Podcasts about ai solutions

Session 10 ‘AI Solutions for Sepsis' from the 5th World Sepsis Congress. Featuring Nathan Shapiro, Sujoy Kar, Ian Hosein, and Katherine Urbáez as your moderator.

The discussion centers around the intersection of artificial intelligence (AI), cybersecurity, and monetization strategies, emphasizing the dual challenges of protecting data and AI models while also effectively pricing these solutions. Experts Bryant Tow and James D. Wilton explore the urgent risks posed by AI, including threats to company data and the integrity of AI models. They highlight the importance of aligning technical depth with business value, particularly as AI adoption accelerates across industries.Bryant Tow, Chief Security Officer at Leapfrog Services, emphasizes the need for organizations to conduct an AI readiness assessment to understand their specific use cases and the necessary infrastructure. He argues that data classification and retention policies are crucial for effective cybersecurity, as they help organizations determine what data needs protection and how to manage it. Tow also discusses the importance of governance and user training in ensuring that AI tools are used appropriately and securely.James D. Wilton, founder of Monovate, adds that pricing strategies for cybersecurity solutions should reflect the varying levels of protection and the perceived value by different customer segments. He suggests that companies can create premium bundles for advanced features while also considering the architecture of their offerings to justify pricing. Wilton highlights the need for businesses to articulate the value of their services, especially in a landscape where clients may be hesitant to invest due to cost-cutting measures.The conversation also touches on the skills gap in the cybersecurity workforce and the potential for outsourcing as a solution. Both experts agree that effective communication between security leaders and go-to-market teams is essential for conveying the value of cybersecurity solutions to clients. They conclude that organizations must continuously demonstrate the benefits of their services to prevent customer fatigue and ensure ongoing investment in cybersecurity measures. All our Sponsors: https://businessof.tech/sponsors/ Do you want the show on your podcast app or the written versions of the stories? Subscribe to the Business of Tech: https://www.businessof.tech/subscribe/Looking for a link from the stories? The entire script of the show, with links to articles, are posted in each story on https://www.businessof.tech/ Support the show on Patreon: https://patreon.com/mspradio/ Want to be a guest on Business of Tech: Daily 10-Minute IT Services Insights? Send Dave Sobel a message on PodMatch, here: https://www.podmatch.com/hostdetailpreview/businessoftech Want our stuff? Cool Merch? Wear “Why Do We Care?” - Visit https://mspradio.myspreadshop.com Follow us on:LinkedIn: https://www.linkedin.com/company/28908079/YouTube: https://youtube.com/mspradio/Facebook: https://www.facebook.com/mspradionews/Instagram: https://www.instagram.com/mspradio/TikTok: https://www.tiktok.com/@businessoftechBluesky: https://bsky.app/profile/businessof.tech

