AI in Business

How to talk about AI without sounding foolish

Dec 11, 202400:09:26Tap to summarize

Episode 011: The AI leader’s playbook: How to talk about AI without sounding foolish G’day and welcome to episode 11 of the 'AI in Business' podcast, where we talk about how leaders and entrepreneurs can benefit from not only the implementation of AI, but also the innovation and growth in creative thinking that comes with it. We’ve seen time and time again how this growth in creativity creates results that positively impact your bottom line.. I’m Lee Hopkins and today I’m diving into a topic that’s close to many leaders’ hearts: How to talk about AI without sounding foolish. Let’s face it, artificial intelligence is a daunting subject for many of us. It comes with its own language, its own rules, and its own set of acronyms. If you’ve ever found yourself in a meeting, nodding along to buzzwords like “machine learning” or “predictive analytics” and hoping no one asks for your thoughts, you’re not alone. But here’s the thing: you don’t need a PhD in computer science to hold your own in a conversation about AI. You just need a basic understanding of the key concepts and the confidence to ask the right questions. By the end of this episode, you’ll have a clear understanding of the key AI terms every leader should know, and you’ll feel more equipped to engage in discussions about AI, whether it’s in your boardroom, at a networking event, or even in casual conversations with your team. Let’s get started. Why talking about AI feels intimidating. AI comes with a significant barrier to entry, and I don’t mean the technology itself. I’m talking about the language. Terms like “neural networks,” “deep learning,” and “natural language processing” can feel intimidating, even for seasoned leaders. And when you’re in a leadership position, there’s often an unspoken pressure to appear knowledgeable about everything, after all, you’re the one steering the ship. But here’s the truth: no one expects you to be an AI expert. Your role as a leader isn’t to understand every technical detail, it’s to grasp the big picture and ask the right questions. The goal isn’t to master the jargon; it’s to understand how AI can solve problems and create opportunities for your business. So, let’s break this down into manageable pieces. We’re going to focus on three key areas: The essential AI terms every leader should know. A real-world example of a company using AI effectively. Practical tips for talking about AI with confidence. Key AI terms every leader should know. Let’s start with the basics. If you take away nothing else from this episode, I want you to remember these three terms. They’ll help you hold your own in any AI conversation, and they’ll give you a solid foundation to build on. First, Machine Learning. Machine learning is one of the most common applications of AI. It’s the ability of a computer to learn from data without being explicitly programmed. Think of it as teaching a computer how to improve over time based on the data it’s given. For example, a retail company might use machine learning to predict which products will sell best during the coming season, based on years of historical sales data. Next, Predictive Analytics. Predictive analytics uses historical data to forecast future trends. It’s like having a crystal ball, but instead of magic, it’s powered by algorithms. For instance, a financial institution might use predictive analytics to identify customers who are at risk of defaulting on loans, allowing them to intervene before it’s too late. Finally, Natural Language Processing (NLP). NLP is how AI understands and responds to human language. It’s what powers technologies like chatbots, voice assistants, and automated translations. If you’ve ever asked Siri or Alexa a question, you’ve interacted with NLP. Now, you don’t need to dive into the technical details of these terms. What’s important is understanding what they mean in a practical sense and how they can be applied to solve real business problems. Case study: Telstra’s success with AI-powered customer service. Let’s bring this to life with a real-world example. Telstra, Australia’s largest telecom company, faced a common challenge: how to handle a high volume of customer inquiries efficiently, without sacrificing the quality of service. To solve this, Telstra turned to AI, specifically, natural language processing. They developed AI-powered chatbots capable of resolving up to 70% of customer inquiries without any human intervention. These chatbots could handle everything from billing questions to technical support, freeing up Telstra’s human staff to focus on more CoMplex and high-value interactions. The results were impressive: Customer satisfaction improved, as customers received faster, more accurate responses to their inquiries. Operational efficiency increased, as fewer resources were needed to handle routine tasks. And Telstra’s leadership team gained valuable insights into customer behaviour, which they used to improve their products and services. The key takeaway here is that Telstra’s leadership team didn’t need to understand every technical detail of natural language processing. They simply needed to understand how the technology could be applied to solve a specific business problem, and to trust their team to execute the vision. Practical tips for talking about AI with confidence. So, how can you, as a leader, talk about AI with confidence, without feeling like you’re in over your head? Here are three practical tips: One: Focus on outcomes, not technology. When discussing AI, focus on the outcomes it can deliver, rather than the technology itself. For example, instead of saying, “We’re implementing machine learning,” say, “We’re using AI to improve our customer retention by predicting which customers are likely to churn.” This shifts the conversation from technical jargon to tangible business value. Two: Ask questions. Never be afraid to ask questions. In fact, asking thoughtful questions is one of the best ways to demonstrate your leadership. For example, you might ask, “How will this AI tool integrate with our existing systems?” or “What metrics will we use to measure its success?” The goal is to understand how AI aligns with your business objectives. And Three: Leverage your team and experts. Remember, you don’t have to know everything, it’s okay to rely on your team or external experts for guidance. Surround yourself with people who understand the technical side of AI, and focus on your role as a strategic decision-maker. Closing thoughts. To wrap up, talking about AI doesn’t have to be intimidating. By understanding a few key terms, focusing on outcomes, and asking the right questions, you can engage in meaningful conversations about AI and lead your organisation with confidence. Remember, you don’t need to be an AI expert, you just need to be an AI-informed leader. If today’s episode has sparked your curiosity about AI and how it can benefit your business, we’d love to hear from you. Drop us an email at curious at ‘ameegoes’.com, that’s ‘a i m e g o s dotcom’, or give us a call on ‘zero four one zero’, ‘six four two’, ‘zero five two’. Let’s have a chat about how we can help you navigate the design and implementation of AI in your organisation. Because if -YOU don’t, your competitors will. Well, that wraps up this episode of the AI in Business podcast. You can catch our 'AI in Business' podcast on Spotify and Apple Podcasts, and if something you’ve heard here inspires you, please leave a comment on our podcast feed. Until next time we meet, keep innovating and taking those bold business risks, and let us help you revolutionise your business with people-first AI. Until next time, -bye.

