Podcasts about Generative

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What if the next big leap in business AI isn't generative at all, but predictive? That's the question at the heart of my conversation with Zohar Bronfman, CEO and co-founder of Pecan AI, a company helping business teams forecast outcomes with precision and turn historical data into future insights. Zohar explains why he believes predictive AI will deliver far greater enterprise value than the generative models dominating headlines. He points to research showing that most generative AI projects fail to produce ROI, while predictive systems built on a company's own data can directly improve revenue, reduce churn, and guide smarter decisions. With Pecan's no-code platform, marketing and operations teams can now create predictive models without needing data scientists—bridging the gap between technical expertise and business execution. Through stories like Little Spoon's, a direct-to-consumer baby food brand that used Pecan AI to identify and retain at-risk customers, Zohar illustrates how predictive analytics turns data into real business impact. He also shares common mistakes companies make when implementing AI—starting with unclear objectives and misaligned resources—and why success depends on defining the problem before choosing the tool. Looking ahead, Zohar envisions predictive AI as the backbone of every organization, shifting business intelligence from reactive analysis to proactive action. As companies move beyond dashboards and toward dynamic decision-making, predictive insights may soon become as fundamental as spreadsheets. So, if your company could anticipate every challenge before it happened, how different would your strategy look? And are business leaders finally ready to treat predictive AI as core infrastructure rather than a passing trend? Share your thoughts after the episode.

Every day, billions of searches flow through Google, making it not just the world's most popular search engine, but one of history's most valuable products. Yet for the first time in nearly 30 years, the company's dominance is under threat. Generative artificial intelligence tools like Open AI's ChatGPT and Perplexity are changing how people find information. On the latest episode of the Bold Names podcast, Liz Reid, VP, head of Google Search, speaks to WSJ's Christopher Mims and Tim Higgins about transforming search for the age of AI. After more than two decades inside the company, Reid says that Google has weathered disruption before and believes this moment will expand, not erode, how people explore the web. But can Google Search survive in a world of AI chatbots and answer engines? To watch the video version of this episode, visit our WSJ Podcasts YouTube channel or the video page of WSJ.com. Check Out Past Episodes: Condoleezza Rice on Beating China in the Tech Race: 'Run Hard and Run Fast' The Google-Backed Startup Taking on Elon Musk in Humanoid Robotics Reid Hoffman Says AI Isn't an ‘Arms Race,' but America Needs to Win Why IBM's CEO Thinks His Company Can Crack Quantum Computing Let us know what you think of the show. Email us at BoldNames@wsj.com Sign up for the WSJ's free Technology newsletter. Read Christopher Mims's Keywords column. Read Tim Higgins's column.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Leadership is rapidly evolving as artificial intelligence becomes deeply integrated into how organizations operate and make decisions. In a world where volatility, uncertainty, complexity, and ambiguity are the norm, leaders are being challenged to not only understand the role of AI—but also to harness it in ways that enhance what makes leadership truly human. This episode dives into why leaders can no longer afford to treat AI as a separate technical domain, but rather as a strategic partner that augments decision making, stretches creativity, and humanizes leadership itself. As generative AI rapidly advances, the question is not whether leaders should use these tools, but how to do so thoughtfully, ethically, and effectively. This conversation explores how leaders can remain at the center, leverage augmentation, and make deliberate choices that will define competitive advantage and organizational health in the next decade. The episode also emphasizes the necessity of skepticism, risk awareness, and the cultivation of skills—like “human calming”—that will set exceptional leaders apart in an AI-rich world. Timestamped Overview [00:05:27] Introduction to AI and Leadership: Exploring why AI is now essential to leadership development and future success.[00:07:00] The Human Core of Leadership: Discussing the enduring need for human-centered leadership—augmented, not replaced, by technology.[00:08:34] Evolution of Leadership Skills: How classic leadership skills stand the test of time, but require a generative AI lens.[00:09:34] Rethinking “Cyborg Leadership”: Moving beyond science fiction to practical digital augmentation for leaders.[00:11:46] Developing the 10 AI-Augmented Leadership Skills: Why these skills matter and the unique place of “human calming.”[00:15:06] The Role of Human Calming: Centering leaders' intention and composure in an AI-driven world.[00:17:36] The Value of Skepticism: Why questioning, challenging, and stretching assumptions is vital in adopting new technology.[00:19:17] Embracing vs. Rejecting AI: Strategies for experimenting, learning, and building organizational trust with emerging tools.[00:24:00] Facing Risks and Unknowns: Assessing current and future risks—including cyber threats and over-focusing on efficiency.[00:30:03] Effectiveness vs. Efficiency: Shifting the leadership focus toward innovation, not just automation.[00:34:03] All Hands on Deck: Why AI is a human and organizational story—not just a technical one.[00:35:12] Future-Back Thinking: Blending human and machine, and why leaders must choose to play and prototype.[00:39:44] Managing the Noise: How scalable foresight and intentional augmentation can help leaders cut through information overload.[00:43:35] Practical Takeaways: Real-life examples of how leaders can use AI tools to augment creativity and effectiveness.[00:46:22] Embracing Skeptical Foresight: Encouraging leaders to challenge assumptions and stretch their strategic thinking.[00:50:02] Don't Get Discouraged: The learning curve of AI and the importance of hands-on experimentation. For the complete show notes be sure to check out our website: https://leaddontboss.com/357

As people move away from traditional search engines and turn to AI tools for answers, Leah Nurik, Co-Founder and CEO of Brandi.ai, joins host Mike Maynard to explore how this change is transforming the way brands build visibility. Leah shares how her background in tech and agency leadership led to the creation of Brandi, a platform that helps companies influence how AI engines like ChatGPT, Gemini, and Claude understand and present their brands. She explains why Generative Engine Optimization (GEO) is emerging as the new SEO, how brands can take control of their visibility in AI-driven search, and what it takes to stay relevant as the rules of digital discovery evolve. Leah also discusses the human side of marketing in the AI era, and why critical thinking, creativity, and authenticity still matter as much as data and algorithms.   About Brandi Brandi is the first intelligence-driven platform built on Generative Engine Optimization for brand visibility. It helps improve brand presence in AI-generated answers from engines like ChatGPT, Claude, Gemini, and Perplexity. In today's landscape—where brand discovery increasingly happens through generative AI—Brandi provides the insights and tools to help your company earn recognition as a trusted answer.   About Leah Nurik Leah Nurik is CEO and Co-Founder of Brandi. Leah has worked with over 400 growth-stage software companies in her 20-plus year career. She's held senior strategy, product, and marketing leadership positions at Motorola, Symbol Technologies, Infowave, and others. She also founded and led Gabriel Marketing Group, an award-winning global public relations, branding, and integrated marketing agency focused on B2B SaaS companies. Leah's expertise spans digital, public relations, content marketing, product marketing, and go-to-market strategy.   Time Stamps 00:00:17 – Guest Introduction: Leah Nurik 00:02:07 – Jumping from agency leadership to developing Brandi 00:03:19 – What is GEO 00:09:13 – How can brands use Brandi to boost AI visibility 00:15:45 – What markets does Brandi support 00:16:38 – What is Brandi's go-to-market strategy 00:18:34 – The future of AI search 00:23:52 – Best Marketing Advice Received by Andy 00:24:22 – Advice for New Marketers 00:26:07 – Contact details and Brandi demos Quotes “The paradigm of internet search is completely shifting. If you're not on the train, you're not leaving the station.” Leah Nurik, Co-Founder and CEO at Brandi. “Generative AI search will overtake traditional search. Ignoring it is like buying a horse when everyone else is driving a car.” Leah Nurik, Co-Founder and CEO at Brandi. “AI can get you about 85% of the way there, but you still need that human overlay to make the content authentic and mission-driven.” Leah Nurik, Co-Founder and CEO at Brandi. “The marketers who will thrive in the age of AI are the ones who can think critically, solve complex problems, and bring human creativity to technology.” Leah Nurik, Co-Founder and CEO at Brandi. “Brandi allows you not just to measure and monitor your brand's performance, but also to influence how AI defines your market and how you're represented in those conversations.” Leah Nurik, Co-Founder and CEO at Brandi. “Our codified intelligence engine is what sets Brandi apart. It decodes customer pain points, listens to market conversations, and delivers real, directional advice marketers can act on.” Leah Nurik, Co-Founder and CEO at Brandi. Follow Leah: Leah Nurik on LinkedIn: https://www.linkedin.com/in/leahgabriel/ Brandi's website: https://mybrandi.ai/ Brandi on LinkedIn: https://www.linkedin.com/company/mybrandi/ Brandi on X: https://x.com/mybrandi_ai   Follow Mike: Mike Maynard on LinkedIn: https://www.linkedin.com/in/mikemaynard/ Napier website: https://www.napierb2b.com/ Napier LinkedIn: https://www.linkedin.com/company/napier-partnership-limited/   If you enjoyed this episode, be sure to subscribe to our podcast for more discussions about the latest in Marketing B2B Tech and connect with us on social media to stay updated on upcoming episodes. We'd also appreciate it if you could leave us a review on your favourite podcast platform. Want more? Check out Napier's other podcast - The Marketing Automation Moment: https://podcasts.apple.com/ua/podcast/the-marketing-automation-moment-podcast/id1659211547