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the crucial difference between ‘no-code AI solutions’ and ‘no work’ when using AI tools. You’ll grasp why seeking easy no-code solutions often leads to mediocre AI outcomes. You’ll learn the vital role critical thinking plays in getting powerful results from generative AI. You’ll discover actionable techniques, like using frameworks and better questions, to guide AI. You’ll understand how investing thought upfront transforms AI from a simple tool into a strategic partner. Watch the full episode to elevate your AI strategy! Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-no-code-ai-tools-sdlc.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn – 00:00 In this week’s In Ear Insights, I have a bone to pick with a lot of people in marketing around AI and AI tools. And my bone to pick is this, Katie. There isn’t a day that goes by either in Slack or mostly on LinkedIn when some person is saying, “Oh, we need a no code tool for this.” “How do I use AI in a no code tool to evaluate real estate proposals?” And the thing is, when I read what they’re trying to do, they seem to have this idea that no code equals no work. That it’s somehow magically just going to do the thing. And I can understand the past tense aversion to coding because it’s a very difficult thing to do. Christopher S. Penn – 00:49 But in today’s world with generative AI, coding is as straightforward as not coding in terms of the ability to make stuff. Because generative AI can do both, and they both have very strong prerequisites, which is you gotta think things through. It’s not no work. Neither case is it no work. Have you seen this also on the various places we hang out? Katie Robbert – 01:15 Well, first, welcome to the club. How well do your ranty pants fit? Because that’s what you are wearing today. Maybe you’re in the ranty shirt club. I don’t know. It’s… I think we were talking about this last week because I was asking—and I wasn’t asking from a ‘I don’t want to do the work’ standpoint, but I was asking from a ‘I’m not a coder, I don’t want to deal with code, but I’m willing to do the work’ standpoint. And you showed me a system like Google Colab that you can go into, you can tell it what you want to do, and you can watch it build the code. It can either keep it within the system or you can copy the code and put it elsewhere. And that’s true of pretty much any generative AI system. Katie Robbert – 02:04 You can say, “I want you to build code for me to be able to do X.” Now, the reason, at least from my standpoint, why people don’t want to do the code is because they don’t know what the code says or what it’s supposed to do. Therefore, they’re like, “Let me just avoid that altogether because I don’t know if it’s going to be right.” The stuff that they’re missing—and this is something that I said on the Doodle webinar that I did with Andy Crestodina: we forget that AI is there to do the work for us. So let the AI not only build the code, but check the code, make sure the code works, and build the requirements for the code. Say, “I want to do this thing.” “What do you, the machine, need to know about building the code?” Katie Robbert – 02:53 So you’re doing the work to build the code, but you’re not actually coding. And so I think—listen, we’re humans, we’re lazy. We want things that are plug and play. I just want to press the go button, the easy button, the old Staples button. I want to press the easy button and make it happen. I don’t want to have to think about coding or configuration or setup or anything. I just want to make it work. I just want to push the button on the blender and have a smoothie. I don’t want to think about the ingredients that go into it. I don’t want to even find a cup. I’m going to drink it straight from the blender. Katie Robbert – 03:28 I think, at least the way that I interpret it, when people say they want the no code version, they’re hoping for that kind of easy path of least resistance. But no code doesn’t mean no work. Christopher S. Penn – 03:44 Yeah. And my worry and concern is that things like the software development lifecycle exist for a reason. And the reason is so that things aren’t a flaming, huge mess. I did see one pundit quip on Threads not too long ago that generative AI may as well be called the Tactical Debt Generator because you have a bunch of people making stuff that they don’t know how to maintain and that they don’t understand. For example, when you are using it to write code, as we’ve talked about in the past, very few people ever think, “Is my code secure?” And as a result, there are a number of threads and tweets and stuff saying, “One day I coded this app in one afternoon.” Christopher S. Penn – 04:26 And then, two days later, “Hey guys, why are all these people breaking into my app?” Katie Robbert – 04:33 It’s— No, it’s true. Yeah, they don’t. It’s a very short-sighted way of approaching it. I mean, think about even all the custom models that we’ve built for various reasons. Katie GPT—when was the last time her system instructions were updated? Even Katie Artifact that I use in Claude all the time—when was the last time her… Just because I use it all the time doesn’t mean that she’s up to date. She’s a little bit outdated. And she’s tired, and she needs a vacation, and she needs a refresh. It’s software. These custom models that you’re building are software. Even if there’s no, quote unquote, “code” that you can see that you have built, there is code behind it that the systems are using that you need to maintain and figure out. Katie Robbert – 05:23 “How do I get this to work long term?” Not just “It solves my problem today, and when I use it tomorrow, it’s not doing what I need it to do.” Christopher S. Penn – 05:33 Yep. The other thing that I see people doing so wrong with generative AI—code, no code, whatever—is they don’t think to ask it thinking questions. I saw this—I was commenting on one of Marcus Sheridan’s posts earlier today—and I said that we live in an environment where if you want to be really good at generative AI, be a good manager. Provide your employee—the AI—with all the materials that it needs to be set up for success. Documentation, background information, a process, your expected outcomes, your timelines, your deliverables, all that stuff. If you give that to an employee with good delegation, the employee will succeed. If you say, “Employee, go do the thing.” And then you walk off to the coffee maker like I did in your job interview 10 years ago. Katie Robbert – 06:26 If you haven’t heard it, we’ll get back to it at some point. Christopher S. Penn – 06:30 That’s not gonna set you up for success. When I say thinking questions, here’s a prompt that anybody can use for pretty much anything that will dramatically improve your generative AI outputs. Once you’ve positioned a problem like, “Hey, I need to make something that does this,” or “I need to fix this thing,” or “Why is this leaking?”… You would say, “Think through 5 to 7 plausible solutions for this problem.” “Rank them in order of practicality or flexibility or robustness, and then narrow down your solution.” “Set to one or two solutions, and then ask me to choose one”—which is a much better process than saying, “What’s the answer?” Or “Fix my problem.” Because we want these machines to think. And if you’re saying—when people equate no code with no think and no work— Yes, to your point. Christopher S. Penn – 07:28 Exactly what you said on the Doodle webinar. “Make the machine do the work.” But you have to think through, “How do I get it to think about the work?” Katie Robbert – 07:38 One of the examples that we were going through on that same webinar that we did—myself and Andy Crestodina—is he was giving very basic prompts to create personas. And unsurprisingly… And he acknowledged this; he was getting generic persona metrics back. And we talked through—it’s good enough to get you started, but if you’re using these very basic prompts to get personas to stand in as your audience, your content marketing is also going to be fairly basic. And so, went more in depth: “Give me strong opinions on mediocre things,” which actually turned out really funny. Katie Robbert – 08:25 But what I liked about it was, sort of to your point, Chris, of the thinking questions, it gave a different set of responses that you could then go, “Huh, this is actually something that I could build my content marketing plan around for my audience.” This is a more interesting and engaging and slightly weird way of looking at it. But unless you do that thinking and unless you get creative with how you’re actually using these tools, you don’t have to code. But you can’t just say, “I work in the marketing industry. Who is my audience?” “And tell me five things that I should write about.” It’s going to be really bland; it’s going to be very vanilla. Which vanilla has its place in time, but it’s not in content marketing. Christopher S. Penn – 09:10 That’s true. Vanilla Ice, on the other hand. Katie Robbert – 09:14 Don’t get me started. Christopher S. Penn – 09:15 Collaborate and listen. Katie Robbert – 09:17 Words to live by. Christopher S. Penn – 09:20 Exactly. And I think that’s a really good way of approaching this. And it almost makes me think that there’s a lot of people who are saying, somewhat accurately, that AI is going to remove our critical thinking skills. We’re just going to stop thinking entirely. And I can see some people, to your point, taking the easy way out all the time, becoming… We talked about in last week’s podcast becoming codependent on generative AI. But I feel like the best thinkers will move their thinking one level up, which is saying, “Okay, how can I think about a better prompt or a better system or a better automation or a better workflow?” So they will still be thinking. You will still be thinking. You will just not be thinking about the low-level task, but you still have to think. Christopher S. Penn – 10:11 Whereas if you’re saying, “How can I get a no-code easy button for this thing?”… You’re not thinking. Katie Robbert – 10:18 I think—to overuse the word think— I think that’s where we’re going to start to see the innovation bell curve. We’re going to start to see people get over that curve of, “All right, I don’t want to code, that’s fine.” But can you think? But if you don’t want to code or think, you’re going to be stuck squarely at the bottom of the hill of that innovation curve. Because if you don’t want to code, it’s fine. I don’t want to code, I want nothing to do with it. That means that I have made my choice and I have to think. I have to get more creative and think more deeply about how I’m prompting, what kind of questions I’m asking, what kind of questions I want it to ask me versus I can build some code. Christopher S. Penn – 11:10 Exactly. And you’ve been experimenting with tools like N8N, for example, as automations for AI. So for that average person who is maybe okay thinking but not okay coding, how do they get started? And I’m going to guess that this is probably the answer. Katie Robbert – 11:28 It is exactly the answer. The 5Ps is a great place to start. The reason why is because it helps you organize your thoughts and find out where the gaps are in terms of the information that you do or don’t have. So in this instance, let’s say I don’t want to create code to do my content marketing, but I do want to come up with some interesting ideas. And me putting in the prompt “Come up with interesting ideas” isn’t good enough because I’m getting bland, vanilla things back. So first and foremost, what is the problem I am trying to solve? The problem I am trying to solve is not necessarily “I need new content ideas.” That is the medicine, if you will. The actual diagnosis is I need more audience, I need more awareness. Katie Robbert – 12:28 I need to solve the problem that nobody’s reading my content. So therefore, I either have the wrong audience or I have the wrong content strategy, or both. So it’s not “I need more interesting content.” That’s the solution. That’s the prescription that you get; the diagnosis is where you want to start with the Purpose. And that’s going to help you get to a better set of thinking when you get to the point of using the Platform—which is generative AI, your SEO tools, your market research, yada yada. So Purpose is “I need to get more audience, I need to get more awareness.” That is my goal. That is the problem I am trying to solve. People: I need to examine, do I have the right audience? Am I missing parts of my audience? Have I completely gone off the deep end? Katie Robbert – 13:17 And I’m trying to get everybody, and really that’s unrealistic. So that’s part of it. The Process. Well, I have to look at my market research. I have to look at my customer—my existing customer base—but also who’s engaging with me on social media, who’s subscribing to my email newsletters, and so on and so forth. So this is more than just “Give me interesting topics for my content marketing.” We’re really digging into what’s actually happening. And this is where that thinking comes into play—that critical thinking of, “Wow, if I really examine all of these things, put all of this information into generative AI, I’m likely going to get something much more compelling and on the nose.” Christopher S. Penn – 14:00 And again, it goes back to that thinking: If you know five people in your audience, you can turn on a screen recording, you can scroll through LinkedIn or the social network of your choice—even if they don’t allow data export—you just record your screen and scroll (not too fast) and then hand that to generative AI. Say, “Here’s a recording of the things that my top five people are talking about.” “What are they not thinking about that I could provide content on based on all the discussions?” So you go onto LinkedIn today, you scroll, you scroll, maybe you do 10 or 15 pages, have a machine tally up the different topics. I bet you it’s 82% AI, and you can say, “Well, what’s missing?” And that is the part that AI is exceptionally good at. Christopher S. Penn – 14:53 You and I, as humans, we are focused creatures. Our literal biology is based on focus. Machines are the opposite. Machines can’t focus. They see everything equally. We found this out a long time ago when scientists built a classifier to try to classify images of wolves versus dogs. It worked great in the lab. It did not work at all in production. And when they went back to try and figure out why, they determined that the machine was classifying on whether there was snow in the photo or not. Because all the wolf photos had snow. The machines did not understand focus. They just classified everything. So, which is a superpower we can use to say, “What did I forget?” “What isn’t in here?” “What’s missing?” You and I have a hard time that we can’t say, “I don’t know what’s missing”—it’s missing. Christopher S. Penn – 15:42 Whereas the machine could go, knowing the domain overall, “This is what your audience isn’t paying attention to.” But that’s not no thinking; that’s not no work. That’s a lot of work actually to put that together. But boy, will it give you better results. Katie Robbert – 15:57 Yeah. And so, gone are the days of being able to get by with… “Today you are a marketing analyst.” “You are going to look at my GA4 data, you are going to tell me what it says.” Yes, you can use that prompt, but you’re not going to get very far. You’re going to get the mediocre results based on that mediocre prompt. Now, if you’re just starting out, if today is Day 1, that prompt is fantastic because you are going to learn a lot very quickly. If today is Day 100 and you are still using that prompt, then you are not thinking. And what I mean by that is you are just complacent in getting those mediocre results back. That’s not a job for AI. Katie Robbert – 16:42 You don’t need AI to be doing whatever it is you’re doing with that basic prompt 100 days in. But if it’s Day 1, it’s great. You’re going to learn a lot. Christopher S. Penn – 16:52 I’m curious, what does the Day 100 prompt look like? Katie Robbert – 16:57 The Day 100 prompt could start with… “Today you are a marketing analyst.” “You are going to do the following thing.” It can start there; it doesn’t end there. So, let’s say you put that prompt in, let’s say it gives you back results, and you say, “Great, that’s not good enough.” “What am I missing?” “How about this?” “Here’s some additional information.” “Here’s some context.” “I forgot to give you this.” “I’m thinking about this.” “How do I get here?” And you just—it goes forward. So you can start there. It’s a good way to anchor, to ground yourself. But then it has to go beyond that. Christopher S. Penn – 17:36 Exactly. And we have a framework for that. Huge surprise. If you go to TrustInsights.ai/rappel, to Katie’s point: the role, the action (which is the overview), then you prime it. You should—you can and should—have a piece of text laying around of how you think, in this example, about analytics. Because, for example, experienced GA4 practitioners know that direct traffic—except for major brands—very rarely is people just typing in your web view address. Most often it’s because you forgot tracking code somewhere. And so knowing that information, providing that information helps the prompt. Of course, the evaluation—which is what Katie’s talking about—the conversation. Christopher S. Penn – 18:17 And then at the very end, the wrap-up where you say, “Based on everything that we’ve done today, come up with some system instructions that encapsulate the richness of our conversation and the final methodology that we got to the answers we actually wanted.” And then that prompt becomes reusable down the road so you don’t have to do it the same time and again. One of the things we teach now in our Generative AI Use Cases course, which I believe is at Trust Insights Use Cases course, is you can build deep research knowledge blocks. So you might say, “I’m a marketing analyst at a B2B consultancy.” “Our customers like people like this.” “I want you to build me a best practices guide for analyzing GA4 for me and my company and the kind of company that we are.” Christopher S. Penn – 19:09 “And I want to know what to do, what not to do, what things people miss often, and take some time to think.” And then you have probably between a 15- and 30-page piece of knowledge that the next time you do that prompt, you can absolutely say, “Hey, analyze my GA4.” “Here’s how we market. Here’s how we think about analytics. Here’s the best practices for GA4.” And those three documents probably total 30,000 words. And it’s at that point where it’s not… No, it is literally no code, and it’s not entirely no work, but you’ve done all the work up front. Katie Robbert – 19:52 The other thing that occurs to me that we should start including in our prompting is the three scenarios. So, basically, if you’re unfamiliar, I do a lot of work with scenario planning. And so, let’s say you’re talking about your budget. I usually do three versions of the budget so that I can sort of think through. Scenario one: everything is status quo; everything is just going to continue business as usual. Scenario two: we suddenly land a bunch of big clients, and we have a lot more revenue coming in. But with that, it’s not just that the top line is getting bigger. Katie Robbert – 20:33 Everything else—there’s a ripple effect to that. We’re going to have to staff up; we’re going to have to get more software, more server, whatever the thing is. So you have to plan for those. And then the third scenario that nobody likes to think about is: what happens if everything comes crashing down? What happens if we lose 75% of our clients? What happens if myself or Chris suddenly can’t perform our duties as co-founders, whatever it is? Those are scenarios that I always encourage people to plan for—whether it’s budget, your marketing plan, blah blah. You can ask generative AI. So if you spent all of this time giving generative AI data and context and knowledge blocks and the deep thinking, and it gives you a marketing plan or it gives you a strategy… Katie Robbert – 21:23 Take it that next step, do that even deeper thinking, and say, “Give me the three scenarios.” “What happens if I follow this plan?” “Exactly.” “What happens if you give me this plan and I don’t measure anything?” “What happens if I follow this plan and I don’t get any outcome?” There’s a bunch of different ways to think about it, but really challenge the system to think through its work, but also to give you that additional information because it may say, “You know what? This is a great thought process.” “I have more questions for you based on this.” “Let’s keep going.” Christopher S. Penn – 22:04 One of the magic questions that we use with generative AI—I use it all the time, particularly requirements gathering—is I’ll give it… Scenarios, situations, or whatever the case may be, and I’ll say… “The outcome I want is this.” “An analysis, a piece of code, requirements doc, whatever.” “Ask me one question at a time until you have enough information.” I did this yesterday building a piece of software in generative AI, and it was 22 questions in a row because it said, “I need to know this.” “What about this?” Same thing for scenario planning. Like, “Hey, I want to do a scenario plan for tariffs or a war between India and Pakistan, or generative AI taking away half of our customer base.” “That’s the scenario I want to plan for.” Christopher S. Penn – 22:52 “Ask me one question at a time.” Here’s—you give it all the knowledge blocks about your business and things. That question is magic. It is absolutely magic. But you have to be willing to work because you’re going to be there a while chatting, and you have to be able to think. Katie Robbert – 23:06 Yeah, it takes time. And very rarely at this point do I use generative AI in such a way that I’m not also providing data or background information. I’m not really just kind of winging it as a search engine. I’m using it in such a way that I’m providing a lot of background information and using generative AI as another version of me to help me think through something, even if it’s not a custom Katie model or whatever. I strongly feel the more data and context you give generative AI, the better the results are going to be. Versus—and we’ve done this test in a variety of different shows—if you just say, “Write me a blog post about the top five things to do in SEO in 2025,” and that’s all you give it, you’re going to get really crappy results back. Katie Robbert – 24:10 But if you load up the latest articles from the top experts and the Google algorithm user guides and developer notes and all sorts of stuff, you give all that and then say, “Great.” “Now break this down in simple language and help me write a blog post for the top five things that marketers need to do to rank in 2025.” You’re going to get a much more not only accurate but also engaging and helpful post because you’ve really done the deep thinking. Christopher S. Penn – 24:43 Exactly. And then once you’ve got the knowledge blocks codified and you’ve done the hard work—may not be coding, but it is definitely work and definitely thinking— You can then use a no-code system like N8N. Maybe you have an ICP. Maybe you have a knowledge block about SEO, maybe you have all the things, and you chain it all together and you say, “I want you to first generate five questions that we want answers to, and then I want you to take my ICP and ask the five follow-up questions.” “And I want you to take this knowledge and answer those 10 questions and write it to a disk file.” And you can then hit—you could probably rename it the easy button— Yes, but you could hit that, and it would spit out 5, 10, 15, 20 pieces of content. Christopher S. Penn – 25:25 But you have to do all the work and all the thinking up front. No code does not mean no work. Katie Robbert – 25:32 And again, that’s where I always go back to. A really great way to get started is the 5Ps. And you can give the Trust Insights 5P framework to your generative AI model and say, “This is how I want to organize my thoughts.” “Walk me through this framework and help me put my thoughts together.” And then at the end, say, “Give me an output of everything we’ve talked about in the 5Ps.” That then becomes a document that you then give back to a new chat and say, “Here’s what I want to do.” “Help me do the thing.” Christopher S. Penn – 26:06 Exactly. You can get a copy at Trust Insights AI 5P framework. Download the PDF and just drop that in. Say, “Help me reformat this.” Or even better, “Here’s the thing I want to do.” “Here’s the Trust Insights 5P framework.” “Ask me questions one at a time until you have enough information to fully fill out a 5P framework audit.” “For this idea I have.” A lot of work, but it’s a lot of work. If you do the work, the results are fantastic. Results are phenomenal, and that’s true of all of our frameworks. I mean, go on to TrustInsights.ai and look under the Insights section. We got a lot of frameworks on there. They’re all in PDF format. Download them from anything in the Instant Insights section. You don’t even need to fill out a form. You can just download the thing and start dropping it. Christopher S. Penn – 26:51 And we did this the other day with a measurement thing. I just took the SAINT framework right off of our site, dropped it in, said, “Make, fill this in, ask me questions for what’s missing.” And the output I got was fantastic. It was better than anything I’ve ever written myself, which is awkward because it’s my framework. Katie Robbert – 27:10 But. And this is gonna be awkwardly phrased, but you’re you. And what I mean by that is it’s hard to ask yourself questions and then answer those questions in an unbiased way. ‘Cause you’re like, “Huh, what do I want to eat today?” “I don’t know.” “I want to eat pizza.” “Well, you ate pizza yesterday.” “Should you be eating pizza today?” “Absolutely.” “I love pizza.” It’s not a helpful or productive conversation. And quite honestly, unless you’re like me and you just talk to yourself out loud all the time, people might think you’re a little bit silly. Christopher S. Penn – 27:46 That’s fair. Katie Robbert – 27:47 But you can. The reason I bring it up—and sort of… That was sort of a silly example. But the machine doesn’t care about you. The machine doesn’t have emotion. It’s going to ask you questions. It’s not going to care if it offends you or not. If it says, “Have you eaten today?” If you say, “Yeah, get off my back,” it’s like, “Okay, whatever.” It’s not going to give you attitude or sass back. And if you respond in such a way, it’s not going to be like, “Why are you taking attitude?” And it’s going to be like, “Okay, let’s move on to the next thing.” It’s a great way to get all of that information out without any sort of judgment or attitude, and just get the information where it needs to be. Christopher S. Penn – 28:31 Exactly. You can also, in your digital twin that you’ve made of yourself, you can adjust its personality at times and say, “Be more skeptical.” “Challenge me.” “Be critical of me.” And to your point, it’s a machine. It will do that. Christopher S. Penn – 28:47 So wrapping up: asking for no-code solutions is fine as long as you understand that it is not no work. In fact, it is a lot of work. But if you do it properly, it’s a lot of work the first time, and then subsequent runs of that task, like everything in the SDLC, get much easier. And the more time and effort you invest up front, the better your life is going to be downstream. Katie Robbert – 29:17 It’s true. Christopher S. Penn – 29:18 If you’ve got some thoughts about no-code solutions, about how you’re using generative AI, how you’re getting it to challenge you and get you to do the work and the thinking, and you want to share them, pop by our free Slack group. Go to TrustInsights.ai/analyticsformarketers where you and over 4,200 marketers are asking and answering each other’s questions every single day. And wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on instead, go to Trust Insights AI TI Podcast. You can find us at all the places fine podcasts are served. Thanks for tuning in. I’ll talk to you on the next one. Speaker 3 – 29:57 Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Speaker 3 – 30:50 Trust Insights also offers expert guidance on social media analytics, marketing technology and Martech selection and implementation, and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMO or Data Scientist to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In Ear Insights podcast, the Inbox Insights newsletter, the So What? Livestream, webinars, and keynote speaking. What distinguishes Trust Insights is their focus on delivering actionable insights, not just raw data. Trust Insights is adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Speaker 3 – 31:55 Data Storytelling: this commitment to clarity and accessibility extends to Trust Insights’ educational resources, which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