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Fear of AI

Dec 8, 202400:10:00Tap to summarize

Episode 010: From hesitation to innovation: Overcoming fear of AI in leadership G’day and welcome to episode 10 of the 'AI in Business' podcast, where we talk about how leaders and entrepreneurs can benefit from not only the implementation of AI, but also the innovation and growth in creative thinking that comes with it. At Ameegoes, we’ve seen time and time again how this growth in creativity creates results that directly impact your bottom line, in a very positive way. I’m Lee Hopkins, the Director of Communication at Ameegoes, and today, I’m talking about something that often holds business leaders back from achieving their true potential: From hesitation to innovation: Overcoming fear of AI in leadership. AI is a hot topic, it’s in the news, it’s in your boardroom, and it’s probably come up in conversations with your peers. But despite all the hype, many leaders remain hesitant about adopting AI. Maybe it feels too CoMplex. Maybe you’re worried about the costs. Or maybe it’s the cultural shift that comes with implementing new technologies. Whatever the reason, you’re not alone. Today, we’re going to explore why fear of AI is so common, how to manage it, and how to take your first steps toward innovation. Why AI creates hesitation. Let’s start with a bit of honesty. If you’re feeling nervous about AI, you’re not alone. In fact, a recent Deloitte study found that around 40% of leaders remain hesitant to adopt AI technologies due to concerns about their understanding of the technology, its costs, and its potential to disrupt existing workflows. That’s a significant number, and it shows that fear of AI isn’t just a “you” problem, it’s a leadership challenge that many of your peers are facing as well. So, why does AI create hesitation? There are a few key reasons, and they’re completely understandable. First, there’s the fear of the unknown. AI is still a relatively new frontier for most businesses, and as humans, we’re wired to resist the unfamiliar, it’s a survival instinct. But in business, this fear can prevent us from embracing opportunities that could transform our organisations. AI can feel like stepping into uncharted waters, and that’s enough to make anyone hesitate. Second, there’s the fear of failure. What if the AI implementation doesn’t work? What if it costs too much, or what if it doesn’t deliver the promised results? These are valid concerns, and they’re especially heightened in industries where budgets are tight and resources are limited. No one wants to be the leader who championed a failed project. And finally, there’s the fear of looking foolish. This is perhaps the most common fear among leaders. Whether it’s in front of your peers, your board, or your team, no one wants to admit they don’t fully understand something. As a leader, you’re expected to have the answers, and the idea of saying the wrong thing, or worse, making the wrong decision, can be paralysing. But here’s the good news: being a leader doesn’t mean you have to know everything. It means you have to be willing to learn and surround yourself with people who can help you make informed decisions. And that’s exactly what we’re going to talk about today. Reframing fear as opportunity. So, how do we overcome these fears? It starts with reframing them as opportunities. Fear is natural, but it doesn’t have to be a barrier. In fact, it can be a powerful motivator for change if you approach it the right way. Instead of seeing AI as a “threat,” try to see it as a tool for growth. Think about the tasks in your business that are repetitive or time-consuming. How could AI help your team automate those processes so they can focus on higher-value work? Instead of worrying about AI replacing jobs, focus on how it can enhance creativity and innovation within your organisation. Instead of worrying about failure, focus on small, low-risk experiments that allow you to learn and adapt. AI doesn’t have to be an all-or-nothing proposition. You can start small, test the waters, and scale your efforts as you gain confidence. And instead of fearing what you don’t know, embrace curiosity. The best leaders are lifelong learners, and AI is an incredible opportunity to expand your knowledge and skill set. The more you learn, the more confident you’ll become in your ability to lead your organisation through the AI era. Case study: ANZ Bank’s journey from fear to innovation. Let me share a real-world example of a company that overcame its hesitation and embraced AI. ANZ Bank, one of Australia’s largest financial institutions, initially hesitated to adopt AI, fearing it would disrupt their traditional workflows and alienate customers. But instead of diving in headfirst, they took a measured approach. They started by using AI to enhance their customer service through chatbots. By analysing thousands of customer inquiries, the AI system was able to provide faster, more accurate responses. Customers received the answers they needed in real time, and the bank’s human staff were freed up to handle more CoMplex and high-value tasks. The results spoke for themselves: Customer satisfaction improved by 20%. Operational costs were significantly reduced, as fewer resources were needed to handle routine inquiries. And perhaps most importantly, the leadership team gained the confidence to expand AI into other areas of the business. Today, ANZ Bank is seen as a leader in AI innovation within the financial sector, and it all started with a single, low-risk pilot project. Source: ANZ Bank AI case study – IBM The key takeaway here? You don’t have to tackle AI all at once. Start small, measure your results, and let those wins build your confidence over time. Strategies for overcoming fear as a leader. At Ameegoes, we’ve worked with dozens of leaders who were initially hesitant about AI. Over time, we’ve identified three strategies that are particularly effective in helping leaders move from hesitation to innovation. Educate yourself. Fear often comes from the unknown. The more you understand about AI, the less intimidating it will feel. Take the time to learn the basics, what AI is, what it isn’t, and how it can be applied in your industry. There are plenty of free resources online, and of course, we’re here to guide you through the process. Start with a pilot project. Choose a single, low-risk area of your business to test AI. This could be automating a repetitive task, improving customer insights, or streamlining internal processes. The goal is to keep it manageable and measurable. Once you see the results, you’ll be better equipped to scale your efforts. Leverage external expertise. You don’t have to do this alone. Partnering with an experienced consultancy, like Ameegoes, can help you navigate the CoMplexities of AI and avoid common pitfalls. Sometimes, having the right guidance is all it takes to turn fear into confidence. Closing thoughts. Hesitation is human, but it doesn’t have to hold you back. By educating yourself, starting small, and leaning on the right support, you can turn your fear into a powerful driver of innovation. AI isn’t just the future of business, it’s happening right now. And the leaders who embrace it today are the ones who will shape tomorrow. Remember, every business leader who’s successfully implemented artificial intelligence started exactly where you are now... Want to know more about how to lead your organisation into the artificial intelligence era with confidence? Well, we’re here to help. Drop us an email at curious at ameegoes.com, that’s a-i-m-e-g-o-s-dot-com, or give us a call on ‘zero four one zero’, ‘six four two’, ‘zero five two’ and organise a suitable time to talk seriously about how we will help you navigate the design and implementation of AI. Let us help you lead your organisation to new heights and new profitability, and have your staff unleash their hidden creativity and help drive your business forward at a rate that will surprise you—because if you don’t, your competitors will. Because if you don’t, your competitors will. Well, that wraps up this episode of the AI in Business podcast. You can catch our 'AI in Business' podcast on Spotify and Apple Podcasts, and if something you’ve heard here inspires you, please leave a comment on our podcast feed. Until next time we meet, keep innovating and taking those bold business risks, and let us help you revolutionise your business with people-first AI. Until next time, bye.