The evolving role of technology in modern defense environments, highlighting innovations in communications, automation, and open-source frameworks. Drawing from personal experience, the conversation emphasizes how real-world conflicts are reshaping how tech is deployed, adopted, and understood across military operations.  This week, Dave, Esmee, and Rob speak with Ben Sparke, Enterprise Azure Cloud & AI Specialist for UK Defence at Microsoft, about  how his military background informs a human-centered approach to technology in the evolving defence sector—highlighting the shift from mission-driven to tech-driven innovation.  TLDR:00:37 – Introduction of Ben Sparke and face-to-face podcasting02:40 – Rob gets confused about Digital Twins representing you in court08:15 – Tech's evolving role in defence, with Ben 34:41 – Why improvisation and human adaptability matter 43:30 – Ben's hundred-mile bike race over the weekend  Guest Ben Sparke: https://www.linkedin.com/in/ben-sparke/ HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/ ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini 

On this episode of the Scouting For Growth podcast, Sabine VdL talks to Bobbie Shrivastav, co-founder and CEO of Solvrays about building AI-driven workflows that aim to eliminate 70% of manual back office work with governance, auditability, and with human-in-the-loop controls directly built in. They also talk about what makes vertical AI for insurance defensible and measurable, compressing sales and implementation cycles without cutting corners on risk, change management, and how to augment teams as talent retires while new talent ramps up. KEY TAKEAWAYS When the work comes into an organisation, not everything is digital. Things are still mailed, the first help we provide is extracting the information from those manual sources and place it with the right person in their case management system. That alone eliminates 5-7 touch points. When an agent sends an email we're able to get a new business application, we're able to extract the information, we understand that this is a new business applications, and we can take that data and integrate it into the new business solution. Before, someone would have checked an email, gone to the new business application and keyed that in so work could move in. We've eliminated that complex new business touch point. 74% of our industry is still tackling legacy. Customers don't care if you're still using mainframes, they shouldn't feel a difference. We're using agentic AI as a connector to legacy systems, we're also doing database to database connectors, and for newer systems we're using APIs. We eliminate a dependency factor and empowered IT to work with new technologies, so they're not dependent on us. But the business and IT partnership with any project, whether it's our solution or another, is the key to success. BEST MOMENTS ‘We want to be a ray of hope for the operations staff for back office.' ‘What makes us superior, from an industry point of view, is that we've innovated in this space for the last 10 years, we understand operations intimately.' ‘Once a signature is signed, our goal is to do one workflow in two weeks, not months or years, weeks.' ‘Where I've seen most anxiety in business and IT is in implementation, it can drain your team. Our goal is: If we can build our orchestration layer the right way you don't have to be so tense.' ABOUT THE GUESTS Bobbie Shrivastav is founder and managing principal of Solvrays. Previously, she was co-founder and CEO of Docsmore, where she introduced an interactive, workflow-driven document management solution to optimize operations. She then co-founded Benekiva, where, as COO, she spearheaded initiatives to improve efficiency and customer engagement in life insurance. She co-hosts the Insurance Sync podcast with Laurel Jordan, where they explore industry trends and innovations. She is co-author of the book series "Momentum: Makers and Builders" with Renu Ann Joseph. LinkedIn ABOUT THE HOST Sabine is a corporate strategist turned entrepreneur. She is the CEO and Managing Partner of Alchemy Crew a venture lab that accelerates the curation, validation, & commercialization of new tech business models. Sabine is renowned within the insurance sector for building some of the most renowned tech startup accelerators around the world working with over 30 corporate insurers, accelerated over 100 startup ventures. Sabine is the co-editor of the bestseller The INSURTECH Book, a top 50 Women in Tech, a FinTech and InsurTech Influencer, an investor & multi-award winner. Twitter LinkedIn Instagram Facebook  TikTok Email Website This Podcast has been brought to you by Disruptive Media. https://disruptivemedia.co.uk/