Maybe we should just skip the whole AGI thing? And instead focus on something ..... useful?Ruchir Puri thinks that's the way forward. Ruchir, IBM Research & IBM Fellow, knows a thing or two about AI and how to make it useful. For decades, he's helped develop the world's biggest AI breakthroughs, like IBM Watson. Don't miss this convo if you're ready to make AI a bit more useful. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the conversationUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Allocation of AGI Focus vs. AUI (Artificial Useful Intelligence)Ruchir Puri's Background in Automation and AI at IBMDiscussion of AGI's Unclear Definition and Historical Milestones (Deep Blue and Watson)Breakdown of Intelligence into IQ, EQ, and RQEmphasis on AUI's Practical Uses in Daily Life and BusinessEvolution of Human Work Due to AI AdvancementsIBM's Software Engineering Agent for Developer ProductivityImportance of Feedback Systems and Intelligent AgentsSteps for Business Leaders: Education, Strategy, and Skill DevelopmentTimestamps:00:00 Everyday AI Podcast & Newsletter03:57 Debating AGI and Scaremongering09:31 Evolution of Knowledge Work10:47 Seamless Language Generation's Impact13:57 AI's Growing Reasoning Abilities19:18 "Software's Dominance and Developer Focus"22:22 AI Solutions for Cybersecurity Challenges26:40 ChatGPT Struggles with Math29:32 Preparing Human Skills for AI's Rise30:35 "Embrace and Strategize with AI"34:00 "Subscribe for Daily AI Insights"Keywords:artificial intelligence, AI podcast, large language models, LLMs, artificial general intelligence, AGI, artificial useful intelligence, AUI, IBM, AI in business, AI strategy, AI implementation, machine learning, deep blue, jeopardy, Watson, Granite models, reasoning AI, agentic AI, AI in software development, AI tools, AI automation, generative AI, EQ, RQ, IQ, AI reasoning, AI technology, AI in careers, AI and human skills, AI in enterprises.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner

While most data scientists chase after scraps at the big business table, a hidden gold mine sits completely ignored. Small businesses are desperate for AI solutions but can't get help because everyone thinks they're "too small."The truth? These overlooked clients - representing a staggering 99.8% of all businesses - are willing to pay real money for simple AI implementations that deliver jaw-dropping ROI. We're talking five to seven-figure returns from solutions you could build in your sleep.In this episode, Heidi Araya joins Dr Genevieve Hayes to reveal exactly how data scientists can escape the soul-crushing enterprise world and build a thriving practice serving clients who actually appreciate your genius.Prepare to discover:Why AI implementations for small businesses can deliver dramatically higher ROI than enterprise solutions [12:16]The three pre-built AI solutions that consistently generate the greatest value for resource-constrained clients [12:16]A practical framework for identifying high-impact opportunities even when clients have minimal data [16:59]The "AI receptionist" solution that generated $30 million in new business from dead leads for one small client [21:19]Guest BioHeidi Araya is the CEO and chief AI consultant of BrightLogic, an AI automation agency that specializes in delivering people-first solutions that unlock the potential of small to medium sized businesses. She is also a patented inventor, an international keynote speaker and the author of two upcoming books, one on process improvement for small businesses and the other on career and personal reinvention.LinksConnect with Heidi on LinkedInBrightLogic websiteConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

In this episode of The Radical Massage Therapist Podcast, Krista chats with Brittany Long, the co-founder of Win With Systems and the self-proclaimed Queen of Evergreen. Brittany shares how massage therapists—especially introverts who hate writing emails, following up with clients, or asking for rebookings—can use AI tools like ChatGPT to streamline their communication, marketing, and admin tasks.We explore:✅ How AI can help with writing client emails, phone scripts, and treatment plans✅ Using automation to free up your schedule without sacrificing client care✅ How introverts can show up consistently in their marketing (without burning out)✅ Building a business that supports your life—not the other way around✅ Creating a “regret-free” career by intentionally designing your scheduleWhether you're drowning in admin or feeling awkward about marketing, Brittany's tips will help you use AI as your personal assistant—so you can spend more time doing what you love.

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Franchise Now AI Radio shares how AI empowers franchisees with smarter marketing. To Learn more please visit https://franchisenow.ai/ Franchise Now City: Colorado Springs Address: 860 Robbie View Website: https://franchisenow.ai

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM FULL SHOW NOTES https://www.microsoftinnovationpodcast.com/680 Microsoft's AI landscape has evolved into three distinct categories: Copilot for Microsoft 365 (M365) applications, Copilot Studio for low-code chatbot development, and Azure AI Foundry (formerly AI Studio) for pro-code flexibility with AI models. Join Nanddeep Nachan on today's Power Platform Show to learn more. TAKEAWAYs• Declarative agents provide the simplest approach to extending Copilot functionality without complex licensing• Teams toolkit in Visual Studio Code offers an easy way to create declarative agents using simple JSON configurations• Copilot Studio gives business users a drag-and-drop interface for creating virtual assistants quickly• Azure AI Foundry provides comprehensive tools for developers and data scientists building advanced AI solutions• Retrieval Augmented Generation (RAG) pattern bridges the gap between LLMs and organization-specific data• Contract management use cases demonstrate how AI can extract insights from millions of documents• Graph RAG pattern enables "global queries" that deliver insights across entire document collections• AI Foundry solutions can be deployed directly to websites, Teams apps, or Microsoft 365 Copilot• Despite impressive personal productivity gains, many organizations still struggle to find compelling enterprise-level use cases for CopilotThis year we're adding a new show to our line up - The AI Advantage. We'll discuss the skills you need to thrive in an AI-enabled world. DynamicsMinds is a world-class event in Slovenia that brings together Microsoft product managers, industry leaders, and dedicated users to explore the latest in Microsoft Dynamics 365, the Power Platform, and Copilot.Early bird tickets are on sale now and listeners of the Microsoft Innovation Podcast get 10% off with the code MIPVIP144bff https://www.dynamicsminds.com/register/?voucher=MIPVIP144bff Accelerate your Microsoft career with the 90 Day Mentoring Challenge We've helped 1,300+ people across 70+ countries establish successful careers in the Microsoft Power Platform and Dynamics 365 ecosystem.Benefit from expert guidance, a supportive community, and a clear career roadmap. A lot can change in 90 days, get started today!Support the showIf you want to get in touch with me, you can message me here on Linkedin.Thanks for listening

“Organizations need to invest in not only the AI, but the change management that goes along with that AI to help bring people along.” -  Heather Jerrehian   In this episode of the People Dividend Podcast, host Mike Horne engages with Heather Jerahian, an entrepreneurial futurist and investor, discussing her extensive experience in scaling startups and leading AI initiatives. The conversation explores the future of work, the importance of authenticity in leadership, the challenges of management in a rapidly changing environment, and the critical role of technology in workforce management. Heather shares insights from her book 'Sale to Scale' and emphasizes the need for organizations to invest in AI and change management to navigate the evolving landscape of human resources.   Key Points: Responsible AI practices are necessary to ensure ethical use of technology. AI should be seen as an enabler for human work, not a replacement. Change management is key to successfully implementing AI solutions.   Links:  Learn more about Mike Horne on Linkedin Email Mike at mike@mike-horne.com Learn More About Executive and Organization Development with Mike Horne Twitter: https://twitter.com/mikehorneauthor  Instagram: https://www.instagram.com/mikehorneauthor/,  LinkedIn Mike's Newsletter: https://www.linkedin.com/newsletters/6867258581922799617/,  Schedule a Discovery Call with Mike: https://calendly.com/mikehorne/15-minute-discovery-call-with-mike     Learn More about Heather Jerrehian LinkedIn: https://www.linkedin.com/in/heatherjerrehian X: @jerrehian Website:  https://www.sailtoscale.com/  

WHR 3.220: Navigating Solo Success with Bert terHart Episode Summary: In this episode of the Work at Home Rockstar Podcast, Tim Melanson sits down with Bert terHart — a sailor, scientist, entrepreneur, and relentless problem solver. Bert shares incredible stories of his solo, nonstop circumnavigation of the globe and a solo canoe trip across Canada, highlighting the grit and discipline needed to pull off such feats. But it doesn't stop there — he also talks about building his business LeadBrain.ai and how he's helping local businesses stay relevant and visible in today's AI-driven world. From solo adventures to smart delegation and leveraging tech, Bert's journey is an epic blend of old-school endurance and modern innovation. Who is Bert terHart? Bert terHart is a self-proclaimed soldier, sailor, scientist, adventurer, and serial entrepreneur. He's a Fellow of the Royal Canadian Geographical Society, Explorer in Residence for the BC Historical Society, and founder of the Canadian Interactive Waterways Initiative. With over 50,000 miles of solo ocean sailing and a background in math, physics, and oceanography, Bert brings a deep passion for nature, exploration, and digital innovation. As CEO of LeadBrain.ai and CTO at the Obesity Medicine and Diabetes Institute, he helps businesses connect with customers exactly when they're searching — turning visibility into results through smart use of IT and AI. Connect with Bert terHart: Website: https://bertterhart.com AI Solutions: https://leadbrain.ai LinkedIn: https://www.linkedin.com/in/bertterhart Facebook: https://www.facebook.com/the5capes Instagram: https://www.instagram.com/svseaburban Host Contact Details: Website: https://workathomerockstar.com Facebook: https://www.facebook.com/workathomerockstar Instagram: https://www.instagram.com/workathomerockstar LinkedIn: https://www.linkedin.com/in/timmelanson YouTube: https://www.youtube.com/@WorkAtHomeRockStarPodcast Twitter: https://twitter.com/workathomestar Email: tim@workathomerockstar.com In this Episode:00:00 Welcome to the Work at Home Rockstar Podcast 00:26 Meet Bert Terhart: Adventurer and Entrepreneur 02:05 Lessons from Failure: The Importance of Reaching Out to Customers 03:43 Polarizing Your Audience for Business Success 10:37 The Discipline of Working from Home 18:49 Understanding Customer Needs 19:03 Improving Market Position 19:36 Logistical Friction in Business 20:36 Leveraging AI for Business Success 21:28 AI in Customer Engagement 25:08 AI in Healthcare 26:49 AI for Small Business Growth 29:49 The Golden Age of AI 32:48 Guest Solo: Exciting Business Insights 35:11 Connecting with Bert Terhart

Michal Wachstock is a results-driven marketing leader with a proven track record of building and scaling B2B SaaS companies. From sparking ideas to driving execution, she thrives on developing go-to-market strategies, creating impactful brands and driving customer acquisition and growth. Michal's journey has included spearheading the launch of multiple startups, building high-performing marketing teams from scratch, and driving significant revenue growth through innovative marketing campaigns. With a passion for customer-centricity and a wealth of experience in brand development, digital marketing, and marketing automation, Michal won't rest until a business has achieved its full potential. Website: https://akooda.co  LinkedIn: https://www.linkedin.com/in/michal-wachstock/  YouTube: https://www.youtube.com/@akooda   Shai Alani has over twelve years in marketing, leading global marketing initiatives at Coralogix, revolutionizing AI control. He is passionate about crafting impactful growth marketing solutions in his role as VP of Marketing, encompassing global B2B efforts.  Website: https://coralogix.com/  LinkedIn: https://www.linkedin.com/in/shaialani/  Facebook: https://www.facebook.com/Coralogix/    In this episode, we uncover marketing strategies, AI's impact on marketing, and personalized tactics shared by industry experts, Michal and Shai.    Apply to join our marketing mastermind group: https://notypicalmoments.typeform.com/to/hWLDNgjz   Follow No Typical Moments at: Website: https://notypicalmoments.com/ LinkedIn: https://www.linkedin.com/company/no-typical-moments-llc/ YouTube: https://www.youtube.com/channel/UC4G7csw9j7zpjdASvpMzqUA Instagram: https://www.instagram.com/notypicalmoments Facebook: https://www.facebook.com/NTMoments

Michal Wachstock is a results-driven marketing leader with a proven track record of building and scaling B2B SaaS companies. From sparking ideas to driving execution, she thrives on developing go-to-market strategies, creating impactful brands and driving customer acquisition and growth. Michal's journey has included spearheading the launch of multiple startups, building high-performing marketing teams from scratch, and driving significant revenue growth through innovative marketing campaigns. With a passion for customer-centricity and a wealth of experience in brand development, digital marketing, and marketing automation, Michal won't rest until a business has achieved its full potential. Website: https://akooda.co  LinkedIn: https://www.linkedin.com/in/michal-wachstock/  YouTube: https://www.youtube.com/@akooda   Shai Alani has over twelve years in marketing, leading global marketing initiatives at Coralogix, revolutionizing AI control. He is passionate about crafting impactful growth marketing solutions in his role as VP of Marketing, encompassing global B2B efforts.  Website: https://coralogix.com/  LinkedIn: https://www.linkedin.com/in/shaialani/  Facebook: https://www.facebook.com/Coralogix/    In this episode, we uncover marketing strategies, AI's impact on marketing, and personalized tactics shared by industry experts, Michal and Shai.    Apply to join our marketing mastermind group: https://notypicalmoments.typeform.com/to/hWLDNgjz   Follow No Typical Moments at: Website: https://notypicalmoments.com/ LinkedIn: https://www.linkedin.com/company/no-typical-moments-llc/ YouTube: https://www.youtube.com/channel/UC4G7csw9j7zpjdASvpMzqUA Instagram: https://www.instagram.com/notypicalmoments Facebook: https://www.facebook.com/NTMoments

"Behind the scenes, it's a Climate AI. It's a very deep Climate AI engine that we have built, which drives all of these workflows." Rohit Toshniwal pulls back the curtain on the sophisticated technology needed to tackle complex environmental challenges, highlighting how Artificial Intelligence is becoming essential for managing sustainability data and driving climate action. Rohit Toshniwal is a serial tech entrepreneur and Co-Founder of Sprih, which builds a Carbon Intelligence and Management platform using Climate AI to help organizations catalyze climate action. An IIT Kanpur graduate, Rohit previously co-founded Arkin Net, acquired by VMware for over $100 million, and helped scale that business within VMware to ~$250 million in revenue. Key Insights from the Conversation:

In the current publishing industry, authors are expected to handle their own social media. If we wanted to be out there interacting with people, we probably wouldn't have picked artforms that have us sitting alone for hours everyday. What writer hasn't wished for an assistant to handle their social media? How about assistants we don't have to pay? In this episode, Kim and Renee explore how AI can lighten authors' marketing burden. They demonstrate AI tools that create marketing checklists, research Amazon keywords, build reader personas, and develop social media strategies that won't leave authors exhausted or creatively drained. Also, Renee, without any AI assistance, goes on a great rant.Remember, we have a Writers Process meetup every Wednesday. Check us out.