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AI demystified: What every CEO needs to know to stay ahead

Dec 5, 202400:09:05Tap to summarize

G’day and welcome to episode 9 of the 'AI in Business' podcast, where we talk about how leaders and entrepreneurs can benefit from not only the implementation of AI, but also the innovation and growth in creative thinking that comes with it. At Aimegos, we’ve seen time and time again how this growth in creativity creates results that directly impact your bottom line, in a very positive way. I'm Lee Hopkins, the Director of Communication at Aimegos, and today we're tackling a topic that’s on many leaders’ minds: What every CEO needs to know to stay ahead. If you’re feeling a little overwhelmed or even sceptical about AI, you’re not alone. Today, I'm going to break it all down into manageable pieces so you can approach AI with confidence, clarity, and purpose. Why AI feels overwhelming. Let’s start by addressing the elephant in the room, why does AI feel so overwhelming? First, there’s the sheer speed of change. Just a decade ago, AI was a term reserved for tech labs and sci-fi movies. Now, it’s everywhere, from the algorithms curating your Netflix recommendations to the chatbots on your favourite e-commerce sites. It’s no surprise that many CEOs feel like they’re constantly playing catch-up. Second, there’s the jargon. Terms like “neural networks,” “deep learning,” and “natural language processing” can make AI seem like an exclusive club for tech experts. And as a leader, the last thing you want is to look uninformed in front of your board, your peers, or your team. Finally, there’s the fear of making the wrong decision. Investing in the wrong AI tool or using it in the wrong way can feel like a costly mistake, especially when budgets are tight, and expectations are high. But here’s the thing: you don’t need to know everything about AI to lead with confidence. You just need to understand the basics and know how to apply them strategically to your business. What exactly is AI? (The simplified version). So, what is AI, really? At its core, artificial intelligence is about creating systems that can perform tasks typically requiring human intelligence. These tasks include learning, reasoning, problem-solving, and even understanding language. Think of AI as a super-smart assistant that can learn patterns, predict outcomes, and automate repetitive tasks. It’s like having an employee who never sleeps, never takes a coffee break, and gets smarter the more they work. Here’s a simple example: Imagine you run a retail business and want to predict which products will be in high demand next month. Instead of relying on guesswork or time-consuming spreadsheets, an AI system could analyse years of sales data, detect patterns, and predict trends with incredible accuracy. Or, say you’re in professional services. You might use AI to automate time tracking or invoice generation, freeing up your team to focus on higher-value tasks like client engagement. In many ways, AI is less about replacing humans and more about augmenting their capabilities. It’s a tool to help your team work smarter, not harder. The key to starting with AI. Now, here’s where many leaders stumble, they think adopting AI means overhauling their entire business overnight. But the reality is very different. The most successful AI implementations start small. At Aimegos, we often tell our clients to focus on just one pain point. Maybe it’s a bottleneck in your operations, like a time-consuming manual process. Or perhaps it’s a missed opportunity, like not having enough data on your customers to personalise your marketing. By starting with a specific problem, you can test AI’s impact on a small scale, measure the results, and build confidence in its potential. AI in action. One of the best examples of this approach comes from Australia Post. A few years ago, Australia Post faced growing challenges with delivery delays and customer complaints. Instead of trying to fix everything at once, they focused on a single issue: improving parcel delivery tracking. They implemented an AI-based system that analysed historical data, traffic patterns, and weather conditions to predict delivery times with greater accuracy. Customers received more precise tracking updates, and the entire logistics network became more efficient. The result? A significant reduction in delivery-related complaints and improved customer satisfaction. What’s more, Australia Post didn’t stop there. Once they saw the success of their AI pilot, they expanded it to other areas of the business, from warehouse management to route optimisation. The key takeaway here is that starting small doesn’t just minimise risk, it creates a foundation for scaling AI across your organisation. What you need to know to lead confidently. As a CEO or entrepreneur, your role in AI adoption isn’t to become a technical expert, it’s to become an AI-informed leader. And that starts with asking the right questions. Here’s a simple framework we use with our clients at Aimegos: 1. Understand the basics. Take the time to learn the foundational concepts of AI. You don’t need to know how an algorithm works, but you should understand what it can do for your business. Define the problem. Before jumping into AI, clearly define the problem you’re trying to solve. Ask yourself: What’s the outcome we’re looking for? How will this improve our business? Communicate with your team. One of the biggest barriers to AI adoption is fear, especially among your staff. Be clear about why you're implementing AI and how it will benefit them. Emphasise that AI is there to enhance their creativity, not replace them. Measure success. Finally, establish clear metrics to measure the success of your AI initiatives. Whether it’s reducing costs, improving efficiency, or increasing customer satisfaction, make sure you can quantify the impact. Closing thoughts. To wrap up, AI isn’t just a technology trend, it’s a business necessity. But it doesn’t have to be intimidating. By starting small, focusing on specific problems, and leaning on experts when needed, you can lead your organisation into the AI era with confidence and purpose. Remember, every business leader who’s successfully implemented artificial intelligence started exactly where you are now. The difference between success and struggle often comes down to having the right guidance and support. Want to know more about how to lead your organisation into the artificial intelligence era with confidence? Well, we’re here to help. Drop us an email at curious at Aimegos, that’s a-i-m-e-g-o-s-dot-com, or give us a call on ‘zero four one zero’, ‘six four two’, ‘zero five two’ and organise a suitable time to talk seriously about how we will help you navigate the design and implementation of AI. Let us help you lead your organisation to new heights and new profitability, and have your staff unleash their hidden creativity and help drive your business forward at a rate that will surprise you. Well, that wraps up this episode of the AI in Business podcast. You can catch our 'AI in Business' podcast on Spotify and Apple Podcasts, and if something you’ve heard here inspires you, please leave a comment on our podcast feed. Until next time we meet, keep innovating and taking those bold business risks, and let us help you revolutionise your business with people-first AI. Until next time, bye. Case study source: https://customers.microsoft.com/en-us/story/1368772233990532064-australia-post-travel-transportation-azure