Shane H. Tepper is a creative director and content strategist who has established himself as a leader in generative engine optimization (GEO). With over 15 years of experience in film, advertising, and B2B technology, he focuses on enhancing brand visibility and narrative control across AI-native platforms. Shane emphasizes the importance of strategic openness in decision-making, advocating for a thoughtful evaluation of opportunities that can lead to transformative outcomes for brands navigating the complexities of the AI landscape. His expertise extends to advising organizations on GEO strategy, AI-native content development, and scalable content operations, positioning him as a valuable resource for brands looking to optimize their storytelling in an AI-driven world. Shane's recent work includes authoring a foundational white paper on GEO and leading AI discoverability audits, all aimed at helping brands effectively engage with consumers in an evolving digital environment. His insights reflect a commitment to blending creativity with technology, ensuring that brands can thrive amidst rapid changes. For those interested in exploring Shane H. Tepper's insights further, his book, Dwelling in a Place of Yes: The Surprising Psychology Behind Fear, Opportunity, and Smarter Choices, offers a deep dive into decision-making in uncertain times. His website, Retina Media, provides valuable resources and information on his work in content strategy and generative engine optimization. Check out both to gain a better understanding of how to navigate the challenges and opportunities presented by AI in today's business landscape. For the accessible version of the podcast, go to our Ziotag gallery.We're happy you're here! Like the pod?Support the podcast and receive discounts from our sponsors: https://yourbrandamplified.codeadx.me/Leave a rating and review on your favorite platformFollow @yourbrandamplified on the socialsTalk to my digital avatar Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss scaling Generative AI past basic prompting and achieving real business value. You will learn the strategic framework necessary to move beyond simple, one-off interactions with large language models. You will discover why focusing on your data quality, or “ingredients,” is more critical than finding the ultimate prompt formula. You will understand how connecting AI to your core business systems using agent technology will unlock massive time savings and efficiencies. You will gain insight into defining clear, measurable goals for AI projects using effective user stories and the 5P methodology. Stop treating AI like a chatbot intern and start building automated value—watch now to find out how! Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-getting-real-value-from-generative-ai.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*. Another week, another gazillion posts on LinkedIn and various social networks about the ultimate ChatGPT prompt. OpenAI, of course, published its Prompt Blocks library of hundreds of mediocre prompts that are particularly unhelpful. And what we’re seeing in the AI industry is this: A lot of people are stuck and focused on how do I prompt ChatGPT to do this, that, or the other thing, when in reality that’s not where the value is. Today, let’s talk about where the value of generative AI actually is, because a lot of people still seem very stuck on the 101 basics. And there’s nothing wrong with that—that is totally great—but what comes after it? Christopher S. Penn – 00:47 So, Katie, from your perspective as someone who is not the propeller head in this company and is very representative of the business user who wants real results from this stuff and not just shiny objects, what do you see in the Generative AI space right now? And more important, what do you see it’s missing? Katie Robbert – 01:14 I see it’s missing any kind of strategy, to be quite honest. The way that people are using generative AI—and this is a broad stroke, it’s a generalization—is still very one-off. Let me go to ChatGPT to summarize these meeting notes. Let me go to Gemini to outline a blog post. There is nothing wrong with that, but it’s not a strategy; it’s one more tool in your stack. And so the big thing that I see missing is, what are we doing with this long term? Katie Robbert – 01:53 Where does it fit into the overall workflow and how is it actually becoming part of the team? How is it becoming integrated into the organization? So, people who are saying, “Well, we’re sitting down for our 2026 planning, we need to figure out where AI fits in,” I think you’re already setting yourself up for failure because you’re leading with AI needs to fit in somewhere versus you need to lead with what do we need to do in 2026, period? Chris has brought up the 5P Framework, which is 100% where I’m going to recommend you start. Start with the purpose. So, what are your goals? What are the questions you’re trying to answer? How are you trying to grow and scale? And what are the KPIs that you want to be thinking about in 2026? Katie Robbert – 02:46 Notice I didn’t say with AI. Leave AI out of it for now. For now, we’ll get to it. So what are the things that you’re trying to do? What is the purpose of having a business in 2026? What are the things you’re trying to achieve? Then you move on to people. Well, who’s involved? It’s the team, it’s the executives, it’s the customers. Don’t forget about the customers because they’re kind of the reason you have a business in the first place. And figure out what all of those individuals bring to the table. How are they going to help you with your purpose and then the process? How are we going to do these things? So, in order to scale the business by 10x, we need to bring in 20x revenue. Katie Robbert – 03:33 In order to bring in 20x revenue, we need to bring in 30x visits to the website. And you start to go down that road. That’s sort of your process. And guess what? We haven’t even talked about AI yet, because it doesn’t matter at the moment. You need to get those pieces figured out first. If we need to bring in 30x the visits to the website that we were getting in the previous year, how do we do that? What are we doing today? What do we need to do tomorrow? Okay, we need to create content, we need to disseminate it, we need to measure it, we need to do this. Oh, maybe now we can think about platforms. That’s where you can start to figure out where in this does AI fit? Katie Robbert – 04:12 And I think that’s the piece that’s missing: people are jumping to AI first and not why the heck are we doing this. So that is my long-winded rant. Chris, I would love to hear your perspective. Christopher S. Penn – 04:23 Perspective specific to AI. Where people are getting tripped up is in a couple different areas. The biggest at the basic level is a misunderstanding of prompting. And we’re going to be talking about this. You’ll hear a lot about this fall as we are on the conference circuit. Prompting is like a recipe. So you have a recipe for baking beef Wellington, what have you. The recipe is not the most important part of the process. It’s important. Winging it, particularly for complex dishes, is not a good idea unless you’ve done it a million times before. The most important part is things like the ingredients. You can have the best recipe in the world; if you have no ingredients, you ain’t eating. That’s pretty obvious. Christopher S. Penn – 05:15 And yet so many people are so focused on, “Oh, I’ve got to have the perfect prompt”—no, you don’t. You need to have good ingredients to get value. So, let’s say you’re doing 2026 strategic planning and you go to the AI to say, “I need to work on my strategic plan for 2026.” They will understand generally what that means because most models are reasoning models now. But if you provide no data about who you are, what you do, how you’ve done it, your results before, who your competitors are, who your customers are, all the 10 things that you need to do strategic planning like your budget, who’s involved, the Five Ps—basically AI won’t be able to help you any better than you will or that your team will. It’s a waste of time. Christopher S. Penn – 06:00 For immediate value unlocks for AI, it starts with the right ingredients, with the right recipe, and your skills. So that should sound an awful lot like people, process, and platform. I call it Generative AI 102. If 101 is, “How do I prompt?” 102 is, “What ingredients need to go with my prompt to get value out of them?” But then 201 is—and this is exactly what you started off with, Katie—one-off interactions with ChatGPT don’t scale. They don’t deliver value because you, the human, are still typing away like a little monkey at the keyboard. If you want value from AI, part of its value comes from saving time, saving money, and making money. Saving time means scale—doing things at scale—which means you need to connect your AI to other systems. Christopher S. Penn – 06:59 You need to plug it into your email, into your CRM, into your DSP. Name the technology platform of your choice. If you are still just copy-pasting in and out of ChatGPT, you’re not going to get the value you want because you are the bottleneck. Katie Robbert – 07:16 I think that this extends to the conversations around agentic AI. Again, are you thinking about it as a one-off or are you thinking about it as a true integration into your workflow? Okay, so I don’t want to have to summarize meeting notes anymore. So let me spend a week building an agent that’s going to do that for me. Okay, great. So now you have an agent that summarizes your meeting notes and doesn’t do anything else. So now you have to, okay, what else do I want it to do? And you start frankensteining together all of these one-off tasks until you have 100 agents to do 100 things versus maybe one really solid workflow that could have done a lot of things and have less failure points. Katie Robbert – 08:00 That’s really what we’re talking about. When you’re short-sighted in thinking about where generative AI fits in, you introduce even more failure points in your business—your operations, your process, your marketing, whatever it is. Because you’re just saying, “Okay, I’m going to use ChatGPT for this, and I’m going to use Gemini for this, and I’m going to use Claude for this, and I’m use Google Colab for this.” Then it’s just kind of all over the place. Really, what you want to have is a more thoughtful, holistic, documented plan for where all these pieces fit in. Don’t put AI first. Think about your goals first. And if the goal is, “We want to use AI,” it’s the wrong goal. Start over. Christopher S. Penn – 08:56 Unless that’s literally your job. Katie Robbert – 09:00 But that would theoretically tie to a larger business goal. Christopher S. Penn – 09:05 It should. Katie Robbert – 09:07 So what is the larger business goal that you’ve then determined? This is where AI fits in. Then you can introduce AI. A great way to figure that out is a user story. A user story is a simple three-part sentence: As a [Persona], I want [X], so that [Y]. So, as the lead AI engineer, I want to build an AI agent. And you don’t stop there. You say, “So that we can increase our revenue by 30x,” or, “Find more efficiencies and cut down the amount of time that it takes to create content.” Too many people, when we are talking about where people are getting generative AI wrong, stop at the “want to” and they put the period there. They forget about the “so that.” Katie Robbert – 09:58 And the “so that” arguably is the most important part of the user story because it gives you a purpose, it gives you a performance metric. So the Persona is the people, the “want to” is the process and the platform. The “so that” is the purpose and the performance. Christopher S. Penn – 10:18 When you do that, when you start thinking about the purpose, it will hint at the platforms that have to be involved. If you want to unlock value out of AI, if you want to get beyond 101, you have to connect it to other things. A real simple example: Say you’re in sales. Where does all the data that you’d want AI to use live? It doesn’t live in ChatGPT; it lives in your CRM. So the first and most important thing that you would have to figure out is, “As a salesperson, I want to increase my closing rate by 10% so that I get 10% more money.” That’s a pretty solid user story. Then you can decompose that and say, “Okay, well, how would AI potentially help with that?” Well, it could identify maybe next best actions on my… Christopher S. Penn – 11:12 …on the deals that are in my pipeline. Maybe I’ve forgotten something. Maybe something fell through the cracks. How do I do that? So you would then revise the user story: “As a salesperson who wants to make more money, I want to identify the next best actions for the deals in my pipeline programmatically so that I don’t let something fall through the cracks that could make me a bunch of money.” Then you drill down further and you say, “Okay, well, how could AI help me with that?” Well, if you have your Sales Playbook, you have your CRM data, and you have a good agentic framework, you could say, “Agent, go get me one of my deals