Today's episode is with Co-Founder, Jason Baxter, to introduce our latest venture, FOSTR AI—a company built to solve one of the most pressing challenges facing businesses today: how to implement AI in your business in a meaningful, aligned, and scalable way. We unpack the fragmented state of AI adoption across small to mid-sized businesses and explain why most organizations, despite interest, are either stuck in experimentation or using disconnected tools that don't move the business forward.  FOSTR AI is the answer to that problem—an execution intelligence layer that creates a company's “digital twin,” aligning AI usage with team structure, goals, and strategy from day one. We discuss how FOSTR helps companies: - Onboard and operationalize AI in a matter of minutes - Centralize AI usage across teams while maintaining control, security, and context - Reduce risk from siloed tools and misaligned AI use Links: FOSTR AI - https://fostrai.com/ Topics: (00:00:00) - Intro (00:00:52) - Introducing FOSTR (00:02:40) - The Challenges Businesses Face with AI Today (00:05:14) - How Companies and Employees Are Misusing AI (00:10:29) - Additional Challenges (00:12:33) - How FOSTR Is Creating Alignment Between Companies and AI Solutions (00:25:57) - Where FOSTR Is in Its Life Cycle (00:30:39) - How to Get in Touch With, Work At, or Invest in FOSTR Chris on Social Media: The Fort Podcast on Twitter/X: https://x.com/theFORTpodcast Instagram: https://www.instagram.com/thefortpodcast LinkedIn: https://bit.ly/45gIkFd   Watch The Fort on YouTube: https://bit.ly/3oynxNX Visit our website: https://bit.ly/43SOvys Leave a review on Apple: https://bit.ly/45crFD0 Leave a review on Spotify: https://bit.ly/3Krl9jO  The FORT is produced by Johnny Podcasts

Listen to this informative dialogue between Austin Walsh of Microsoft and Mauricio Ortiz, from a recent Angelbeat event. They describe the importance of human oversight of AI initiatives.

Today's guest is Ben Webster, VP of AI Solutions at NLP Logix. NLP Logix is a fast-growing AI services firm based in Florida that serves both the public and private sectors. Ben returns to the program to explore the complexities of de-identifying patient data for AI-driven healthcare applications. Hospital chains are increasingly leveraging first-party data assets to ensure compliance while maintaining the analytical power needed for AI models. However, achieving proper de-identification is often costly, time-intensive, and difficult to scale across multiple use cases. This episode is sponsored by NLP Logix. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Artificial intelligence is here, and it's changing the way school business officials operate—if they know how to use it effectively. In this episode of School Business Insider, host John Brucato sits down with Aziz Aghayev, CEO of Flowlyst, to discuss how AI is transforming school finance operations, from budget forecasting to policy creation and meeting summaries.Aziz shares: The Five Phases of AI Adoption SBOs go through How AI can boost productivity and reduce manual workload Practical use cases for ChatGPT, Gemini, Perplexity, and more The biggest misconceptions and fears about AI in education Time-saving hacks that can revolutionize your workflowAI Tools Mentioned in This Episode:

Send us a textEmily Yamasaki speaks with Expert Intelligence's Lalin Theverapperuma, Ph.D. (CEO), and Andreas "Andi" Krupke, Ph.D. (Science Officer), on the SLAS2025 exhibition floor. The duo shares the company's inspiring journey from being an Innovation AveNEW participant in 2023 to now, highlighting their innovative AI technology designed to automate analytical data interpretation in the biotech and pharma industries. The conversation covers their unique Limited Sample Model™ (LSM) technology and the challenges of transitioning from tech to biotech. Thank you to our SponsorAt Waters™, we unlock the potential of science by solving problems that matter. Our software and instruments ensure the safety of the medicines we take, the purity of the food we eat and the water we drink, and the quality and durability of products we use every day. Together with our customers, in labs around the world, we deliver scientific insights to improve human health and well-being, helping to leave the world better than we found it.Stay connected with SLAS:www.slas.orgFacebookXLinkedInInstagramYouTubeAbout SLASSLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building. Upcoming SLAS Events: SLAS Europe 2025 Conference and Exhibition 20-22 May 2025 Hamburg, Germany View the full events calendar

Welcome to another engaging episode of The SaaS CFO Podcast, where host Ben Murray sits down with Arjun Pillai, the visionary co-founder and CEO of Docket. Arjun takes us on a journey through his impressive 13-year career in the realms of sales tech, martech, and data tech. Having founded multiple companies and successfully exited them, Arjun offers a wealth of experience and insights that he's now channeling into his new venture, Docket. This episode is a treasure trove for anyone interested in the confluence of entrepreneurship and innovative technology. In their conversation, Arjun and Ben delve into the nuts and bolts of Docket's pioneering product - an AI sales engineer designed to assist B2B sales teams. As Arjun highlights, this tool aims to elevate the capacity of salespeople by enabling them to efficiently handle intricate product inquiries and competitive challenges, all while drawing from the best practices within their company. The dialogue also touches on key aspects of startup funding, AI technology, and creating a robust go-to-market strategy, making it essential listening for aspiring entrepreneurs and industry leaders. Join us as we explore Arjun's transition from a successful engineer to a seasoned entrepreneur, uncovering the lessons learned and the paths paved along the way. With Docket's promising trajectory in the AI sales landscape and Arjun's insightful perspectives, this episode promises to deliver invaluable knowledge and inspiration for listeners across the board. Tune in for a conversation that bridges innovation and strategy in the ever-evolving world of SaaS. Show Notes: 00:00 "AI Solutions for Sales Challenges" 04:26 Streamlining Sales Through Real-Time Support 09:03 CFOs Exploring GTM AI Strategies 11:19 AI Startups: Balancing Cost and Efficiency 16:00 Early Success Driven by Strong Fundamentals 19:38 Scaling GTM: Key Sales Metrics 22:58 "Prioritize Feedback For New Features" 24:02 Connect via LinkedIn or DocketAI Links: SaaS Fundraising Stories: https://www.thesaasnews.com/news/docket-raises-3-million-in-funding https://www.thesaasnews.com/news/docket-ai-raises-15-million-in-series-a Arjun Pillai's LinkedIn: https://www.linkedin.com/in/rarjunpillai/ Docket's LinkedIn: https://www.linkedin.com/company/docket-inc/ Docket's Website: https://www.docketai.com/ To learn more about Ben check out the links below: Subscribe to Ben's daily metrics newsletter: https://saasmetricsschool.beehiiv.com/subscribe Subscribe to Ben's SaaS newsletter: https://mailchi.mp/df1db6bf8bca/the-saas-cfo-sign-up-landing-page SaaS Metrics courses here: https://www.thesaasacademy.com/ Join Ben's SaaS community here: https://www.thesaasacademy.com/offers/ivNjwYDx/checkout Follow Ben on LinkedIn: https://www.linkedin.com/in/benrmurray

Send Everyday AI and Jordan a text messageMaybe we should just skip the whole AGI thing?

This episode of the podcast is sponsored by Guesty, your all-in-one platform for hospitality businesses to automate and optimize every aspect of your operations. ***Use code SSTIRCRAZY for 50% off your first annual plan***  >> Discover more about Guesty in the Virtual Vendor Showcase Brooke Pfautz is the innovative mind behind Vintory and Comparent and has been a trailblazer in the vacation rental industry for over 17 years. He's also fully immersed in AI to not only streamline operations but also supercharge growth and efficiency, particularly in owner acquisition. In this episode Brooke shares the platforms he uses the most and offers advice and recommendations on their use. Revolutionize Your Employee Onboarding with THRIVE Essentials: Faster Training, Stronger Teams, Better Results! Discover how THRIVE Essentials accelerates onboarding for new property management staff, boosting performance and reducing turnover. >> THRIVE Essentials Are you listening to this podcast on the move? Get to the show notes here: https://www.vacationrentalformula.com/VRS602  

Discover how a modern tech platform integrates traditional market data with AI to provide investment signals, optimize investments, and automate reporting in wealth management. Learn about the impact of generative AI in transforming the financial industry and why confidence in AI has surged, enabling rapid growth and better adaptation within firms. With Arianna Colombo, MDOTMLINKSMDOTM https://www.mdotm.ai/Arianna on Linkedin: https://www.linkedin.com/in/arianna-colombo-6941101a2/

If you run a franchise business and want to learn how to tap into AI tools in the most effective way, don't miss AI in Action - the latest podcast series from Franchise Marketing Radio. Find out more at https://franchisenow.ai/ Franchise Now City: Colorado Springs Address: 860 Robbie View Website: https://franchisenow.ai

Roy Derks, Developer Experience at IBM, talks about the integration of Large Language Models (LLMs) in web development. We explore practical applications such as building agents, automating QA testing, and the evolving role of AI frameworks in software development. Links https://www.linkedin.com/in/gethackteam https://www.youtube.com/@gethackteam https://x.com/gethackteam https://hackteam.io We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Emily, at emily.kochanekketner@logrocket.com (mailto:emily.kochanekketner@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understand where your users are struggling by trying it for free at [LogRocket.com]. Try LogRocket for free today.(https://logrocket.com/signup/?pdr) Special Guest: Roy Derks.

The AI market is noisy, but real business value is hard to prove. In this episode, Alon Talmor, CEO of Ask-AI, tackles the biggest challenge in AI adoption—demonstrating measurable ROI. He shares why many AI solutions fail to justify their cost, how Ask AI approaches value-driven AI, and what businesses should consider before investing.   Thanks for tuning in! Want more content from Pavilion?    New episodes of Topline drop every Sunday with new Topline Spotlight mini-episodes every Thursday. Subscribe to never miss an episode.   Stay ahead with the latest industry developments, emerging go-to-market trends, and valuable benchmarking data. Subscribe to Topline Newsletter for expert insights from Asad Zaman every Thursday.   Tune into The Revenue Leadership Podcast with Kyle Norton every Wednesday. He dives deep into the strategies and tactics that drive success as a revenue leader, featuring real operators like Jason Lemkins of SaaStr, Stevie Case of Vanta, and Ron Gabrisko of Databricks.   Your're invited! Join the free Topline Slack channel to connect with 600+ revenue leaders, share insights, and keep the conversation going beyond the podcast!   Key chapters: (00:00) - Introduction to Alon Talmor and Ask.ai (02:50) - The Evolution of AI and Its Impact on B2B Customer Experience (06:04) - Challenges in Differentiating AI Solutions (08:54) - The Importance of Value Selling in AI (11:48) - Measuring ROI and Productivity in AI (14:58) - Future Trends in AI and Customer Experience (18:09) - Consolidation of Tools and Final Thoughts

In the latest episode of Fixing Healthcare, hosts Dr. Robert Pearl and Jeremy Corr welcome Joe Petro, Corporate Vice President of Microsoft Health & Life Sciences Solutions and Platforms. A ... The post FHC #167: How Microsoft's AI solutions got a doctor home in time for dinner appeared first on Fixing Healthcare.