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Implementing AI in business without losing staff trust

Dec 1, 202400:05:54Tap to summarize

Key Takeaways from Episode 8: • AI implementation parallels social media's business impact from 20 years ago • Start small with one process like email responses or data analysis • Involve your team from the beginning to build trust and enthusiasm • Measure and communicate success through clear KPIs • AI implementation can actually increase job satisfaction • Focus on augmenting human capabilities, not replacing them • Approach AI as a people strategy first, technology strategy second • Success depends on having proper guidance and support Sunday 1 December 2024 12:59 am G'day and welcome to episode 8 of the 'AI in Business' podcast, where we talk about how leaders and entrepreneurs can benefit from not only the implementation of AI, but also the innovation and growth in creative thinking that comes with it. At Amegos we have seen time and time again how this growth in creativity creates results that directly impact on your bottom line—in a very positive way. I'm Lee Hopkins, the Director of Communications at amegos, and today we're talking about something that's keeping many of you awake at night: implementing AI in your business without losing your mind or your staff's trust. Twenty years ago I was exactly where many of you are now, staring at the emergence of social media and wondering if it would destroy workplace productivity. Instead, it revolutionised how we connect with customers and staff. Today, I see the same fears about AI, but also the same incredible potential. Let me share a recent experience with a CEO in Adelaide. Sarah was terrified that implementing AI would make her look incompetent in front of her tech-savvy team. "Lee," she said, "I don't even know where to start, and my staff are already talking about ChatGPT like it's their new best mate." Well, here's the thing, you don't need to be a tech wizard to lead your organisation into the AI era. What you need is a strategic approach that puts people first. Let's break this down into three practical steps that have worked for numerous Australian businesses: First, start small. Choose one process, maybe 'email response times' or basic data analysis, and implement AI there. One of our Melbourne clients began by using artificial intelligence to draft initial customer service responses, which their team then personalised. The result was that response times dropped by 60%, and staff reported feeling less stressed about inbox management. Second, involve your team from day one. Make it clear that AI is about augmenting their capabilities, not replacing them. When the Commonwealth Bank introduced AI tools for their marketing team, they first ran workshops where staff could experiment and provide feedback. This approach turned potential resistance into enthusiastic adoption. Third, measure and communicate success. Set clear K-P-I goals before implementation and share the wins. A Brisbane logistics company we worked with saved 15 hours per week on routine tasks after implementing AI, time their team now spends on strategic planning and innovation. Here's what most people don't realise about AI implementation, it actually increases job satisfaction when done right. Staff who previously spent hours on repetitive tasks are now solving complex problems and being more creative. That's not just good for morale, it's brilliant for your bottom line. The key is to approach AI implementation as a people strategy first and a technology strategy second. Think of it like introducing a new team member, one who's incredibly efficient at routine tasks but needs guidance on company culture and values. If you're feeling overwhelmed about where to start, you're not alone. That's exactly why we developed our "People-First" approach, ensuring you feel confident and in control before rolling out any artificial intelligence initiatives. Remember, every business leader who's successfully implemented artificial intelligence started exactly where you are now. The difference between success and struggle often comes down to having the right guidance and support. Want to know more about how to lead your organisation into the artificial intelligence era with confidence? Well, we're here to help. Drop us an email at curious at ameegos.com, that's a-i-m-e-g-o-s-dot-com, or give us a call on zero four one zero, six four two, zero five two and organise a suitable time to talk seriously about how we will help you navigate the design and implementation of AI. Let us help you lead your organisation to new heights and new profitability, and have your staff unleash their hidden creativity and help drive your business forward at a rate that will surprise you. Well, that wraps up this episode of the AI in Business podcast. You can catch our 'AI in Business' podcast on Spotify and Apple Podcasts, and if something you've heard here inspires you, please leave a comment on our podcast feed. Until next time we meet, take some business risks, because you never know what will pay off, and let us help you revolutionise your business with people-first AI.