at a time from my CRM, take my Sales Playbook, interrogate it and say, ‘Hey, Sales Playbook, here’s my deal. What should my next best action be?'” Christopher S. Penn – 11:59 If you’ve done a good job with your Sales Playbook and you’ve got battle cards and all that stuff in there, the AI will pretty easily figure out, “Oh, this deal is in this state. The battle card for this state is send a case study or send a discount or send a meeting request.” Then the AI has to go back to its agent and say, “CRM, record a task for me. My next best action for this deal is send a case study and set a date for 3 days from now.” Now, you’ve taken the user story, drilled down. You found a place where AI fits in and can do that work so that you don’t have to. Because a human could do that work. And a human should know what’s in your Sales Playbook. Christopher S. Penn – 12:48 But let’s be honest, if you do a really good job with the Sales Playbook, it might be 300 pages long. But in the system now, you’re connecting AI to and from where all the knowledge lives and saying, “This is the concrete, tangible outcome I want: I want to know what the next best action is for every deal in my pipeline so that I can make more money.” Katie Robbert – 13:10 I would argue that even if your sales book is 200 pages long, you should still kind of know how you’re selling things. Christopher S. Penn – 13:19 Should. Katie Robbert – 13:21 But that’s the thing: to get more value out of generative AI, you have to know the thing first. So, yeah, generative AI can give you suggestions and help you brainstorm. But really, it comes down to what you know. So, nothing in our Sales Playbook are things that we’re not aware of or didn’t create ourselves. Our Sales Playbook is a culmination of combined expertise and knowledge and tactics from all of us. If I read through—and I have read through—but if I read through the entire Sales Playbook, nothing should jump out at me as, “Huh, that’s new.” Katie Robbert – 13:58 I wasn’t aware of that. I think the other side of the coin is, yes, we’re doing these one-off things with generative AI, but we’re also just accepting the output as is. We’re, “Okay, so that must be it.” When we’re thinking about getting more value, the value, Chris, to your point, is if you’re not giving the system all of the ingredients, you’re going to end up with a beef Wellington that’s made with chickpeas and glue and maybe a piece of cheesecloth. I’m waiting for you to try to wrap your head around that. Christopher S. Penn – 14:45 Yeah, no, that sounds horrible. Katie Robbert – 14:48 Exactly. That’s exactly the point: the value you get out of generative AI. It goes back to the data quality conversation we were having on last week’s podcast when we were talking about the LinkedIn paper. It’s not enough just to accept the output and clean it from there. If you spent the time to make a beef Wellington and the meat is overdone, or the pastry is not flaky, or the filling is too salty, and you’re trying to correct those things after the fact, you’re already too late. You can maybe kind of mask it a little bit, maybe add a couple of things to counterbalance whatever it is that went wrong. But it really starts at the beginning of what you’re putting into it. Katie Robbert – 15:39 So maybe don’t be so heavy-handed with the salt, maybe don’t overwork the dough so that it is actually more flaky and more like a pastry dough than a pizza dough. Christopher S. Penn – 15:52 I’m really hungry now. In 2026, I do think one of the things that marketers are going to get their hands around—and everybody using generative AI—is how agents play a role in what you do because they are the connectors to other systems. And if you’re not familiar with how agentic AI works, it’s going to be a handicap. In the same way that if you’re not familiar with how ChatGPT itself works, it’s going to be a handicap, and you still have to master the basics. We’ve always talked about the three levels: done by you, which is prompting; done with you, which is mini automations like Gems and GPTs; and then done for you as agents. I think people have kind of at least figured out done by you, give or take. Christopher S. Penn – 16:41 Yes, there’s still a lot of crappy prompts out there, but for the most part people don’t need to be told what a prompt is anymore. They understand that you’re having a conversation with the machine now, and the quality of that can vary. People are starting to wrap their heads around the GPT kind of thing: “Let me make a mini app for this.” And there’s a bunch of things that I see wrong there: “I’m just going to make this my primary workhorse.” No, it doesn’t have the context, doesn’t have the ingredients to do that. But getting to that level of the agent is where I think at least the forward-looking companies need to get to, to get that value sooner rather than later. Christopher S. Penn – 17:20 This past year in 2025, we have built probably two dozen agentic systems, which is nothing more than an AI wrapped around a whole bunch of code connecting to data sources. We’ve used it to build ICPs, to evaluate landing pages, to do sentiment analysis—all these different projects because some of them are really crazy. But the key for the value was connecting to those systems. Christopher S. Penn – 17:49 That’s the really difficult part because—and we have a whole thing about this if you want to chat about it—we have a data quality audit. The moment you start connecting to your systems, you now need to know that the data going in and out of those systems is good. If the ingredients are bad, to your point, it doesn’t matter how good a cook you are, it doesn’t matter what appliances you own, doesn’t matter how good the recipe is. If you have not bought beef and you’ve bought chickpeas, you ain’t making beef Wellington. Katie Robbert – 18:27 Side note: I have made a vegetarian beef Wellington with chickpeas, and it actually came out pretty good. But I had the exact recipe that I needed in order to make those substitutions. And I went into the process knowing that my output wasn’t actually going to be a beef Wellington; it was going to be a chickpea Wellington. I think that’s also part of it—the expectation setting. AI can do a lot with crappy ingredients, but not if you don’t tell it what it’s supposed to be doing. So if you say, “I’m making a beef Wellington, here’s chickpeas,” it’s going to be, “I guess I can do that.” Katie Robbert – 19:13 But if you’re saying, “I’m making a chickpea loaf covered in puff pastry and a mushroom filling,” it’s, “Oh, I can totally do that,” because there was no mention of beef, and now I don’t have the context that I’m supposed to be doing anything with beef. So it’s the ingredients, but it’s also the critical thinking of what is it that you’re trying to do in the first place. Katie Robbert – 19:34 That goes back to this is where people aren’t getting the right value out of generative AI because they’re just doing these one-off things and they’re not giving it the context that it needs to actually do something. And then it’s not integrated into the business as a whole. It’s just, Chris is over there using generative AI to make songs. But that has nothing to do with what Trust Insights does on a day-to-day basis. So that’s never going to make us any money. He’s spending the time and the resources. This is all fictional. He doesn’t actually spend company time doing this. Christopher S. Penn – 20:09 I spent a lot of time personally. Katie Robbert – 20:10 Doing this, and that’s fine. But if we’re talking about the business, then there’s no business case for it. You haven’t gone through the Five Ps. Katie Robbert – 20:20 To say this is where this particular thing fits into the business overall. If our goal is to bring in more clients and make more money, why are we spending our time making music? Christopher S. Penn – 20:32 Exactly. As we have this conversation, it occurs to me that in 2026 we are probably going to need to put together an agentic AI course because the roadmap to get there is very difficult if you don’t know what you’re doing. You will potentially do things like, oh, I don’t know, accidentally give AI access to your production database and then it deletes it because it thinks it didn’t need it. Which happened to someone on the Replit repository not too long ago. Katie Robbert – 21:04 Whoops. Christopher S. Penn – 21:08 This is why we do git commits and rollbacks and we use sandbox AI. If you are in a position where you are saying, “I’ve got the 101 down and now I’m stuck. I don’t know where to go next,” the three things that you should be looking at: Number one is the Five Ps to figure out what you should be doing, period. Number two is a data quality audit to make sure that the data you’re feeding into AI is going to be any good. Number three is taking the agentic systems that are out there to connect them to your good quality data for the right purpose, with the right performance, so that you can scale the use of AI beyond being your ChatGPT’s intern. That’s what you are. Katie Robbert – 21:58 Chris, I don’t know if you know this, but we have a course that actually walks you through a lot of those things. You can go to Trust Insights AI strategy course. To be clear, this specific course doesn’t teach you how to use AI. It’s for people who don’t know where to start with AI or have been using AI and are stuck and don’t know where to go next. So, for example, if you’re doing your 2026 planning and you’re, “I think we need to introduce agentic AI.” Christopher S. Penn – 22:33 Cool. Katie Robbert – 22:34 I would highly recommend using the tools that you learn in this course to figure out, “Do I need to do that? Where does it fit? Who needs to do it? How are we going to maintain it? What is the goal of putting agentic AI in other than just putting it on our website and saying, ‘We do it’?” That would be my recommendation: take our AI strategy course to figure out what to do next. Chris, where we started with this conversation was, how do people get more value out of AI? So, Chris, congratulations. Chris is an AI ready strategist. Katie Robbert – 23:14 We’re very proud of him. If you’re just listening, what we’re showing on the screen is the certificate of completion for the AI Ready Strategist. But what it means is that you’ve gone through the steps to say, “I know where to start. If I’m stuck, I know how to get unstuck.” Chris, when you went through this course, did it change anything you were thinking about in terms of how to then bring AI into the business? Christopher S. Penn – 23:42 Yes. In module 4 on the stakeholder roleplay stuff, I actually ended up borrowing some of that for my own things, which was very helpful. Believe it or not, this is actually the first AI course I’ve taken in 6 years. Katie Robbert – 23:58 I’m going to take that as a very high compliment. Christopher S. Penn – 24:01 Exactly. Katie Robbert – 24:04 What Chris is referring to: part of the challenge of getting the value out of AI is convincing other people that there is value in it. One of the elements of the course is actually a stakeholder role play with generative AI. Basically, you can say, “This is what I want to do.” And it will simulate talking to your stakeholder. If your stakeholder is saying, “Okay, I need to know this, this, and this.” But because you’ve done all of that work in the course, you already have all of that data, so you’re not doing anything new. You’re saying, “Oh, here’s that information. Here, let me serve it up to you.” Katie Robbert – 24:41 So it’s an easy yes. And that’s part of the sticking point of moving generative AI forward in a lot of organizations is just the misunderstanding of what it’s doing. Christopher S. Penn – 24:52 Exactly. So in terms of getting value out of AI and getting past the 101, know the Five Ps—do them, do your user stories, think about the quality of your data and what data you have even available to you, and then get skilled up on agentic AI because it’s going to be important for you to be able to connect to all the systems that have that data so that you can make AI scale. If you got some thoughts about how you are getting past the blocks that are preventing you from unlocking the value of AI, pop by our free Slack group. Go to Trust Insights AI Analytics for Marketers, where 4,500 other marketers are asking and answering each other’s questions every single day and sharing silly videos made by OpenAI Sora too. Christopher S. Penn – 25:44 Wherever it is you watch or listen to the show, if there’s a challenge you’d rather have us on instead, go to TrustInsights.ai/TIpodcast. You can find us in all the places that fine podcasts are served. Thanks for tuning in. We’ll talk to you on the next one. Speaker 3 – 26:02 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. 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 scientists 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 are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models. Yet, they excel at exploring and explaining complex concepts clearly through compelling narratives and visualizations—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.