Join Donna Peterson on the B2B Marketing Excellence and AI Podcast as she explores the impactful uses of AI with early adopter Matthew McClosky. Matthew delves into his journey from using ChatGPT to creating custom GPTs, specifically designed to improve sales and marketing tasks. Learn how to streamline email responses, automate prospecting, and get faster, more personalized customer interactions. Discover actionable steps to implement these tools and significantly optimize your business processes. Tune in for an enlightening conversation filled with practical AI insights that you can start applying today. Timeline-- 02:44 Creating Custom GPTs- 06:21 Utilizing GPTs for Sales and Marketing- 10:32 Sharing and Collaborating with GPTs- 16:08 Future of AI in Business More information on Matthew McClosky – Connect with him on LinkedInOr view his Sales Director GPT 

AIOps is revolutionizing IT operations, enabling businesses to manage infrastructure more efficiently than ever. In this episode, we explore how automation, AI, and machine learning are reshaping IT management—driving self-healing systems, autonomous operations, and proactive performance optimization. As organizations scale, ensuring resilience, minimizing downtime, and controlling costs are more critical than ever. Join us for a forward-looking discussion on the key trends fueling AIOps adoption and the strategies IT leaders can use to future-proof their operations. Expect actionable insights on leveraging AI-driven automation for smarter, more scalable, and cost-effective IT management. Speakers: Taruna Gandhi, Head of Product Marketing for OpsRamp, Hewlett Packard Cameron Bulanda, VP of Technical Sales and Centers of Excellence, Connection Show Notes: 00:00 Introduction to AI in Operations 03:11 The Importance of Observability 05:54 Breaking Down Silos with AIOps 09:10 Real-Life Examples of Self-Healing Systems 12:02 Proactive Management with AI Insights 14:51 Leveraging Anonymized Data for Better Insights 18:05 Future of AI in Operations Management 20:49 Driving Sustainability with AI 23:59 Choosing the Right Partner for AI Solutions

Hey CX Nation,In this week's episode of The CXChronicles Podcast #255, we welcomed Tim Houlne, CEO at Humach based in Frisco, TX. Humach combines the strengths of both humans and machines to deliver exceptional customer experiences.Since first opening their doors in 1988, Humach has been at the forefront of customer experience (CX) innovation, delivering world-class call center solutions that have transformed CX for hundreds of clients worldwide.In this episode, Tim and Adrian chat through the Four CX Pillars: Team, Tools, Process & Feedback. Plus share some of the ideas that his team at Humach think through on a daily basis to build world class customer experiences.**Episode #255 Highlight Reel:**1. How Humach has been leveraging AI in contact centers for the past decade 2. Leveraging custom language models to build effective AI-powered solutions  3. Y-Combinator launched 90 digital voice companies in the last 18 months 4. Baking employee feedback into the culture of your business to drive innovation 5. Building and enriching relationships with your customers as you grow Click here to learn more about Tim HoulneClick here to learn more about HumachHuge thanks to Tim for coming on The CXChronicles Podcast and featuring his work and efforts in pushing the customer experience, customer contact & customer support space into the future.If you enjoy The CXChronicles Podcast, stop by your favorite podcast player hit the follow button and leave us a review today.For our Spotify friends, make sure you are following CXC & please leave a 5 star review so we can find new listeners & members of our community.For our Apple friends, same deal -- follow CXCP and leave us a review letting folks know why you love our customer focused content.You know what would be even better?Go tell one of your friends or teammates about CXC's content,  our strategic partners (Hubspot, Intercom, & Zendesk) + they can learn more about our CX/CS/RevOps On-Demand services & please invite them to join the CX Nation!Are you looking to learn more about the world of Customer Experience, Customer Success & Revenue Operations?Click here to grab a copy of my book "The Four CX Pillars To Grow Your Business Now" available on Amazon or the CXC website.Reach Out To CXC Today!Support the showContact CXChronicles Today Tweet us @cxchronicles Check out our Instagram @cxchronicles Click here to checkout the CXC website Email us at info@cxchronicles.com Remember To Make Happiness A Habit!!

Welcome back to this week's episode of Sit Down Startup! Today, host Adam O'Donnell sits down with Mark Doble, Co-Founder of Alexi, to explore his inspiring journey in the legal tech space and the challenges of achieving product-market fit while raising over $10 million in funding.Join us as Mark shares his experiences transitioning from law to entrepreneurship, the pivotal moments that tested his resolve, and how Alexi is revolutionizing legal research through innovative AI solutions. He emphasizes the importance of conviction, adaptability, and understanding market needs in building a successful startup.(00:00:00) The Low Points: Overcoming Adversity in the Early Days of Alexi(00:03:40) From Law School to Startup: Finding the Path to Entrepreneurship(00:09:23) The Turning Point: Achieving Product-Market Fit with Customer Validation(00:15:40) First Principles Thinking: Innovating in Legal Tech Beyond Conventional WisdomApply to the Zendesk for Startups program. Qualifying startups can use Zendesk for six months for free. Click to learn more: https://www.zendesk.com/lp/startup-partner/?ref=gen&partner_account=0016R00003GUn7OQAT

Understanding RVUs and the Future of Pediatric PaymentsIn this episode, sponsored by Hippo Health and Freed.ai, the hosts engage in a detailed conversation with Chip Hart, an expert in managing pediatric practices. They discuss the concept of Relative Value Units (RVUs), their origins, and their impact on pediatricians and primary care physicians. Chip explains how RVUs affect billing and physician compensation, the disparities they introduce, and their contribution to physician burnout. The discussion also explores alternative payment models, such as value-based care, and the complexities of implementing them in pediatric settings. The episode concludes with insights into the future of pediatric compensation and the importance of recognizing and properly valuing primary care in pediatrics.00:00 Introduction and Sponsor Message00:46 Welcoming Chip Hart02:03 Understanding RVUs05:33 Impact of RVUs on Pediatricians08:47 Challenges with Value-Based Care18:21 Disparities in Healthcare23:57 Physician Burnout and Systemic Issues32:29 AI Solutions and Future Outlook33:23 Fee-for-Service Model Concerns34:30 Misunderstandings and Overbilling in Medical Practices35:12 Specialist Overuse and Financial Implications37:24 RVU Impact on Pediatric Practices40:12 Medicaid and Medicare Payment Structures44:14 Challenges with RVU-Based Compensation55:12 Value-Based Contracts and Pediatric Care01:02:21 Direct Primary Care and Financial Models01:09:04 Final Thoughts and Call to ActionSupport the show