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Paul Glover - Automated Agile

Nov 22, 202400:35:47Tap to summarize

Welcome to the 'AI in Business' podcast. In this show we talk about how leaders and entrepreneurs can benefit from not only the implementation of AI, but also the innovation and growth in creative thinking that comes with it. At Aimegos we have seen time and time again how this growth in creativity creates results that directly impact on your bottom line—in a very positive way. I'm your host, Lee Hopkins. ------------------------- AiMegos (0:0.052) Today, I'm talking with Paul Glover from a company called Burendo in the UK. And we're discussing automated agile, a product that he's got up and running. So Paul, can you give us the elevator pitch about automated agile, please? Paul Glover (0:17.590) Yeah, so automated agile is really a way of thinking and all it really is is understanding that AI can utilize, you can utilize AI throughout the product delivery lifecycle and in doing so add productivity. But there isn't really a strong understanding of how to do that all the way through. There's individual use cases which are important, but it's about leveraging that rich context to produce great outputs. So what automated agile does is think about the whole product delivery life cycle and how you can get the most out of it utilizing AI. AiMegos (0:52.744) Okay, cool. So then if we look at the origin story of automated agile, what challenges did you have bringing it to where it is now? Paul Glover (1:6.338) Well, I think it's about understanding for people, I think, because it moves so quickly and that's overwhelming. what automated agile doesn't try and do is say, use this tool, use this process, use this way of thinking. What it does do is come up with a way of thinking about that to understand what drives the best performance out of AI, each of these steps, and how do we create a structure that allows you to put new tools and new processes in. And I think as a concept, that's something that You know, people are kind of thinking about that on a use case specific, you know, sense. Now you see a lot of tools out there that'll solve individual problems, but in terms of a whole workflow, you know, there are limited people out there really thinking about that and helping businesses. And that's really what this is automated agile about rather than being a product. It's more around how do we help businesses understand what the next step forward is because the floor underneath them is changing at a rapid pace. AiMegos (2:4.734) Yeah, isn't it? Yeah, absolutely. Star Trek, Star Trek, and I'm thinking the Holodeck in particular. Is there any similarity between the Holodeck and Automated Agile? Paul Glover (2:20.622) Yeah, the holodeck theory is something I like to talk about a lot, know, and it probably rings true with like nerds and people who've watched Star Trek, but ultimately it's all about, you know, you have an idea and then you have your products. And in between those two is a lot of friction, you know, is generally why I do for a living. And then that's, you know, what the product of your life cycle is. Whereas in a holodeck in Star Trek, you walk into a room and you say, you know, give me, you know, 1920s London, and it will. And that's really how software should be. You should be able to speak to a tool and say, this is the product I want, and it shows it you straight away. And then we'll change that and update it. So in our tests that we've done utilizing a process with automated agile at its heart, we've managed to create prototypes instead of 90 minutes, 75 minutes for one type of prototype. And what that does is put something in front of a customer and give them the opportunity to. and see whether or not they want to make any changes to it. And that's what we're trying to do. That's why we call it the Holodeck theory. It's that how do we close down that friction as much as humanly possible to make the process of customer feedback and customer improvement as immediate as possible? Because the primary measure of progress is working software, right? So it's about how do we keep those phases small? and keep the question that we're asking AI to complete as simple as possible. But yet make that forward progress more rapidly than we would be able to using traditional agile methodologies. AiMegos (3:58.822) OK, it reminds me then because of this, you know, talking to the engine rather than, you know, prompting it by typing. It's, do you remember? You probably do. A couple of years ago and up until maybe last year, there was a big push by all of the senior tech people, you know, in Silicon Valley, saying, you know, everyone will have to learn how to prompt, write prompts and code. But there was one CEO who said, no, you won't. Within 12 months, you won't have to do any of that. The AI will do it for you. And I'm guessing that's where Automated Agile is heading, is that you don't need those technical skills. You just talk to your engine, and it creates from there. Is that right? Have I got that right? Paul Glover (4:56.942) Well, I think I'm a business analyst originally and business analysis, I think comes from the place of anybody can do it, but you hire a business analyst because they've got the skills to do it in a way which is lean and not wasteful. And I think that's all prompt engineering is for me. I think anybody could go through 30 cycles of asking some, you know, an AI to produce something and it does, and it's not quite right. or they could make sure someone has got that precision of language that when they ask it a question, you're getting a very specific answer out of back of it. you know, AI likes people who help it help itself. So I think, yes, you know, you certainly could get the prompt engineering piece to be done by AI. And at some point in the future, there will be a level of understanding of the area. So it will help somewhat with that. You're never going to get to the point where precision of language doesn't matter. So I think. AiMegos (5:53.172) Hmm. Paul Glover (5:54.508) you know, maybe prompts engineering will change as a methodology, but that precision is always going to be necessary. AiMegos (6:0.158) Yeah, yeah, I mean, certainly with the work that I do, if I write a prompt, and it could be a large prompt, if I type one up, I will then ask the LLM that I'm talking with to reshape that prompt to make it tighter and more accessible to that engine. And yeah, sometimes you just look at it and go, that's a third the size of what I typed up. it works brilliantly. Paul Glover (6:28.236) Yeah. And there's a whole industry, isn't there, around prompt tuning where, you know, you, you, you might be at a great, create a great answer from a prompt, uh, but is it token efficient? You know, and I think once we get to that point, but, uh, you know, really what we're doing is we're trying to take work away, uh, from, uh, the product delivery life cycle to reproduce that productivity. we, you know, we're seeing maybe 30%, uh, increasing productivity off the back of this kind of methodology and thinking. Um, so, you know, when you're doing that, can that into creativity really. But you know in terms of prompt engineering definitely you can utilize AI to help you with that and that's what we think across the whole product delivery lifecycle it's just how to get the most out of it. What benefit can I get right now? AiMegos (7:13.569) That then leads me to think about context. And I'd be interested to know why context is so critical in AI in particular, in automated agile. Why does it become smarter? Paul Glover (7:32.972) Yeah, well, it's about making sure you ask it that very specific question again. So I think in terms of automated agile, one of the key fundamentals of it is you build a series of documentation which accurately and fully describes a product. Now that would be contrary to your traditional agile methodologies which say that you can't really think, understand what you want at the beginning of a project because who does? You want to iterate once you gather customer feedback. Well, what automated agile tries to do is it creates that 100 % understanding of where your product is right now based on the information you've got right now. So you can build that product to 100 % level and get that immediate feedback. And rather than spending weeks on your document, you want to make sure that it could be done inside the call that you're having with the customer straight away. And that's where automated agile kind of flips some of these traditional methodologies on its head where documentation might not be as important as the people and the understanding in the room. the reason for that is because of all the time that you have to spend producing that documentation. It makes it a wasteful action. Whereas when you're utilizing things like AI processes, it'll produce that documentation immediately. I you can check it immediately. And then when you're asking the AI a question in the future, it's got all of this information that it utilizes alongside what you're saying to it, to then give you that better answer. So this is where some of the prompt engineering methodologies and where you're talking, you talk about single shot prompts and stuff like that. And each of those will give you an answer and that answer might save you 30%, 40 % of the work. So what automated agile tries to do is build structures of information so that instead of that 30%, we're aiming for 60 % or 70 % by giving that additional context of what we're trying to do to the AI when it produces that answer. AiMegos (9:32.286) So then let's bring it back from a conceptual theoretical into the real world. Could you walk us through a typical day for a team that's using automated agile? Paul Glover (9:46.626) Yeah, so I would say there's no team using automated agile right now in anger. It's at the experim...