From May 2, 2023: Generative AI products have been tearing up the headlines recently. Among the many issues these products raise is whether or not their outputs are protected by Section 230, the foundational statute that shields websites from liability for third-party content.On this episode of Arbiters of Truth, Lawfare's occasional series on the information ecosystem, Lawfare Senior Editor Quinta Jurecic and Matt Perault, Director of the Center on Technology and Policy at UNC-Chapel Hill, talked through this question with Senator Ron Wyden and Chris Cox, formerly a U.S. congressman and SEC chairman. Cox and Wyden drafted Section 230 together in 1996—and they're skeptical that its protections apply to generative AI. To receive ad-free podcasts, become a Lawfare Material Supporter at www.patreon.com/lawfare. You can also support Lawfare by making a one-time donation at https://givebutter.com/lawfare-institute.Support this show http://supporter.acast.com/lawfare. Hosted on Acast. See acast.com/privacy for more information.

On this episode of Inside the Firm does density ever create affordable housing, then some hot takes from Tyler Suomala, and finally, what is generative engine optimization and why should it be your next focus? Join us as we go back Inside the Firm!

How can marketers stay discoverable as AI reshapes the search landscape?This special Hard Corps Marketing Show takeover episode features an episode from the Connect To Market podcast, hosted by Casey Cheshire. In this conversation, Casey sits down with Al Sargent, Senior Director, Product, Solution & Partner Marketing at ZEDEDA, to explore the evolving field of Generative Engine Optimization (GEO). Al delivers a strategic and practical breakdown of how marketers can adapt to the rise of AI tools like ChatGPT, Perplexity, and Gemini- tools that are reshaping how content is discovered and consumed.He explains how GEO differs from traditional SEO, why documentation matters more than ever, and how to leverage content repetition and high-authority sites to maintain discoverability. Al also shares his personal journey in tech and marketing, emphasizing the role of empathy, mentorship, and community-building in professional growth.In this episode, we cover:How to use LLM.txt files and structured content to improve visibilityThe importance of repurposing and repeating content across platformsLeveraging high-authority sites like Wikipedia to support GEOWhy competitive comparison content is crucial in the AI search era

On today's episode of Major Choices, Brayden, Jed, and Mallory talk about something getting a lot of buzz on campus these days: GenAI-101. Plus, learn a few extra tips on how to use AI responsibly as a college student. 

Our ongoing discussion of the difficulty in integrating the journey on the way of the life of faithfulness to the evengalion of Jesus, The Christ, the Orthodox Christian way of life, into contemporary western culture continues as Jim & Fr Symeon talk about the tower of babel as the proto-story of humanity's quest for control over our own destiny & God, repeatedly, making us aware we're not, He is.In this second half of the conversation we began in S7E9, Go Ahead & Lose Control, we focus more on what is involved in breaking free from civil religion, human ideology, & the distraction of politics by pursuing the authentic spiritual life, which breeds humility, which allows us to see ourselves not as those who are capable of changing the world, but as the chief of sinners.Let us know what you think!Particularly let us know if you prefer this video format to the side by side.Reference materials for this episode: - Sherlock Holmes' “ideal reasoner” speech   - The Five Orange Pips, the “ideal reasoner” monologue   - https://www.gutenberg.org/files/1661/1661-h/1661-h.htmScripture citations for this episode:Martyrdom - 2 Maccabees 6 & 7Voluntarily constraining our freedom - Romans 14The Christian Saints Podcast is a joint production of Generative sounds & Paradosis Pavilion with oversight from Fr Symeon KeesParadosis Pavilion - https://youtube.com/@paradosispavilion9555https://www.instagram.com/christiansaintspodcasthttps://twitter.com/podcast_saintshttps://www.facebook.com/christiansaintspodcasthttps://www.threads.net/@christiansaintspodcastIconographic images used by kind permission of Nicholas Papas, who controls distribution rights of these imagesPrints of all of Nick's work can be found at Saint Demetrius Press - http://www.saintdemetriuspress.comAll music in these episodes is a production of Generative Soundshttps://generativesoundsjjm.bandcamp.comDistribution rights of this episode & all music contained in it are controlled by Generative SoundsCopyright 2021 - 2023

Two service pros, same service, same price, same city… so why does AI recommend them and not you? Here's the truth. AI doesn't guess. It chooses the clearer, safer, more repeated name. This is where answer engine optimization (AEO) meets your daily reality as a service pro. In 2025, SEO alone won't save you. Generative engine optimization, AI discovery, and digital networking are now the trails that decide who gets chosen. In this episode of the Branding Momentum podcast, you'll learn how AI makes the tie-break between you and a competitor: • How to make your niche and specialty crystal clear so both AI search and humans know exactly what you do • Why consistency across LinkedIn, your website, podcasts, and transcripts teaches AI to connect the dots• Where to show up through digital networking—guest podcasts, collaborations, newsletters, articles, and communities—so your name travels further • Why one collaboration multiplies your visibility across feeds, YouTube clips, blogs, and transcripts faster than twenty solo posts in your own bubble If you've been visible but not chosen, this is the missing piece. I'm Veronica Di Polo, a marketing strategist based in Moraira, Spain, helping service-based business owners get leads with words that sell. _______________________  

If you didn't have the chance to attend Content Marketing World 2025, give this episode a listen! I talk with Lee Chapman and Morgan Norris about their time and we unpack the event's key takeaways from topics on storytelling and AI, to the future of platforms like LinkedIn and Reddit.In this episode Wendy Covey welcomes Lee Chapman, President of TREW, and Morgan Norris, Senior Brand Strategist, to discuss their experiences at Content Marketing World 2025. Morgan Norris presented a manufacturing masterclass, focusing on executing a campaign in 30 days. This session provided attendees with actionable strategies to build brand awareness quickly, a skill increasingly necessary in today's fast-paced market. Lee Chapman participated in the mentor-mentee program, emphasizing the value of community and shared learning within the industry.The episode delves into key themes from the conference, including storytelling as a strategy, AI and search disruption, and innovative content systems. AI and search were hot topics, with discussions on generative engine optimization (GEO) and the evolving role of AI in content creation. The speakers emphasized the need for unique content to stand out in a sea of AI-generated material. The episode also explored the potential of platforms like LinkedIn and Reddit for industrial marketing, highlighting the importance of thought leadership and community engagement.TakeawaysStorytelling is crucial for aligning sales and marketing, as highlighted by Pam Didner's session.Farah Kober demonstrated the impact of storytelling on brand perception and purchase intent.Generative engine optimization (GEO) is becoming a key focus in AI and search strategies.Unique content is essential to stand out in a market saturated with AI-generated material.Interactive content like configurators and ROI generators can enhance user engagement.Creating comparative content can enhance your brand's visibility and engagement.Users on Reddit are highly intentional, often seeking specific answers or engaging in community discussions.ResourcesConnect with Lee on LinkedInConnect with Morgan on LinkedInConnect with Wendy on LinkedInRegister for the Industrial Marketing Summit