Bio   Bala has rich experience in retail technology and process transformation. Most recently, he worked as a Principal Architect for Intelligent Automation, Innovation & Supply Chain in a global Fortune 100 retail corporation. Currently he works for a luxury brand as Principal Architect for Intelligent Automation providing technology advice for the responsible use of technology (Low Code, RPA, Chatbots, and AI). He is passionate about technology and spends his free time reading, writing technical blogs and co-chairing a special interest group with The OR Society.   Interview Highlights 02:00 Mentors and peers 04:00 Community bus 07:10 Defining AI 08:20 Contextual awareness 11:45 GenAI 14:30 The human loop 17:30 Natural Language Processing 20:45 Sentiment analysis 24:00 Implementing AI solutions 26:30 Ethics and AI 27:30 Biased algorithms 32:00 EU AI Act  33:00 Responsible use of technology   Connect   Bala Madhusoodhanan on LinkedIn     Books and references   ·       https://nymag.com/intelligencer/article/ai-artificial-intelligence-chatbots-emily-m-bender.html  - NLP   ·       https://www.theregister.com/2021/05/27/clearview_europe/  - Facial Technology Issue   ·       https://www.designnews.com/electronics-test/apple-card-most-high-profile-case-ai-bias-yet  - Apple Card story   ·       https://www.ft.com/content/2d6fc319-2165-42fb-8de1-0edf1d765be3  - Data Centre growth   ·       https://www.technologyreview.com/2024/02/06/1087793/what-babies-can-teach-ai/   ·       Independent Audit of AI Systems -   ·       Home | The Alan Turing Institute   ·       Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World, Marco Iansiti & Karim R. Lakhani   ·       AI Superpowers: China, Silicon Valley, and the New World, Kai-Fu Lee   ·       The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You, Mike Walsh   ·       Human+Machine: Reimagining Work in the Age of AI, Paul R Daugherty, H. James Wilson   ·       Superintelligence: Paths, Dangers, Strategies, Nick Bostrom   ·       The Alignment Problem: How Can Artificial Intelligence Learn Human Values, Brian Christian   ·       Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI, Reid Blackman   ·       Wanted: Human-AI Translators: Artificial Intelligence Demystified, Geertrui Mieke De Ketelaere   ·       The Future of Humanity: Terraforming Mars, Interstellar Travel, Immortality, and Our Destiny Beyond, Michio Kaku, Feodor Chin et al  Episode Transcript Intro: Hello and welcome to the Agile Innovation Leaders podcast. I'm Ula Ojiaku. On this podcast I speak with world-class leaders and doers about themselves and a variety of topics spanning Agile, Lean Innovation, Business, Leadership and much more – with actionable takeaways for you the listener. Ula Ojiaku So I have with me here, Bala Madhusoodhanan, who is a principal architect with a global luxury brand, and he looks after their RPA and AI transformation. So it's a pleasure to have you on the Agile Innovation Leaders podcast, Bala, thank you for making the time. Bala Madhusoodhanan It's a pleasure to have a conversation with the podcast and the podcast audience, Ula. I follow the podcast and there have been fantastic speakers in the past. So I feel privileged to join you on this conversation. Ula Ojiaku Well, the privilege is mine. So could you start off with telling us about yourself Bala, what have been the key points or the highlights of your life that have led to you being the Bala we know now? Bala Madhusoodhanan It's putting self into uncharted territory. So my background is mechanical engineering, and when I got the job, it was either you go into the mechanical engineering manufacturing side or the software side, which was slightly booming at that point of time, and obviously it was paying more then decided to take the software route, but eventually somewhere the path kind of overlapped. So from a mainframe background, started working on supply chain, and then came back to optimisation, tied back to manufacturing industry. Somewhere there is an overlap, but yeah, that was the first decision that probably got me here. The second decision was to work in a UK geography, rather than a US geography, which is again very strange in a lot of my peers. They generally go to Silicon Valley or East Coast, but I just took a choice to stay here for personal reasons. And then the third was like the mindset. I mean, I had over the last 15, 20 years, I had really good mentors, really good peers, so I always had their help to soundboard my crazy ideas, and I always try to keep a relationship ongoing. Ula Ojiaku What I'm hearing is, based on what you said, lots of relationships have been key to getting you to where you are today, both from mentors, peers. Could you expand on that? In what way? Bala Madhusoodhanan The technology is changing quite a lot, at least in the last 10 years. So if you look into pre-2010, there was no machine learning or it was statistics. People were just saying everything is statistics and accessibility to information was not that much, but post 2010, 2011, people started getting accessibility. Then there was a data buzz, big data came in, so there were a lot of opportunities where I could have taken a different career path, but every time I was in a dilemma which route to take, I had someone with whom either I have worked or who was my team lead or manager to guide me to tell me, like, take emotion out of the decision making and think in a calm mind, because you might jump into something and you might like it, you might not like it, you should not regret it. So again, over the course of so many such decisions, my cognitive mind has also started thinking about it. So those conversations really help. And again, collective experience. If you look into the decision making, it's not just my decision, I'm going through conversations that I had with people where they have applied their experience, so it's not just me or just not one situation, and to understand the why behind that, and that actually helps. In short, it's like a collection of conversations that I had with peers. A few of them are visionary leaders, they are good readers. So they always had a good insight on where I should focus, where I shouldn't focus, and of late recently, there has been a community bus. So a lot of things are moving to open source, there is a lot of community exchange of conversation, the blogging has picked up a lot. So, connecting to those parts also gives you a different dimension to think about. Ula Ojiaku So you said community bus, some of the listeners or people who are watching the video might not understand what you mean by the community bus. Are you talking about like meetups or communities that come around to discuss shared interests? Bala Madhusoodhanan If you are very much specifically interested in AI, or you are specifically interested in, power platform or a low code platform, there are a lot of content creators on those topics. You can go to YouTube, LinkedIn, and you get a lot of information about what's happening. They do a lot of hackathons, again, you need to invest time in all these things. If you don't, then you are basically missing the boat, but there are various channels like hackathon or meetup groups, or, I mean, it could be us like a virtual conversation like you and me, we both have some passionate topics, that's why we resonate and we are talking about it. So it's all about you taking an initiative, you finding time for it, and then you have tons and tons of information available through community or through conferences or through meetup groups. Ula Ojiaku Thanks for clarifying. So, you said as well, you had a collection of conversations that helped you whenever you were at a crossroad, some new technology or something emerges or there's a decision you had to make and checking in with your mentors, your peers and your personal Board of Directors almost, that they give you guidance. Now, looking back, would you say there were some turns you took that knowing what you know now, you would have done differently? Bala Madhusoodhanan I would have liked to study more. That is the only thing, because sometimes the educational degree, even though without a practical knowledge has a bigger advantage in certain conversation, otherwise your experience and your content should speak for you and it takes a little bit of effort and time to get that trust among leaders or peers just to, even them to trust saying like, okay, this person knows what he's talking about. I should probably trust rather than, someone has done a PhD and it's just finding the right balance of when I should have invested time in continuing my education, if I had time, I would have gone back two years and did everything that I had done, like minus two years off-set it by two years earlier. It would have given me different pathways. That is what I would think, but again, it's all constraints. I did the best at that point in time with whatever constraints I had. So I don't have any regret per se, but yeah, if there is a magic wand, I would do that. Ula Ojiaku So you are a LinkedIn top voice from AI. How would you define AI, artificial intelligence? Bala Madhusoodhanan I am a bit reluctant to give a term Artificial Intelligence. It's in my mind, it is Artificial Narrow Intelligence, it's slightly different. So let me start with a building block, which is machine learning. So machine learning is like a data labeller. You go to a Tesco store, you read the label, you know it is a can of soup because you have read the label, your brain is not only processing that image, it understands the surrounding. It does a lot of things when you pick that can of soup. You can't expect that by just feeding one model to a robot. So that's why I'm saying like it's AI is a bit over glorified in my mind. It is artificial narrow intelligence. What you do to automate certain specific tasks using a data set which is legal, ethical, and drives business value is what I would call machine learning, but yeah, it's just overhyped and heavily utilised term AI. Ula Ojiaku You said, there's a hype around artificial intelligence. So what do you mean by that? And where do you see it going? Bala Madhusoodhanan Going back to the machine learning definition that I said, it's basically predicting an output based on some input. That's as simple as what we would say machine learning. The word algorithm is basically something like a pattern finder. What you're doing is you are giving a lot of data, which is properly labelled, which has proper diversity of information, and there are multiple algorithms that can find patterns. The cleverness or engineering mind that you bring in is to select which pattern or which algorithm you would like to do for your use case. Now you're channelling the whole machine learning into one use case. That's why I'm going with the term narrow intelligence. Computers can do brilliant jobs. So you ask computers to do like a Rubik's cubes solving. It will do it very quickly because the task is very simple and it is just doing a lot of calculation. You give a Rubik's cube to a kid. It has to apply it. The brain is not trained enough, so it has to cognitively learn. Maybe it will be faster. So anything which is just pure calculation, pure computing, if the data is labelled properly, you want to predict an outcome, yes, you can use computers. One of the interesting videos that I showed in one of my previous talks was a robot trying to walk across the street. This is in 2018 or 19. The first video was basically talking about a robot crossing a street and there were vehicles coming across and the robot just had a headbutt and it just fell off. Now a four year old kid was asked to walk and it knew that I have to press a red signal. So it went to the signal stop. It knew, or the baby knew that I can only walk when it is green. And then it looks around and then walks so you can see the difference – a four year old kid has a contextual awareness of what is happening, whereas the robot, which is supposed to be called as artificial intelligence couldn't see that. So again, if you look, our human brains have been evolved over millions of years. There are like 10 billion neurons or something, and it is highly optimised. So when I sleep, there are different set of neurons which are running. When I speak to you, my eyes and ears are running, my motion sensor neurons are running, but these are all highly optimised. So the mother control knows how much energy should be sent on which neuron, right, whereas all these large language models, there is only one task. You ask it, it's just going to do that. It doesn't have that intelligence to optimise. When I sleep, maybe 90 percent of my neurons are sleeping. It's getting recharged. Only the dream neurons are working. Whereas once you put a model live, it doesn't matter, all the hundred thousand neurons would run. So, yeah, it's in very infancy state, maybe with quantum computing, maybe with more power and better chips things might change, but I don't see that happening in the next five to 10 years. Ula Ojiaku Now, what do you say about Gen AI? Would you also classify generative AI as purely artificial neural intelligence? Bala Madhusoodhanan The thing with generative AI is you're trying to generalise a lot of use cases, say ChatGPT, you can throw in a PDF, you can ask something, or you can say, hey, can you create a content for my blog or things like that, right? Again, all it is trying to do is it has some historical content with which it is trying to come up with a response. So the thing that I would say is humans are really good with creativity. If a problem is thrown at a person, he will find creative ways to solve it. The tool with which we are going to solve might be a GenAI tool, I don't know, because I don't know the problem, but because GenAI is in a hype cycle, every problem doesn't need GenAI, that's my view. So there was an interesting research which was done by someone in Montreal University. It talks about 10 of the basic tasks like converting text to text or text to speech and with a generative AI model or multiple models, because you have a lot of vendors providing different GenAI models, and then they went with task specific models and the thing that they found was the task specific models were cheap to run, very, very scalable and robust and highly accurate, right. Whereas GenAI, if, when you try to use it and when it goes into a production ready or enterprise ready and if it is used by customers or third party, which are not part of your ecosystem, you are putting yourself in some kind of risk category. There could be a risk of copyright issues. There could be a risk of IP issues. There could be risk of not getting the right consent from someone. I can say, can you create an image of a podcaster named Ula? You never know because you don't remember that one of your photos on Google or Twitter or somewhere is not set as private. No one has come and asked you saying, I'm using this image. And yeah, it's finding the right balance. So even before taking the technology, I think people should think about what problem are they trying to solve? In my mind, AI or artificial intelligence, or narrow intelligence can have two buckets, right. The first bucket is to do with how can I optimise the existing process? Like there are a lot of things that I'm doing, is there a better way to do it? Is there an efficient way to do it? Can I save time? Can I save money? Stuff like that. So that is an optimisation or driving efficiency lever. Other one could be, I know what to do. I have a lot of data, but I don't have infrastructure or people to do it, like workforce augmentation. Say, I have 10 data entry persons who are graduate level. Their only job is to review the receipts or invoices. I work in FCA. I have to manually look at it, approve it, and file it, right? Now it is a very tedious job. So all you are doing is you are augmenting the whole process with an OCR engine. So OCR is Optical Character Recognition. So there are models, which again, it's a beautiful term for what our eyes do. When we travel somewhere, we get an invoice, we exactly know where to look, right? What is the total amount? What is the currency I have paid? Have they taken the correct credit card? Is my address right? All those things, unconsciously, your brain does it. Whereas our models given by different software vendors, which have trained to capture these specific entities which are universal language, to just pass, on data set, you just pass the image on it. It just picks and maps that information. Someone else will do that job. But as part of your process design, what you would do is I will do the heavy lifting of identifying the points. And I'll give it to someone because I want someone to validate it. It's human at the end. Someone is approving it. So they basically put a human in loop and, human centric design to a problem solving situation. That's your efficiency lever, right? Then you have something called innovation level - I need to do something radical, I have not done this product or service. Yeah, that's a space where you can use AI, again, to do small proof of concepts. One example could be, I'm opening a new store, it's in a new country, I don't know how the store layout should look like. These are my products. This is the store square footage. Can you recommend me the best way so that I can sell through a lot? Now, a visual merchandising team will have some ideas on where the things should be, they might give that prompt. Those texts can be converted into image. Once you get the base image, then it's human. It's us. So it will be a starting point rather than someone implementing everything. It could be a starting point. But can you trust it? I don't know. Ula Ojiaku And that's why you said the importance of having a human in the loop. Bala Madhusoodhanan Yeah. So the human loop again, it's because we humans bring contextual awareness to the situation, which machine doesn't know. So I'll tie back this to the NLP. So Natural Language Processing, it has two components, so you have natural language understanding and then you have natural language generation. When you create a machine learning model, all it is doing is, it is understanding the structure of language. It's called form. I'm giving you 10,000 PDFs, or you're reading a Harry Potter book. There is a difference between you reading a Harry Potter book and the machine interpreting that Harry Potter book. You would have imagination. You will have context of, oh, in the last chapter, we were in the hilly region or in a valley, I think it will be like this, the words like mist, cold, wood. You started already forming images and visualising stuff. The machine doesn't do that. Machine works on this is the word, this is a pronoun, this is the noun, this is the structure of language, so the next one should be this, right? So, coming back to the natural language understanding, that is where the context and the form comes into play. Just think of some alphabets put in front of you. You have no idea, but these are the alphabet. You recognise A, you recognise B, you recognise the word, but you don't understand the context. One example is I'm swimming against the current. Now, current here is the motion of water, right? My current code base is version 01. I'm using the same current, right? The context is different. So interpreting the structure of language is one thing. So, in natural language understanding, what we try to do is we try to understand the context. NLG, Natural Language Generation, is basically how can I respond in a way where I'm giving you an answer to your query. And this combined is NLP. It's a big field, there was a research done, the professor is Emily Bender, and she one of the leading professors in the NLP space. So the experiment was very funny. It was about a parrot in an island talking to someone, and there was a shark in between, or some sea creature, which basically broke the connection and was listening to what this person was saying and mimicking. Again, this is the problem with NLP, right? You don't have understanding of the context. You don't put empathy to it. You don't understand the voice modulation. Like when I'm talking to you, you can judge what my emotion cues are, you can put empathy, you can tailor the conversation. If I'm feeling sad, you can put a different spin, whereas if I'm chatting to a robot, it's just going to give a standard response. So again, you have to be very careful in which situation you're going to use it, whether it is for a small team, whether it is going to be in public, stuff like that. Ula Ojiaku So that's interesting because sometimes I join the Masters of Scale strategy sessions and at the last one there was someone whose organisational startup was featured and apparently what their startup is doing is to build AI solutions that are able to do sentiment analysis. And I think some of these, again, in their early stages, but some of these things are already available to try to understand the tone of voice, the words they say, and match it with maybe the expression and actually can transcribe virtual meetings and say, okay, this person said this, they looked perplexed or they looked slightly happy. So what do you think about that? I understand you're saying that machines can't do that, but it seems like there are already organisations trying to push the envelope towards that direction. Bala Madhusoodhanan So the example that you gave, sentiment of the conversation, again, it is going by the structure or the words that I'm using. I am feeling good. So good, here is positive sentiment. Again, for me the capability is slightly overhyped, the reason being is it might do 20 percent or 30 percent of what a human might do, but the human is any day better than that particular use case, right? So the sentiment analysis typically works on the sentiment data set, which would say, these are the certain proverbs, these are the certain types of words, this generally referred to positive sentiment or a good sentiment or feel good factor, but the model is only good as good as the data is, right? So no one is going and constantly updating that dictionary. No one is thinking about it, like Gen Z have a different lingo, millennials had a different lingo. So, again, you have to treat it use case by use case, Ula. Ula Ojiaku At the end of the day, the way things currently are is that machines aren't at the place where they are as good as humans. Humans are still good at doing what humans do, and that's the key thing. Bala Madhusoodhanan Interesting use case that I recently read probably after COVID was immersive reading. So people with dyslexia. So again, AI is used for good as well, I'm not saying it is completely bad. So AI is used for good, like, teaching kids who are dyslexic, right? Speech to text can talk, or can translate a paragraph, the kid can hear it, and on the screen, I think one note has an immersive reader, it actually highlights which word it is, uttering into the ears and research study showed that kids who were part of the study group with this immersive reading audio textbook, they had a better grasp of the context and they performed well and they were able to manage dyslexia better. Now, again, we are using the technology, but again, kudos to the research team, they identified a real problem, they formulated how the problem could be solved, they were successful. So, again, technology is being used again. Cancer research, they invest heavily, in image clustering, brain tumours, I mean, there are a lot of use cases where it's used for good, but then again, when you're using it, you just need to think about biases. You need to understand the risk, I mean, everything is risk and reward. If your reward is out-paying the minimum risk that you're taking, then it's acceptable. Ula Ojiaku What would you advise leaders of organisations who are considering implementing AI solutions? What are the things we need to consider? Bala Madhusoodhanan Okay. So going back to the business strategy and growth. So that is something that the enterprises or big organisations would have in mind. Always have your AI goals aligned to what they want. So as I said, there are two buckets. One is your efficiency driver, operational efficiency bucket. The other one is your innovation bucket. Just have a sense check of where the business wants to invest in. Just because AI is there doesn't mean you have to use it right. Look into opportunities where you can drive more values. So that would be my first line of thought. The second would be more to do with educating leaders about AI literacy, like what each models are, what do they do? What are the pitfalls, the ethical awareness about use of AI, data privacy is big. So again, that education is just like high level, with some examples on the same business domain where it has been successful, where it has been not so successful, what are the challenges that they face? That's something that I would urge everyone to invest time in. I think I did mention about security again, over the years, the practice has been security is always kept as last. So again, I was fortunate enough to work in organisations where security first mindset was put in place, because once you have a proof of value, once you show that to people, people get excited, and it's about messaging it and making sure it is very secured, protecting the end users. So the third one would be talking about having secure first design policies or principles. Machine learning or AI is of no good if your data quality is not there. So have a data strategy is something that I would definitely recommend. Start small. I mean, just like agile, you take a value, you start small, you realise whether your hypothesis was correct or not, you monitor how you performed and then you think about scale just by hello world doesn't mean that you have mastered that. So have that mindset, start small, monitor, have constant feedback, and then you think about scaling. Ula Ojiaku What are the key things about ethics and AI, do you think leaders should be aware of at this point in time? Bala Madhusoodhanan So again, ethical is very subjective. So it's about having different stakeholders to give their honest opinion of whether your solution is the right thing to do against the value of the enterprise. And it's not your view or my view, it's a consent view and certain things where people are involved, you might need to get HR, you might need to get legal, you might need to get brand reputation team to come and assist you because you don't understand the why behind certain policies were put in place. So one is, is the solution or is the AI ethical to the core value of the enterprise? So that's the first sense check that you need to do. If you pass that sense check, then comes about a lot of other threats, I would say like, is the model that I'm using, did it have a fair representation of all data set? There's a classic case study on one of a big cloud computing giant using an AI algorithm to filter resumes and they had to stop it immediately because the data set was all Ivy League, male, white, dominant, it didn't have the right representation. Over the 10 years, if I'm just hiring certain type of people, my data is inherently biased, no matter how good my algorithm is, if I don't have that data set. The other example is clarify AI. They got into trouble on using very biased data to give an outcome on some decision making to immigration, which has a bigger ramification. Then you talk about fairness, whether the AI system is fair to give you an output. So there was a funny story about a man and a woman in California living together, and I think the woman wasn't provided a credit card, even though everything, the postcode is the same, both of them work in the same company, and it was, I think it has to do with Apple Pay. Apple Pay wanted to bring in a silver credit card, Apple card or whatever it is, but then it is so unfair that the women who was equally qualified was not given the right credit limit, and the bank clearly said the algorithm said so. Then you have privacy concern, right? So all these generic models that you have that is available, even ChatGPT for that matter. Now you can chat with ChatGPT multiple times. You can talk about someone like Trevor Noah and you can say hey, can you create a joke? Now it has been trained with the jokes that he has done, it might be available publicly. But has the creator of model got a consent saying, hey Trevor, I'm going to use your content so that I can give better, and how many such consent, even Wikipedia, if you look into Wikipedia, about 80 percent of the information is public, but it is not diversified. What I mean by that is you can search for a lot of information. If the person is from America or from UK or from Europe, maybe from India to some extent, but what is the quality of data, if you think about countries in Africa, what do you think about South America? I mean, it is not representing the total diversity of data, and we have this large language model, which has been just trained on that data, right? So there is a bias and because of that bias, your outcome might not be fair. So these two are the main things, and of course the privacy concern. So if someone goes and says, hey, you have used my data, you didn't even ask me, then you're into lawsuit. Without getting a proper consent, again, it's a bad world, it's very fast moving and people don't even, including me, I don't even read every terms and condition, I just scroll down, tick, confirm, but those things are the things where I think education should come into play. Think about it, because people don't understand what could go wrong, not to them, but someone like them. Then there is a big fear of job displacement, like if I put this AI system, what will I do with my workforce? Say I had ten people, you need to think about, you need to reimagine your workplace. These are the ten jobs my ten people are doing. If I augment six of those jobs, how can I use my ten resources effectively to do something different or that piece of puzzle is always, again, it goes back to the core values of the company, what they think about their people, how everything is back, but it's just that needs a lot of inputs from multiple stakeholders. Ula Ojiaku It ties back to the enterprise strategy, there is the values, but with technology as it has evolved over the years, things will be made obsolete, but there are new opportunities that are created, so moving from when people travelled with horses and buggies and then the automotive came up. Yes, there wasn't as much demand for horseshoes and horses and buggies, but there was a new industry, the people who would mechanics or garages and things like that. So I think it's really about that. Like, going back to what you're saying, how can you redeploy people? And that might involve, again, training, reskilling, and investing in education of the workforce so that they're able to harness AI and to do those creative things that you've emphasised over this conversation about human beings, that creative aspect, that ability to understand context and nuance and apply it to the situation. Bala Madhusoodhanan So I was fortunate to work with ForHumanity, an NGO which basically is trying to certify people to look into auditing AI systems. So EU AI Act is now in place, it will be enforced soon. So you need people to have controls on all these AI systems to protect - it's done to protect people, it's done to protect the enterprise. So I was fortunate enough to be part of that community. I'm still working closely with the Operation Research Society. Again, you should be passionate enough, you should find time to do it, and if you do it, then the universe will find a way to give you something interesting to work with. And our society, The Alan Turing Institute, the ForHumanity Society, I had a few ICO workshops, which was quite interesting because when you hear perspectives from people from different facets of life, like lawyers and solicitors, you would think, ah, this statement, I wouldn't interpret in this way. It was a good learning experience and I'm sure if I have time, I would still continue to do that and invest time in ethical AI. As technology, it's not only AI, it's ethical use of technology, so sustainability is also part of ethical bucket if you look into it. So there was an interesting paper it talks about how many data centres have been opened between 2018 to 2024, which is like six years and the power consumption has gone from X to three times X or two times X, so we have opened a lot. We have already caused damage to the environment with all these technology, and just because the technology is there, it doesn't mean you have to use it, but again, it's that educational bit, what is the right thing to do? And even the ESG awareness, people are not aware. Like now, if you go to the current TikTok trenders, they know I need to look into certified B Corp when I am buying something. The reason is because they know, and they're more passionate about saving the world. Maybe we are not, I don't know, but again, once you start educating and, telling those stories, humans are really good, so you will have a change of heart. Ula Ojiaku What I'm hearing you say is that education is key to help us to make informed choices. There is a time and place where you would need to use AI, but not everything requires it, and if we're more thoughtful in how we approach, these, because these are tools at the end of the day, then we can at least try to be more balanced in the risks and taking advantage of opportunities versus the risks around it and the impact these decisions and the tools that we choose to use make on the environment. Now, what books have you found yourself recommending most to people, and why? Bala Madhusoodhanan Because we have been talking on AI, AI Superpower is one book which was written by Kai-Fu Lee. There is this book by Brian Christian, The Alignment Problem: Machine Learning and Human Values alignment of human values and machine it was basically talking about what are the human values? Where do you want to use machine learning? How do you basically come up with a decision making, that's a really interesting read. Then there is a book called Ethical Machines by Reid Blackman. So it talks about all the ethical facets of AI, like biases, fairnesses, like data privacy, transparency, explainability, and he gives quite a detail, example and walkthrough of what that means. Another interesting book was Wanted: Human-AI Translators: Artificial Intelligence Demystified by a Dutch professor, again, really, really lovely narration of what algorithms are, what AI is, where, and all you should think about, what controls and stuff like that. So that is an interesting book. Harvard Professor Kahrim Lakhani, he wrote something called, Competing in the Age of AI, that's a good book. The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You by Mike Walsh is another good book, which I finished a couple of months back. Ula Ojiaku And if the audience wants to find you, how can they reach out to you? Bala Madhusoodhanan They can always reach out to me at LinkedIn, I would be happy to touch base through LinkedIn. Ula Ojiaku Awesome. And do you have any final words and or ask of the audience? Bala Madhusoodhanan The final word is, again, responsible use of technology. Think about not just the use case, think about the environmental impact, think about the future generation, because I think the damage is already done. So, at least not in this lifetime, maybe three or four lifetimes down the line, it might not be the beautiful earth that we have. Ula Ojiaku It's been a pleasure, as always, speaking with you, Bala, and thank you so much for sharing your insights and wisdom, and thank you for being a guest on the Agile Innovation Leaders Podcast. Bala Madhusoodhanan Thank you, lovely conversation, and yeah, looking forward to connecting with more like minded LinkedIn colleagues. Ula Ojiaku That's all we have for now. Thanks for listening. If you liked this show, do subscribe at www.agileinnovationleaders.com or your favourite podcast provider. Also share with friends and do leave a review on iTunes. This would help others find this show. I'd also love to hear from you, so please drop me an email at ula@agileinnovationleaders.com Take care and God bless!   