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News 20th November 2024

Nov 20, 202400:06:11Tap to summarize

Welcome to the AI in Business podcast. In this show we talk about how leaders and entrepreneurs can benefit from not only the implementation of AI, but also the innovation and growth in creative thinking that comes with it. At Aimegos we have seen time and time again how this growth in creativity creates results that directly impact on your bottom line—in a very positive way. I'm your host, Lee Hopkins. Today we have some news that will be of importance to you and the team of creatives you assemble to figure out why and how you are going to implement AI. Here are six notable AI events that have or will occur in the near past or future, relevant for CEOs and entrepreneurs in Australia: 1. Salesforce AI Demo Day in Melbourne Synopsis: Salesforce hosted an AI demo day in Melbourne, showcasing its AI-powered assistants designed to enhance customer service operations. The event featured hands-on experiences with AI agents that can manage repetitive inquiries, allowing human staff to focus on more complex tasks. Keynote speaker Rowena Westphalen discussed upcoming AI tools tailored for small and medium enterprises (SMEs) that will launch soon. Why It Matters: This event highlights the growing accessibility of AI tools for SMEs, which can significantly improve operational efficiency and customer engagement. Australian CEOs and entrepreneurs should pay attention to these developments as they can leverage AI to enhance their business processes and drive growth without the need for extensive resources. Explore more about the event here [1]. 2. Launch Your Own Successful AI App Workshop Synopsis: A workshop titled "Launch Your Own Successful AI App" is set to take place tomorrow, focusing on practical steps for entrepreneurs to develop AI applications. This event will provide insights into the AI app development process, from ideation to execution. Why It Matters: For Australian entrepreneurs looking to innovate, this workshop offers a valuable opportunity to learn from experts and network with like-minded individuals. Understanding how to create AI applications can open new revenue streams and enhance competitive advantage in the market. Check out the workshop details here [2]. 3. AI Implementation in Business Seminar Synopsis: Scheduled for November 26 in Sydney, this seminar will delve into the practical aspects of implementing AI in business operations. It aims to equip attendees with strategies to integrate AI technologies effectively. Why It Matters: As AI continues to transform industries, understanding its implementation is crucial for Australian business leaders. This seminar will provide actionable insights that can help CEOs and entrepreneurs streamline operations and improve decision-making processes. Find more information about the seminar here [2]. 4. AI and Creativity Symposium Synopsis: Taking place on Saturday at the University of New England, this symposium will explore the intersection of AI and creativity, featuring discussions on how AI can enhance creative processes in various industries. Why It Matters: For CEOs and entrepreneurs in creative sectors, this event presents an opportunity to discover how AI can be harnessed to foster innovation and creativity. Understanding these applications can lead to new business models and creative strategies. Learn more about the symposium here [2]. 5. AI Marketing and Social Media Summit Synopsis: This summit, scheduled for November 28, will focus on the role of AI in marketing and social media strategies. It will feature industry leaders discussing the latest trends and tools available for marketers. Why It Matters: As digital marketing evolves, leveraging AI tools can significantly enhance marketing effectiveness. Australian business leaders should attend to gain insights into optimizing their marketing strategies and improving customer engagement through AI. Explore the summit details here [2]. 6. Unlock the Future: Cognitive Neuroscience in the Age of AI Synopsis: This event on November 27 will discuss the implications of cognitive neuroscience in the context of AI advancements. It aims to bridge the gap between neuroscience and AI applications in business. Why It Matters: Understanding the cognitive aspects of AI can help Australian CEOs and entrepreneurs make informed decisions about AI adoption and its impact on consumer behavior. This knowledge can lead to more effective product development and marketing strategies. Find out more about the event here [2]. Learn more: Big business fills AI demo as Salesforce pledges tools for SMEs Discover Ai Events & Activities in Australia | Eventbrite Learning from AI Innovators at Global Network Week | Yale School of Management Well, that wraps up this episode of the AI in Business podcast. Subscribe to our podcast on your platform of choice and we'll jump into your feed in a week's time. Until then, take some risks because you never know what will pay off, and let us help you revolutionise your business with people-first AI. Until next week, bye... Aimegos.com

