I was asking at the event, right, I said, like, who here has got like many junior people asking a senior person questions? And they were saying loads of people. And they said, and how much is that senior person's time worth? They were like saying, you know, 70 quid an hour, 200 quid now, five quid an hour. And I said, okay, how many hours a week are they doing that? And some people said, 20 hours a week. That's insane, right? That's the cost of that person's time being done in this way. But if you imagine in a reasonably large organization, how much time, effort, energy, resource goes into basic conversations, be it support, be it customer, be it wiz, where is my order? Or be it, you know, how do I do this? It's an enormous amount of time. It's just. So if we think about three categories of different digital AI agents, so one type would be what we call interactive agents. That's where they're basically primarily conversational. So it could be with people or with team members or employees. The second category that we're going to talk about is going to be action agents. So that's where we're actually like doing execution of things and that could be computer use agents where they actually operate a SaaS software or look on the Internet and do do different things like physically operating a browser, or they could be using APIs to actually action things, update CRMs, pull different things, all that kind of stuff like that. The third category is analyst agents. Probably one of my favorite ones, actually finding out new insights and intelligence and opportunities from the data that you've already got. This is the Implement AI podcast. We're out in Dubai, but wherever we are, we've produced this book. So we've spent three years learning about how to build an AI platform, how to implement it into businesses and this handbook, basically we've distilled all those insights, everything we learn into this guide. So if you want a copy of this, go to our social media, our website, our resources center, or if you watch the pod, the link is in the description. So think about like some of the real world examples. One of the highest value ones that we use all the time, and I think it's one of the most popular ones, is the call analyst agent, basically. So that's listening to all the phone calls that came in, but it could be teams meetings as well. This is the most powerful agent I think we do. Yes, I think because it just, just generates money out of Nowhere. Correct. It's just magic, literally. Do you want revenue or not? Would you like some money that you already have? It's like basically behind, it's like going behind the sofa, putting your hand in the sofa and you pull out like thousands of pounds basically or tens of thousands of pounds or hundreds of thousands of pounds basically. So the point there is like this is where the analyst agent will like go far beyond. Some people think, oh, I've got AI on my calls. Analyze the sentiment. You're missing the point basically, right? We're talking about understanding specific friction points. Buying intent, you know, name entity, recognition, you know, competitors that are mentioned, how well your team handled the call based five dimensions. Then also like did they discuss a high value service? If so, what's the value of that service? Did they buy or book an appointment? Why didn't they do that? And you're learning recursively. So you either you have a learning to improve the agent's performance or you're learning to improve the humans performance. So the core message here really is, you know, production AI infrastructure is what this is all about. It's about having agents doing work, not experimentation and talk endlessly. And I keep saying, you know, if you're a senior leader, an owner, you're on a board, you don't have these conversations about how you start really deploying agents into your business this year, right? I don't think you're doing a job and I don't mean replacing your workforce. It's really now about augmentation, it's about helping them do things in ways they couldn't do. But when you do have a human in the loop, you can revert back to human time. Would you have to? But what you're going to learn is in your organization, your business, your workflow, especially your regulator as well. Where is that line? Where do you want humans in the lead? Where do you want that core escalated to humans. And that's what you're only going to learn, that you can do that from pilots. But you only really learn this at scale where you have a sort of ongoing interaction with customers, prospects, stakeholders, employees at scale, in real time. First you need to see what you've never seen before, then you can do what you've never done before basically. Right? So the point here is that like most businesses know they should be using AI, they've heard of like different, you know, things like voice agents, chat bots or tools, they play around with it. But the key thing that they don't understand is like they get the most opportunity and the most elements from actually going deep into it. Thank you for joining us for this episode of the Implement AI Podcast. If you're interested in learning more about how we can assist you and your business in leveraging AI for growth and efficiency, visit our website at ImplementAI IO. Don't forget to subscribe to the Implement AI podcast on Apple Podcasts, on Spotify, or wherever you listen to. Stay updated on future episodes. Thank you for listening and we'll see you next time.