Dr. John Gatta, CEO of the ECRA Group, discusses AI solutions for schools, specifically AI assistants. As part of an expanded partnership with IASA, ECRA has developed three AI assistants to help school districts in the areas of the Illinois School Code, Parent Questions and Human Resources.

Joining us today is Adi Bathla, CEO of Revv, an AI-powered platform that's transforming how collision repair shops approach ADAS calibration. Adi and his team recently raised over $20 million to expand their operations and revolutionize the way shops handle this critical service. In this episode, we'll explore the incredible opportunities ADAS calibration presents for collision repair businesses, discuss how Revv's AI solutions are simplifying the process, and uncover strategies for shops to maximize profitability in this evolving space. 

Send us a textArtificial intelligence is destined to play a big role in the pharmaceutical industry in 2025.With this rapid growth, what specific changes can we expect in patient support and pharmaceutical marketing?And how will that impact healthcare costs and patient experience?In this episode of the HealthBiz Podcast, guest William Grambley, CEO of AllazoHealth, discusses how artificial intelligence and patient-level data can lower operating costs, improve medication adherence, and create tailored solutions for patients at every stage of their journey.TOPICS(0:23) Intro(1:02) Background on William Grambley(2:34) How Naval Service Shaped William Grambley(3:23) The Role of Experience and Work History(6:38) What Brought William to AllazoHealth(9:05) Understanding Compliance, Persistence, and Adherence(10:36) Examining Low Levels of Adherence(12:28) How Issues with Medication Adherence Have Changed Over Time(15:00) Distinguishing Between Adherence and Therapy Initiation(17:32) The Importance of Personalization(20:35) The Future of Pharma and AI in 2025(25:02) Dynamic Change and Personalization(27:36) GLP-1s and Adherence(30:30) Book Recommendations from William Grambley

We finally chased down the smart and savvy Rob Quast, Principal Technologist at Pure, to discuss the latest trends in the tech world around AI, Networking and Cloud storage. Our conversation kicks off with Rob's journey, from his time at ePlus and working in sys admin roles, to a memorable experience at Pure's NYC Accelerate event where he saw the stock exchange firsthand. We touch on the various aspects of a PT's role, including Rob's experience showing demos and helping customers understand complex solutions. Our conversation shifts to some of Rob's most passionate work, including involvement in a large AI solution for Coreweave. He walks through the intricacies of a massive deal and how it required close collaboration with the product management team, post-validation work, and strategic networking. Rob also shares insights from a hyperscaler win for Pure Storage, explaining what "hyperscaler" means and how they're used in the industry. We dive into the technical details of large AI deals, such as GPUDirect, and discuss how Pure can better connect with networking professionals. A key theme here is the intersection of data storage and networking, with Rob revealing why NVMe TCP is a game-changer for the future of cloud infrastructure, particularly when compared to technologies like Infiniband. We close with conversation looking toward the future, exploring the realities of cloud storage and hybrid cloud solutions, and what customers are trying to achieve and the challenges they face. The episode wraps up with a focus on object storage, where Rob discusses how Pure Storage's Fusion platform helps manage global namespaces and facilitates multi-tenant cloud environments.

Data-Driven AI Solutions Transform Cognitive Care: How VitalCaring Enhances Patient Outcomes, Supports Clinicians, and Tackles Healthcare's Pressing Challenges Host: Megan Antonelli Guest: Janice Riggins Explore how VitalCaring is pioneering AI-driven cognitive care to meet the growing challenges of Alzheimer's, dementia, and other cognitive impairments. By integrating advanced technology with a patient-centered approach, VitalCaring enhances patient outcomes and empowers clinicians with tools for real-time progress tracking, supporting their role in delivering exceptional care. Join Megan Antonelli and her guest Chief Clinical Officer Janice Riggins who explains how these solutions not only bolster the patient and caregiver experience but also align with the values-based care standards enabling sustainable, quality care that adapts to the evolving needs of patients. VitalCaring's initiative prioritizes measurable outcomes through data-backed cognitive therapy and expands resources for patients while upholding excellence in care. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen

In this episode, Scott Becker sits down with Dr. Darryl Williams, CEO and Founder of Partsol (Partnership Solutions International). Dr. Williams shares insights on the challenges of navigating AI hype, the innovative development of their Absolute Truth Algorithms, and much more.

The future of business is a conversation. In this episode of The Catalyst by Softchoice, Heather Haskin and Craig McQueen, Vice President of AI Solutions at Softchoice, dive into how conversational AI is reshaping industries and redefining success.  From smarter customer support to groundbreaking innovations, discover why this technology is more than just talk—it's a game-changer. With real-world examples and insights into overcoming challenges, this episode is your ultimate guide to navigating the AI revolution.  Featuring: Craig McQueen, Softchoice Vice President of AI Solutions The Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology.

In this episode, Scott Becker sits down with Dr. Darryl Williams, CEO and Founder of Partsol (Partnership Solutions International). Dr. Williams shares insights on the challenges of navigating AI hype, the innovative development of their Absolute Truth Algorithms, and much more.