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News 13th November 2024

Nov 12, 202400:04:55Tap to summarize

Welcome to the AI in Business podcast. In this show we talk about how leaders and entrepreneurs can benefit from not only the implementation of AI, but also the innovation and growth in creative thinking that comes with it. At Aimegos we have seen time and time again how this growth in creativity creates results that directly impact on your bottom line—in a very positive way. I'm your host, Lee Hopkins. Today we have some news that will be of importance to you and the team of creatives you assemble to figure out why and how you are going to implement AI. ----- Global AI market value surpasses $196 billion, projected to grow 13x in 6 years The AI industry is experiencing explosive growth, with the global market now valued at over $196 billion and expected to increase by more than 13 times in the next six years. This rapid expansion presents significant opportunities for Australian businesses to leverage AI technologies, potentially boosting productivity, streamlining operations, and gaining a competitive edge in the global market. Netflix generates $1 billion annually from AI-powered recommendations Netflix’s use of AI for personalised content recommendations is generating $1 billion in annual revenue. This demonstrates the substantial financial impact that AI can have when applied to customer experience and engagement. Australian businesses across various sectors can learn from this example, exploring ways to implement AI-driven personalisation to enhance customer satisfaction and drive revenue growth. AI adoption by organisations set to expand at 36.6% CAGR between 2024 and 2030 The rapid growth of AI adoption by organisations is expected to continue, with a projected compound annual growth rate (CAGR) of 36.6% from 2024 to 2030. This trend underscores the importance for Australian business leaders to stay informed about AI developments and consider how they can integrate AI solutions into their operations to remain competitive in an increasingly AI-driven business landscape. Japan unveils $65 billion plan to boost chip and AI industries The Japanese government has announced a $65 billion investment plan to strengthen its semiconductor and AI industries by 2030. This significant commitment highlights the growing global focus on AI and related technologies. Australian business leaders should take note of this trend, considering how they can position their companies to benefit from similar initiatives and potential partnerships in the Asia-Pacific region. 83% of APAC C-suite executives rank generative AI among top three business priorities A recent study reveals that 83% of C-suite executives in the Asia-Pacific region consider generative AI as one of their top three business priorities. This widespread recognition of AI’s importance in the business world emphasises the need for Australian leaders to educate themselves about generative AI and explore its potential applications within their organisations to stay competitive in the regional market. Google Maps receives its biggest AI update, enhancing navigation and exploration features Google has implemented its largest-ever AI update to Google Maps, introducing more complex query capabilities and AI-curated answers for location-based questions. This development showcases how AI is transforming everyday tools used by businesses and consumers alike. Australian entrepreneurs and executives should consider how similar AI enhancements could improve their products or services, potentially opening new avenues for innovation and customer engagement. --------- Well, that wraps up this episode of the AI in Business podcast. Subscribe to our podcast on your platform of choice and we'll jump into your feed in a week's time. Until then, take some risks because you never know what will pay off, and let us help you revolutionise your business with people-first AI. Until next week, bye...