Before Siri had sass and Alexa started judging your music taste, the original virtual assistant was quietly revolutionizing the '90s—powered by many patents and a whole lot of foresight. Now, as AI goes from buzzword to boss, we ask, will it transform your job, your home… or just steal your knowledge?  This week, Dave, Esmee and Rob speak with Kevin Surace, Futurist, Inventor & "Father" of the Virtual Assistant, about exploring the evolution of AI, what the future might hold, and how disruptive innovation can shake up your organization in ways you might not expect.   TLDR: 00:40 – Introduction of Kevin Surace 05:12 – Rob gets confused by Google Maps reviews and selfies 08:15 – Deep dive into the evolution of AI with Kevin 52:00 – How intelligent agents can help manage digital noise and support mental well-being 1:07:30 – Wrapping up the book the Joy Success Cycle and heading to a concert  GuestKevin Surace: https://www.linkedin.com/in/ksurace/ HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/ ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini 

In this episode, we explore the evolving impact of generative artificial intelligence (GAI) on the workforce, with a focus on how GAI can affect Asian American professionals. Drawing from recent research, we highlight how tasks requiring human agency—such as interpersonal communication and organizing—are gaining value, while roles centered on data processing and analysis face increasing automation. Tune in for strategies on up-skilling and re-skilling, plus a few alter ego career pivots as we imagine our lives beyond AI.Link to article about GAI.

Can we have a normal conversation about AI? Brian talks with Meghan Sullivan about the effect of rapidly advancing technology on human dignity and our understanding of the imago Dei. Dr. Brian Doak is an Old Testament scholar and professor.Meghan Sullivan is a decorated scholar and teacher at the University of Notre Dame, where she is professor of philosophy.Check out the opening ND Summit Keynote on the DELTA Framework and the Institute for Ethics and the Common Good.New York Times article: Finding God in the App StoreIf you enjoy listening to the George Fox Talks podcast and would like to watch, too, check out our channel on YouTube! We also have a web page that features all of our podcasts, a sign-up for our weekly email update, and publications from the George Fox University community.

AI is reshaping industries at a rapid pace, but as its influence grows, so do the ethical concerns that come with it.   This episode examines how AI is being applied across sectors such as healthcare, finance, and retail, while also exploring the crucial issue of ensuring that these technologies align with human values.   In this conversation, Lois Houston and Nikita Abraham are joined by Hemant Gahankari, Senior Principal OCI Instructor, who emphasizes the importance of fairness, inclusivity, transparency, and accountability in AI systems.   AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   ---------------------------------------------------- Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hey everyone! In our last episode, we spoke about how Oracle integrates AI capabilities into its Fusion Applications to enhance business workflows, and we focused on Predictive, Generative, and Agentic AI. Lois: Today, we'll discuss the various applications of AI. This is the final episode in our AI series, and before we close, we'll also touch upon ethical and responsible AI.  01:01 Nikita: Taking us through all of this is Senior Principal OCI Instructor Hemant Gahankari. Hi Hemant! AI is pretty much everywhere today. So, can you explain how it is being used in industries like retail, hospitality, health care, and so on?  Hemant: AI isn't just for sci-fi movies anymore. It's helping doctors spot diseases earlier and even discover new drugs faster. Imagine an AI that can look at an X-ray and say, hey, there is something sketchy here before a human even notices. Wild, right? Banks and fintech companies are all over AI. Fraud detection. AI has got it covered. Those robo advisors managing your investments? That's AI too. Ever noticed how e-commerce companies always seem to know what you want? That's AI studying your habits and nudging you towards that next purchase or binge watch. Factories are getting smarter. AI predicts when machines will fail so they can fix them before everything grinds to a halt. Less downtime, more efficiency. Everyone wins. Farming has gone high tech. Drones and AI analyze crops, optimize water use, and even help with harvesting. Self-driving cars get all the hype, but even your everyday GPS uses AI to dodge traffic jams. And if AI can save me from sitting in bumper-to-bumper traffic, I'm all for it. 02:40 Nikita: Agreed! Thanks for that overview, but let's get into specific scenarios within each industry.  Hemant: Let us take a scenario in the retail industry-- a retail clothing line with dozens of brick-and-mortar stores. Maintaining proper inventory levels in stores and regional warehouses is critical for retailers. In this low-margin business, being out of a popular product is especially challenging during sales and promotions. Managers want to delight shoppers and increase sales but without overbuying. That's where AI steps in. The retailer has multiple information sources, ranging from point-of-sale terminals to warehouse inventory systems. This data can be used to train a forecasting model that can make predictions, such as demand increase due to a holiday or planned marketing promotion, and determine the time required to acquire and distribute the extra inventory. Most ERP-based forecasting systems can produce sophisticated reports. A generative AI report writer goes further, creating custom plain-language summaries of these reports tailored for each store, instructing managers about how to maximize sales of well-stocked items while mitigating possible shortages. 04:11 Lois: Ok. How is AI being used in the hospitality sector, Hemant? Hemant: Let us take an example of a hotel chain that depends on positive ratings on social media and review websites. One common challenge they face is keeping track of online reviews, leading to missed opportunities to engage unhappy customers complaining on social media. Hotel managers don't know what's being said fast enough to address problems in real-time. Here, AI can be used to create a large data set from the tens of thousands of previously published online reviews. A textual language AI system can perform a sentiment analysis across the data to determine a baseline that can be periodically re-evaluated to spot trends. Data scientists could also build a model that correlates these textual messages and their sentiments against specific hotel locations and other factors, such as weather. Generative AI can extract valuable suggestions and insights from both positive and negative comments. 05:27 Nikita: That's great. And what about Financial Services? I know banks use AI quite often to detect fraud. Hemant: Unfortunately, fraud can creep into any part of a bank's retail operations. Fraud can happen with online transactions, from a phone or browser, and offsite ATMs too. Without trust, banks won't have customers or shareholders. Excessive fraud and delays in detecting it can violate financial industry regulations. Fraud detection combines AI technologies, such as computer vision to interpret scanned documents, document verification to authenticate IDs like driver's licenses, and machine learning to analyze patterns. These tools work together to assess the risk of fraud in each transaction within seconds. When the system detects a high risk, it triggers automated responses, such as placing holds on withdrawals or requesting additional identification from customers, to prevent fraudulent activity and protect both the business and its client. 06:42 Nikita: Wow, interesting. And how is AI being used in the health industry, especially when it comes to improving patient care? Hemant: Medical appointments can be frustrating for everyone involved—patients, receptionists, nurses, and physicians. There are many time-consuming steps, including scheduling, checking in, interactions with the doctors, checking out, and follow-ups. AI can fix this problem through electronic health records to analyze lab results, paper forms, scans, and structured data, summarizing insights for doctors with the latest research and patient history. This helps practice reduced costs, boost earnings, and deliver faster, more personalized care. 07:32 Lois: Let's take a look at one more industry. How is manufacturing using AI? Hemant: A factory that makes metal parts and other products use both visual inspections and electronic means to monitor product quality. A part that fails to meet the requirements may be reworked or repurposed, or it may need to be scrapped. The factory seeks to maximize profits and throughput by shipping as much good material as possible, while minimizing waste by detecting and handling defects early. The way AI can help here is with the quality assurance process, which creates X-ray images. This data can be interpreted by computer vision, which can learn to identify cracks and other weak spots, after being trained on a large data set. In addition, problematic or ambiguous data can be highlighted for human inspectors. 08:36 Oracle University's Race to Certification 2025 is your ticket to free training and certification in today's hottest tech. Whether you're starting with Artificial Intelligence, Oracle Cloud Infrastructure, Multicloud, or Oracle Data Platform, this challenge covers it all! Learn more about your chance to win prizes and see your name on the Leaderboard by visiting education.oracle.com/race-to-certification-2025. That's education.oracle.com/race-to-certification-2025. 09:20 Nikita: Welcome back! AI can be used effectively to automate a variety of tasks to improve productivity, efficiency, cost savings. But I'm sure AI has its constraints too, right? Can you talk about what happens if AI isn't able to echo human ethics?  Hemant: AI can fail due to lack of ethics.  AI can spot patterns, not make moral calls. It doesn't feel guilt, understand context, or take responsibility. That is still up to us.  Decisions are only as good as the data behind them. For example, health care AI underdiagnosing women because research data was mostly male. Artificial narrow intelligence tends to automate discrimination at scale. Recruiting AI downgraded resumes just because it had a word "women's" (for example, women's chess club). Who is responsible when AI fails? For example, if a self-driving car hits someone, we cannot blame the car. Then who owns the failure? The programmer? The CEO? Can we really trust corporations or governments having programmed the use of AI not to be evil correctly? So, it's clear that AI needs oversight to function smoothly. 10:48 Lois: So, Hemant, how can we design AI in ways that respect and reflect human values? Hemant: Think of ethics like a tree. It needs all parts working together. Roots represent intent. That is our values and principles. The trunk stands for safeguards, our systems, and structures. And the branches are the outcomes we aim for. If the roots are shallow, the tree falls. If the trunk is weak, damage seeps through. The health of roots and trunk shapes the strength of our ethical outcomes. Fairness means nothing without ethical intent behind it. For example, a bank promotes its loan algorithm as fair. But it uses zip codes in decision-making, effectively penalizing people based on race. That's not fairness. That's harm disguised as data. Inclusivity depends on the intent sustainability. Inclusive design isn't just a check box. It needs a long-term commitment. For example, controllers for gamers with disabilities are only possible because of sustained R&D and intentional design choices. Without investment in inclusion, accessibility is left behind. Transparency depends on the safeguard robustness. Transparency is only useful if the system is secure and resilient. For example, a medical AI may be explainable, but if it is vulnerable to hacking, transparency won't matter. Accountability depends on the safeguard privacy and traceability. You can't hold people accountable if there is no trail to follow. For example, after a fatal self-driving car crash, deleted system logs meant no one could be held responsible. Without auditability, accountability collapses. So remember, outcomes are what we see, but they rely on intent to guide priorities and safeguards to support execution. That's why humans must have a final say. AI has no grasp of ethics, but we do. 13:16 Nikita: So, what you're saying is ethical intent and robust AI safeguards need to go hand in hand if we are to truly leverage AI we can trust. Hemant: When it comes to AI, preventing harm is a must. Take self-driving cars, for example. Keeping pedestrians safe is absolutely critical, which means the technology has to be rock solid and reliable. At the same time, fairness and inclusivity can't be overlooked. If an AI system used for hiring learns from biased past data, say, mostly male candidates being hired, it can end up repeating those biases, shutting out qualified candidates unfairly. Transparency and accountability go hand in hand. Imagine a loan rejection if the AI's decision isn't clear or explainable. It becomes impossible for someone to challenge or understand why they were turned down. And of course, robustness supports fairness too. Loan approval systems need strong security to prevent attacks that could manipulate decisions and undermine trust.  We must build AI that reflects human values and has safeguards. This makes sure that AI is fair, inclusive, transparent, and accountable.  14:44 Lois: Before we wrap, can you talk about why AI can fail? Let's continue with your analogy of the tree. Can you explain how AI failures occur and how we can address them? Hemant: Root elements like do not harm and sustainability are fundamental to ethical AI development. When these roots fail, the consequences can be serious. For example, a clear failure of do not harm is AI-powered surveillance tools misused by authoritarian regimes. This happens because there were no ethical constraints guiding how the technology was deployed. The solution is clear-- implement strong ethical use policies and conduct human rights impact assessment to prevent such misuse. On the sustainability front, training AI models can consume massive amount of energy. This failure occurs because environmental costs are not considered. To fix this, organizations are adopting carbon-aware computing practices to minimize AI's environmental footprint. By addressing these root failures, we can ensure AI is developed and used responsibly with respect for human rights and the planet. An example of a robustness failure can be a chatbot hallucinating nonexistent legal precedence used in court filings. This could be due to training on unverified internet data and no fact-checking layer. This can be fixed by grounding in authoritative databases. An example of a privacy failure can be AI facial recognition database created without user consent. The reason being no consent was taken for data collection. This can be fixed by adopting privacy-preserving techniques. An example of a fairness failure can be generated images of CEOs as white men and nurses as women, minorities. The reason being training on imbalanced internet images reflecting societal stereotypes. And the fix is to use diverse set of images. 17:18 Lois: I think this would be incomplete if we don't talk about inclusivity, transparency, and accountability failures. How can they be addressed, Hemant? Hemant: An example of an inclusivity failure can be a voice assistant not understanding accents. The reason being training data lacked diversity. And the fix is to use inclusive data. An example of a transparency and accountability failure can be teachers could not challenge AI-generated performance scores due to opaque calculations. The reason being no explainability tools are used. The fix being high-impact AI needs human review pathways and explainability built in. 18:04 Lois: Thank you, Hemant, for a fantastic conversation. We got some great insights into responsible and ethical AI. Nikita: Thank you, Hemant! If you're interested in learning more about the topics we discussed today, head over to mylearn.oracle.com and search for the AI for You course. Until next time, this is Nikita Abraham…. Lois: And Lois Houston, signing off! 18:26 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.  