Send us a textIn episode 242 of Beyond The Story, Sebastian Rusk interviews Zulfiya Forsythe, the CEO and Founder of Omadli Group, as she shares her inspiring journey from being a corporate accountant to venturing into the world of IT and data analytics.Tune in to hear how her passion for improving efficiency led to the creation of a company that empowers others to harness the power of data and technology.TIMESTAMPS[00:01:04] Journey from accounting to IT.[00:07:11] Love for numbers and creativity.[00:08:52] Veterinary clinics and data management.[00:14:02] AI chatbot solutions for veterinary.[00:15:37] AI solutions for business processes.QUOTES"People come to you for expertise and they rely on you to kind of provide that and be self-sourced and dependent on solving these problems." - Zulfiya Forsythe“Let's take a look at the processes that are taking a long time on your end… And let's figure out the kind of workflow that we can set up for you so you can scale your business so you can also educate your team on the AI solutions as well.” - Zulfiya Forsythe“AI is definitely not going anywhere. Looks like it's here to stay, whether we like it or not.” - Sebastian Rusk==========================Need help launching your podcast?Schedule a Free Podcast Strategy Call TODAY!PodcastLaunchLabNow.com==========================SOCIAL MEDIA LINKSSebastian RuskInstagram: https://www.instagram.com/podcastlaunchlab/Facebook: Facebook.com/sruskLinkedIn: LinkedIn.com/in/sebastianrusk/YouTube: Youtube.com/@PodcastLaunchLabZulfiya ForsytheInstagram: https://www.instagram.com/zulfiyaforsythe/LinkedIn: https://www.linkedin.com/in/zulfiya-forsythe-akbarova-cpa-0214b98/WEBSITEOmadli Group: https://omadligroup.com/==========================PAYING RENT? Earn airlines when you do with the Bilt Rewards MastercardAPPLY HERE: https://bilt.page/r/2H93-5474

FEATURING:* Ginger Armbruster, Chief Privacy Officer, City of Seattle IT* Ed Odom, Race and Social Justice Lead, City of Seattle IT* Ana LaNasa-Selvidge, Organizational Change Management Lead, City of Seattle IT* Greg Smith, Chief Information Security Officer, City of Seattle IT* Michael Cruz, Director of Data and AI, SLED, MicrosoftIN THIS EPISODE, YOU'LL LEARN:* How the City of Seattle is approaching AI adoption with a focus on responsible use, data privacy, and equity.* The unique privacy challenges AI poses for city governments, especially concerning data protection and maintaining public trust.* Why organizational change management is essential for the successful implementation of new technologies and securing employee buy-in.* Strategies for identifying and addressing potential biases in AI systems and guaranteeing equitable service delivery for all communities.* The importance of collaboration and transparent communication in navigating the complexities of AI and cybersecurity in the public sector.TIMESTAMPS* (00:00) Intro & Guest Introductions* (05:22) Cybersecurity Landscape and Vision for AI* (09:30) AI as a "Glitter Bomb" and Unique Privacy Challenges* (13:46) AI Solutions for City Governments & Lessons Learned* (18:32) Change Management for Successful Tech Adoption* (21:48) Ensuring All Voices are Heard and Included with AI* (27:22) AI and the Evolution of Cybersecurity* (30:48) The Importance of Data Stewardship for AI Initiatives* (32:32) Addressing Public Record Requests and Data Transparency with AI* (36:44) Strategies for Fostering Innovation and Adaptability in City Government* (40:48) Addressing Potential Biases in AI Systems & Ensuring EquityLINKS MENTIONED* Government AI Coalition* Department of Homeland Security's AI Safety and Security Board* Microsoft Copilot* City of Seattle Privacy Program* Seattle Race and Social Justice InitiativeWhenever you're ready, there are 4 ways you can connect with TechTables:1. The TechTables Newsletter: Join our thriving community of senior technology leaders by subscribing to the TechTables Newsletter. Gain early access to the latest episodes, industry insights, and exclusive event updates.2.

In the fast-paced world of startups, innovation and empathy are crucial for success. On the latest episode of Talking Too Loud, Savage and Sylvie dive into Castmagic, the customer-centric company that is leveraging AI to reimagine content workflows. Tune in to learn how Co-Founders Blaine Bolus and Ramon Barrios, used a podcast collaboration as a launchpad for a business infused with problem-driven development maintaining creative freedom. Links to Learn More:Follow Blaine on LinkedInFollow Ramon on LinkedInFollow Savage on LinkedInSubscribe to Talking Too Loud on WistiaWatch on YouTubeFollow Talking Too Loud on InstagramFollow Talking Too Loud on TikTokLove what you heard? Leave us a review! On AppleOn Spotify

In the fast-paced world of startups, innovation and empathy are crucial for success. On the latest episode of Talking Too Loud, Savage and Sylvie dive into Castmagic, the customer-centric company that is leveraging AI to reimagine content workflows. Tune in to learn how Co-Founders Blaine Bolus and Ramon Barrios, used a podcast collaboration as a launchpad for a business infused with problem-driven development maintaining creative freedom. Links to Learn More:Follow Blaine on LinkedInFollow Ramon on LinkedInFollow Savage on LinkedInSubscribe to Talking Too Loud on WistiaWatch on YouTubeFollow Talking Too Loud on InstagramFollow Talking Too Loud on TikTokLove what you heard? Leave us a review! On AppleOn Spotify

  If you're feeling overwhelmed by the daily tasks and struggling to stay organized, then you are not alone! Are you spending hours searching for important files and documents, only to end up frustrated and stressed? It's time to enhance your productivity and business efficiency. Let's find effective strategies to overcome these challenges and take your business to the next level! Uncover the unexpected twist in this business owner's journey that will leave you inspired and rethinking your approach to challenges. Get ready to witness a transformation that defies all odds and sets the bar high for business resilience. Find out how this entrepreneur's unique experiences have shaped his approach to problem-solving and business success. Stay tuned to discover the powerful lesson that changed everything and propelled him to new heights. Don't miss out on this game-changing insight that will reshape your perspective on business and personal growth. In this part 2 of 2 episodes of The Modern Selling Podcast, Mario Martinez Jr. discusses with Trebot Johns topics such as overcoming business challenges and seizing opportunities. Drawing from his experience as the founder of Vengreso and FlyMSG, Mario infuses the conversations with a personal touch, making the content highly relatable and practical for small business owners. From the significance of reframing setbacks to the implementation of AI-driven solutions for increased productivity, the episode offers a diverse range of insights. Through a blend of personal narratives, pragmatic approaches, and forward-thinking perspectives, the episode equips small business owners with enhanced problem-solving abilities and resilience. Whether it's gaining insights into organizational methods, capitalizing on opportunities, or embracing innovative technologies, this episode presents a wealth of valuable takeaways for navigating the complexities of modern business. Whatever you do, you better do that 110% or don't expect to win. That's just how I view things. - Mario Martinez Jr. In this episode, you will be able to: Master Strategies for Overcoming Business Challenges: Learn how to navigate and conquer common hurdles in business to achieve long-term success. Harness the Benefits of AI in Lead Generation: Discover how AI can revolutionize your lead generation efforts, leading to increased efficiency and higher quality leads. Streamline Sales Prospecting Automation: Uncover tips for automating your sales prospecting process to save time and increase productivity. Embrace the Importance of Organization in Business Success: Explore the vital role of organization in achieving sustainable growth and efficiency in your business. Navigate the Transition from Service to SaaS Model: Gain insights on successfully transitioning your business from a service-based model to a SaaS model for enhanced scalability and profitability. The key moments in this episode are: 00:00:00 - Opportunity over Why Me 00:00:31 - Leadfeeder: The Secret Weapon 00:01:08 - Revolutionizing Lead Generation 00:01:44 - Part Two of Trebor Johns Interview 00:02:24 - Organizational Strategies 00:15:03 - The Shift to SaaS 00:16:32 - Overcoming Adversity 00:18:22 - Seizing Opportunities 00:24:12 - Embracing Challenges 00:27:56 - Personal Growth and Parenting 00:28:40 - The Impact of Childhood Experiences on Entrepreneurial Mindset 00:30:26 - Instilling Work Ethic in the Next Generation 00:33:05 - Teaching Responsibility and Value 00:36:01 - Homeschooling and Career Exposure 00:39:47 - Collaborative Podcast Opportunity 00:41:20 - Challenges of SMMAs 00:42:25 - Benefits of AI Solutions 00:43:17 - Importance of AI in Business 00:45:36 - Building Scalable Solutions 00:46:43 - Conclusion and Call to Action Timestamped summary of this episode: 00:00:00 - Opportunity over Why Me Grant Cardone's message about putting in effort and seizing opportunities over asking "why me" is emphasized. The focus shifts to taking action and making the most of opportunities. 00:00:31 - Leadfeeder: The Secret Weapon A brief introduction to Leadfeeder, a tool for identifying website visitors, tracking behavior, and integrating with CRMs for efficient lead engagement. The focus is on providing detailed insights and prioritizing sales efforts. 00:01:08 - Revolutionizing Lead Generation A call to revolutionize lead generation with Leadfeeder for targeted and successful lead engagement. The emphasis is on leveraging customizable notifications and lead scoring to change the game for sales. 00:01:44 - Part Two of Trevor Johns Interview Mario Martinez Jr. introduces part two of the podcast interview with Trebor Johns. He highlights the importance of listening to part one, which covers various topics related to business ownership, sales challenges, and prospecting. 00:02:24 - Organizational Strategies Mario Martinez Jr. shares insights into his organized approach to file structures, email management, and workflow organization. The focus is on creating a highly structured system to facilitate efficient storage and retrieval of information. 00:15:03 - The Shift to SaaS Mario discusses the changing landscape of software development, the speed of development, and the importance of having a sellable SaaS product before investing. 00:16:32 - Overcoming Adversity Mario shares his personal story of being the first in his family to go to college and the challenges he faced in the college application process. 00:18:22 - Seizing Opportunities Mario reflects on the moment he got accepted into UC Berkeley and the valuable lesson he learned about making the most of opportunities. 00:24:12 - Embracing Challenges Mario discusses the importance of focusing on what to do with an opportunity rather than questioning why it was given, emphasizing the need to give 110% in all aspects of life. 00:27:56 - Personal Growth and Parenting Mario shares his experience as a single father and his efforts to guide his son's focus on education, business, and extracurricular activities for the future. 00:28:40 - The Impact of Childhood Experiences on Entrepreneurial Mindset Mario Martinez Jr. shares how his upbringing and family struggles shaped his strong work ethic and entrepreneurial mindset. He emphasizes the importance of experiencing hardship to build character and determination in young entrepreneurs. 00:30:26 - Instilling Work Ethic in the Next Generation Martinez discusses the challenge of instilling a strong work ethic in his privileged sons and shares his decision to let go of their gardener, opting to do yard work as a family. He believes in not paying for household tasks but incentivizing learning and creativity. 00:33:05 - Teaching Responsibility and Value Martinez discusses the importance of not paying children for basic family responsibilities but offering incentives for learning and creativity. He emphasizes the value of teaching children about hard work, responsibility, and the real-life skills needed for success. 00:36:01 - Homeschooling and Career Exposure Martinez shares his approach to homeschooling his son and exposing him to diverse career opportunities. He discusses the decision to allow his son to explore business and marketing courses as an alternative to a challenging cybersecurity course, emphasizing the importance of early exposure to different career paths. 00:39:47 - Collaborative Podcast Opportunity Martinez proposes republishing the conversation on his podcast, highlighting the value he sees in the discussion. He also offers to share the episode on his platforms and encourages ongoing collaboration. 00:41:20 - Challenges of SMMAs The speaker discusses the challenges of social media marketing agencies (SMMAs), such as inability to guarantee results and high client turnover within 90 days. 00:42:25 - Benefits of AI Solutions The conversation shifts to the benefits of AI solutions, including the potential to reduce employee count and improve efficiency in lead generation and outreach. 00:43:17 - Importance of AI in Business The speaker emphasizes the importance of AI in optimizing business processes and staying ahead of competitors who are already leveraging these technologies for maximum ROI. 00:45:36 - Building Scalable Solutions The focus is on building scalable solutions using engineering blueprints and pods, with an emphasis on automating and optimizing different aspects of the business. 00:46:43 - Conclusion and Call to Action The podcast episode concludes with a call to action for listeners to connect on LinkedIn and engage with the host, Mario Martinez Jr., while also promoting the host's SaaS product and encouraging listeners to leave a review on iTunes. Mastering Strategies for Overcoming Business Challenges Effective problem-solving skills are crucial for small business owners to navigate challenges successfully. By mastering strategies for overcoming obstacles, entrepreneurs can enhance their resilience and adaptability in the ever-changing business landscape. With the right approach, businesses can turn setbacks into opportunities for growth and innovation. Harnessing the Benefits of AI Incorporating AI technologies can revolutionize business operations, offering efficiency and accuracy in various processes. Small business owners can harness the benefits of AI to streamline tasks, improve decision-making, and enhance customer experiences. By embracing AI, companies can stay competitive and expand their capabilities in the digital age. Streamlining Sales Prospecting Automation Automating sales prospecting can significantly boost efficiency and productivity for small businesses. By streamlining processes through automation, owners can save time, reduce errors, and focus on high-value tasks. Leveraging technology for sales prospecting can result in improved lead generation, better customer relationships, and ultimately, increased sales revenue. The resources mentioned in this episode are: Connect with Mario on LinkedIn for more engaging content related to the Modern Selling podcast, for more insights, and discussions related to sales and marketing. Download FlyMSG for free to save 20 hours or more in a month and increase your productivity. Give the Modern Selling podcast a five-star rating and review on iTunes to show your support. Reach out to Viking AI Solutions for automation solutions and AI-driven services to optimize your business processes.  

Did you know how AI is revolutionizing drug discovery and diagnosis in healthcare?Are you curious about how real-world data is helping researchers understand disease progression?Have you ever wondered what it takes to transform vast clinical data into actionable healthcare insights?What role should AI play in determining the best treatments for complex health issues?Hey there, tech enthusiasts!