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News 5th November 2024

Nov 4, 202400:06:48Tap to summarize

Welcome to the AI in Business podcast. In this show we talk about how leaders and entrepreneurs can benefit from not only the implementation of AI, but also the innovation and growth in creative thinking that comes with it. At AiMegos we have seen time and time again how this growth in creativity creates results that directly impact on your bottom line—in a very positive way. I'm your host, Lee Hopkins. Today we have some news that will be of importance to you and the team of creatives you assemble to figure out why and how you are going to implement AI. ********************** Firstly, Open AI has launched ChatGPT Search, a direct competitor to Google Search, and a competitor to the free version of Perplexity. With ChatGPT Search you can get fast, timely answers with links to relevant web sources, which you would have previously needed to go to a search engine for. This blends the benefits of a natural language interface with the value of up-to-date sports scores, news, stock quotes, and more. Chats also now include links to sources, such as news articles and blog posts, giving you a way to learn more. OpenAI have created an extension for the Chrome browser so that ChatGPT Search—with your permission—becomes the default search engine. https://openai.com/index/introducing-chatgpt-search/ And while we are mentioning Google, Google's DeepMind team have just announced they are going to make available a watermarking tool. This will allow near-instant recognition of content that is created by artificial intelligence. Developers and businesses will get the first roll-out of the tool. https://t.co/n2aYoeJXqn Thirdly, KPMG is experimenting with AI agents — software tools that can be programmed to perform tasks on behalf of the user — as the Big Four accounting and consulting firm looks to become a leading early adopter of the technology, an executive said. The company has reportedly “prototyped and incubated” several agents, including one that is intended to support audit teams. https://www.ciodive.com/news/kpmg-testing-ai-agents/731431/ Lastly, there's a big rush by startups and other nimble players to create some tool in the Agentic space. What's 'Agentic', you might ask? Agentic AI refers to a class of artificial intelligence systems that are designed to operate autonomously, pursuing complex goals and tasks with minimal or no direct human supervision. These AI systems are capable of making decisions, planning actions, and adapting to dynamic environments based on real-time data and feedback. Agentic AI has several key components that make it so powerful, hence why the rush is on to get product out: 1. Autonomy: Agentic AI can function independently, initiating and completing tasks without constant human oversight. This allows it to handle complex workflows and decision-making processes, often in real-time environments. 2. Goal-Oriented Behavior: Unlike traditional AI, which typically follows predefined rules or responds to specific inputs, agentic AI is designed to pursue objectives proactively. It can set its own sub-goals and adjust strategies as needed to achieve broader targets. 3. Reasoning and Planning: These systems use sophisticated reasoning capabilities to break down complex tasks into smaller steps (a process sometimes referred to as “chaining”). They continuously assess their progress and adapt their plans based on new information or changing circumstances. 4. Adaptability: Agentic AI can dynamically adjust its actions in response to changes in its environment. This makes it particularly useful in scenarios where conditions are unpredictable or constantly evolving. 5. Learning and Improvement: Through techniques like reinforcement learning, agentic AI systems can improve their performance over time by learning from their interactions with the environment. Agentic AI is being deployed across various industries due to its ability to manage complex processes autonomously, such as * Robotics and Autonomous Vehicles. * Enterprise Automation: In business settings, agentic AI is used for workflow optimization, automating multi-step processes such as supply chain management or customer service operations. * Healthcare: Agentic AI can assist medical professionals by handling time-consuming tasks such as data analysis or treatment planning, allowing doctors to focus on patient care. * Customer Service: Intelligent personal assistants and chatbots powered by agentic AI provide personalized support by understanding user needs and responding proactively. You might remember back to our first AI in Business podcast where Gary Cooper discussed how bots could be revolutionised to actually be helpful, rather than their current frustratingly dumb state. https://aimegos.com/ai-in-business-podcast-001/ Well, that's a quick overview of what is happening in the world of AI and business this week. And that wraps up this episode of the AI in Business podcast. Subscribe to our podcast on your platform of choice and we'll jump into your feed in a week's time. Until then, take some risks because you never know what will pay off, and let us help you revolutionise your business with people-first AI. Until next week, bye...

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Kate Crocker: Ethical design in the age of AI

Oct 29, 202400:25:05Tap to summarize

In this conversation, Kate Crocker, an expert in dark patterns and AI, discusses the manipulative design tactics used on websites and apps that trick users into unintended actions. She explains the implications of these dark patterns for consumers, particularly in the context of data privacy and online scams. The discussion also covers how generative AI can inadvertently create dark patterns and the ethical considerations businesses must navigate when using AI. Finally, Kate highlights the upcoming regulations aimed at curbing dark patterns and promoting ethical design practices. Takeaways Dark patterns manipulate users into unintended actions. They exploit cognitive biases, leading to decision fatigue. Generative AI can create dark patterns that are hard to detect. Deepfakes pose risks of misinformation and privacy invasion. Informed consent is compromised by manipulative designs. Regulations against dark patterns are on the horizon. Consumers increasingly demand ethical practices in design. Dynamic pricing can exploit user behavior and preferences. AI's rapid data analysis can personalize dark patterns. Businesses have a unique opportunity to adopt ethical practices. Sound Bites "Dark patterns are designed tricks to manipulate users." "Dark patterns exploit cognitive biases and decision fatigue." "AI can easily create dark patterns that are hard to detect." Further resources https://www.katecrockercopywriter.com.au/dark-patterns-consultant/ (there’s a free downloadable information sheet on this page) Australia https://www.oaic.gov.au/privacy/privacy-guidance-for-organisations-and-government-agencies/guidance-on-privacy-and-the-use-of-commercially-available-ai-products https://www.industry.gov.au/publications/voluntary-ai-safety-standard/10-guardrails European Union https://artificialintelligenceact.eu/ dark patterns, AI ethics, consumer protection, legal design, ethical design, data privacy, generative AI, user experience, digital manipulation, online scams

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Bruce Welsh of 6PR interviews Lee Hopkins about AI

Oct 28, 202400:14:26Tap to summarize

In this episode of the Amigos podcast, Lee Hopkins discusses the transformative impact of artificial intelligence (AI) on businesses and individuals. He explores the evolution of AI, its current applications, and the potential future developments that could reshape industries. The conversation highlights the importance of understanding AI's capabilities, the necessity of quality input for effective output, and the implications of AI in sectors like healthcare and customer service. Lee emphasizes the need for businesses to adapt and leverage AI tools to enhance creativity, efficiency, and profitability. Takeaways AI has the potential to revolutionize business operations. The evolution of AI has made it accessible to everyone. Quality input is crucial for effective AI output. AI can significantly reduce costs for businesses. AI applications are expanding rapidly across various sectors. Healthcare professionals may need to retrain due to AI advancements. AI can outperform humans in customer service scenarios. Businesses should consider getting second opinions from AI tools. The cost of AI tools is decreasing, making them more accessible. Organizations must adapt to maximize the benefits of AI.

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All episodes

How to talk about AI without sounding foolish

Fear of AI

AI demystified: What every CEO needs to know to stay ahead

Implementing AI in business without losing staff trust

Paul Glover - Automated Agile

News 20th November 2024

News 13th November 2024

News 5th November 2024

Kate Crocker: Ethical design in the age of AI

Bruce Welsh of 6PR interviews Lee Hopkins about AI