Alexander Schlager, CEO of Aiceberg.ai, discusses the intersection of artificial intelligence (AI) and cybersecurity, emphasizing the importance of securing AI-powered workflows. Aiceberg employs traditional machine learning techniques to safeguard generative AI systems, providing a deterministic and explainable approach to security. This method allows organizations to understand how their AI systems operate and ensures that they can trace and audit the decisions made by these systems, which is crucial in an era where AI incidents may lead to legal challenges.The conversation highlights the need for organizations to establish robust governance frameworks as they adopt AI technologies. Schlager points out that many businesses are still grappling with basic cybersecurity measures, which complicates their ability to implement effective AI governance. He stresses that organizations must assess their existing security postures and ensure that they are prepared for the rapid deployment of agentic AI, which allows non-technical users to create and manage AI workflows independently.Schlager provides concrete examples of how Aiceberg's technology is integrated into real-world applications, such as in the banking sector, where AI workflows may involve third-party interactions. He explains that Aiceberg monitors these interactions to classify and respond to potential security threats, ensuring that organizations can demonstrate compliance and safety in the event of an incident. This proactive approach to security is essential for maintaining trust and accountability in AI systems.Finally, the discussion touches on the broader implications of AI adoption, including the potential for improved customer experiences across various industries. Schlager notes that while AI can enhance service delivery, organizations must navigate the challenges of user expectations and the maturity of their AI implementations. By focusing on customer service and experience, companies can unlock significant value from their AI investments, but they must also prioritize security and governance to mitigate risks. 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 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Summary In this episode of the AI for Sales podcast, Chad Burmeister speaks with Ali Parandeh about the evolution of AI, particularly focusing on generative AI and its transformative impact on customer experience and sales processes. They discuss the advancements in AI tools, the importance of context in AI applications, and the skills sales professionals need to thrive in an AI-driven landscape. The conversation also touches on innovative technologies that are shaping the future of AI and how businesses can leverage these tools for efficiency and personalization. Takeaways Generative AI is revolutionizing how we interact with technology. AI can create personalized customer experiences in real-time. Advanced AI applications can automate complex sales processes. AI tools are becoming essential for modern businesses. Context engineering will be crucial for effective AI deployment. Sales professionals should embrace AI tools to enhance productivity. Automation can free up time for more creative tasks. AI can assist in content creation and documentation. Understanding AI's capabilities is key for future success. Curiosity and experimentation with AI tools can lead to innovation. Chapters 00:00 Introduction to AI and Generative AI 02:30 Transforming Customer Experience with AI 04:26 Advanced AI Applications in Sales 10:21 Innovative AI Tools and Success Stories 13:11 Navigating AI's Impact on Creativity 17:54 The Future of AI Technologies 21:47 Essential Skills for Sales Professionals The AI for Sales Podcast is brought to you by BDR.ai, Nooks.ai, and ZoomInfo—the go-to-market intelligence platform that accelerates revenue growth. Skip the forms and website hunting—Chad will connect you directly with the right person at any of these companies.

Security leaders from CyberArk, Fortra, and Sysdig share actionable strategies for securely implementing generative AI and reveal real-world insights on data protection and agent management.Topics Include:Panel explores practical security approaches for GenAI from prototype to productionThree-phase framework discussed: planning, pre-production, and production security considerationsSecurity must be built-in from start - data foundation is criticalUnderstanding data location, usage, transformation, and regulatory requirements is essentialFortra's security conglomerate approach integrates with AWS native tools and partnersMachine data initially easier for compliance - no PII or HIPAA concernsIdentity paradigm shift: agents can dynamically take human and non-human roles97% of organizations using AI tools lack identity and access policiesSecurity responsibility increases as you move up the customization stackOWASP Top 10 for GenAI addresses prompt injection and data poisoningRigorous model testing including adversarial attacks before deployment is crucialSysdig spent 6-9 months stress testing their agent before production releaseTension exists between moving fast and implementing proper security controlsDifferent security approaches needed based on data sensitivity and model usageZero-standing privilege and intent-based policies critical for agent managementMulti-agent systems create "Internet of Agents" with exponentially multiplying risksDiscovery challenge: finding where GenAI is running across enterprise environmentsAPI security and gateway protection becoming critical with acceptable latencyTop customer need: translating written AI policies into actionable controlsThreat modeling should focus on impact rather than just vulnerability severityParticipants:Prashant Tyagi - Go-To-Market Identity Security Technology Strategy Lead, CyberArkMike Reed – Field CISO, Cloud Security & AI, FortraZaher Hulays – Vice President Strategic Partnerships, SysdigMatthew Girdharry - WW Leader for Observability & Security Partnerships, Amazon Web ServicesFurther Links:CyberArk: Website – LinkedIn – AWS MarketplaceFortra: Website – LinkedIn – AWS MarketplaceSysdig: Website – LinkedIn – AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this episode, host Paige West speaks with Matthias Huber, Sr. Director, Solutions Manager, IoT/Embedded & Edge Computing, Supermicro, all about accelerating Edge AI infrastructure for predictive and Generative AI.

 We're back! In this Season 5 premiere, the team reunites after their summer break to kick off an exciting new chapter. Join us as we catch up, share bold predictions for the year ahead, and explore big questions, like whether 2026 will be the year of the autonomous organization. Expect candid reflections, lively discussion, and a sneak peek at what's coming up this season.  We are very keen this season to establish a feedback loop with listeners, so will be doing shows exploring listener questions and challenges - something we are really looking forward to.  Please get in touch with us, via LinkedIn, Substack or cloudrealities@capgemini.com, if you have questions or challenges for us, we'd love to hear from you!TLDR: 00:20 – We're back! 00:35 – Catching up on what we did during the summer break 10:48 – Planning ahead until Christmas: Microsoft Ignite, AWS re:Invent, an AI mini-series and cool guests 20:27 – Tech talk: iPhone 17, deep democracy training, and the human impact of innovation 32:10 – Will autonomous organizations powered by agents emerge within 12–18 months? 40:45 – Reflections inspired by Jaws, climbing adventures, and Bruce Springsteen  HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/ ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini 

Yinon Costica is the co-founder and VP of product at Wiz, which sold to Google for $32 billion in cash. Costica joins Big Technology Podcast to discuss the extent of the cybersecurity threats that generative AI is creating, from vulnerabilities in AI software to the risks involved in “vibe coding.” Tune in to hear how attackers are using AI, why defenders face new asymmetries, and what guardrails organizations need now. We also cover Google's $32 billion acquisition of Wiz, the DeepSeek controversy, post-quantum cryptography, and the future risks of autonomous vehicles and humanoid robots. Hit play for a sharp, accessible look at the cutting edge of AI and cybersecurity.---Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice.Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016bQuestions? Feedback? Write to: bigtechnologypodcast@gmail.com 00:00 Opening and guest intro01:05 AI as a new software stack04:25 Core AI tools with RCE flaws06:18 Cloud infrastructure risks09:20 How secure is AI-written code13:54 Agents and security reviewers17:38 How attackers use AI today22:09 Asymmetry: attackers vs. defenders32:36 What Wiz actually does40:11 DeepSeek case and media spin

Get ready to discover a whole new way for people to find your business online at the forefront of the AI revolution in this insight-packed episode. Joining the conversation is Dom Wells, Founder & CEO of Onfolio Holdings (NASDAQ: ONFO), a public holding company for profitable online businesses. After acquiring an SEO agency, Dom turned it into a smart new service called Generative Engine Optimization (GEO) — helping businesses show up inside answers, tips, and conversations from tools like ChatGPT, Bing Copilot, and Claude. GEO is changing how brands get noticed in 2025 and beyond. Instead of just showing links, AI tools give people clear answers. GEO makes sure your business is part of those answers, so you’re seen where customers are already looking. In this episode, you’ll find out: How GEO is different from old-school SEO. Why AI search feels more helpful and personal than regular search engines. Simple ways to check and boost your visibility in tools like ChatGPT and Bing Copilot. Real stories of businesses getting fast results with GEO — plus how to grab free audits and tips shared during the show.

In this episode of Founded & Funded, Madrona Investor Joe Horsman sits down with Jeff Leek and Rob Bradley, co-founders of Synthesize Bio, a foundation model company for biology that's unlocking experiments researchers could never run in the lab. Jeff, chief data officer at the Fred Hutch Cancer Center, and Rob, the McIlwain Family endowed chair in data science, share: •Why a startup the right fit for generative genomics •How generative genomics could reshape research, drug trials, and more •Why RNA is the right starting point for a generative AI model in biology •What this breakthrough means for the future of drug development •Why now is biology's “ChatGPT moment” •What makes Synthesize a true foundation model for biology (not a point solution) Whether you're a founder, biotech innovator, or AI researcher, this is a must-listen conversation about the intersection of AI, biology, and the future of medicine. Transcript:https://www.madrona.com/the-future-of-biology-is-generative-inside-synthesize-bios-rna-ai-model Chapters:  (2:00) – Why a Foundation Model for Biology? (5:00) – The Case for RNA (7:00) – Biology's Large Language Model Analogy (9:00) – Solving Impossible Problems (11:00) – Validation & Testing (14:00) – Balancing Big Picture & Specific Biology (15:00) – Why a Company, Not Just a Lab (16:00) – Has Biology Had Its “ChatGPT Moment”? (19:00) – The Data Challenge (23:00) – Real-World Use Cases (26:00) – How Research Will Look in 10 Years (28:00) – Increasing the Odds of Discovery (29:00) – Clinical Trials & Precision Medicine (31:00) – Access & Next Steps

The entry-level project management job isn't what it used to be. With AI automating many of the classic coordinator tasks, the ground floor seems to have disappeared—leaving aspiring PMs wondering how to even get started. In this episode, Galen Low sits down with Benjamin Chan, Founder of CLYMB Consulting, to unpack what this shift really means for junior PMs, hiring managers, and the next generation of project leaders.Together, they explore how AI is reshaping the role of the project coordinator, what skills and traits are most valuable in today's job market, and how organizations can reimagine career paths to make sure talent isn't left behind. Whether you're breaking in, hiring, or mentoring, this conversation is full of real-world perspective and actionable ideas for navigating the new career landscape.Resources from this episode:Join DPM MembershipSubscribe to the newsletter to get our latest articles and podcastsConnect with Ben on LinkedInCheck out CLYMB Consulting

In this powerful episode, Yvette Bethel and Edwin Clamp explore one of the most urgent challenges facing organizations, institutions, and societies today: How do we shift from degenerative systems—those that deplete trust, extract value, and reinforce corruption—toward generative ecosystems that create value, restore integrity, and serve the whole? Join us as we unpack: What makes a system degenerative or corrupt (and how to recognize the signals) The hidden costs of institutional decay, distrust, and misaligned incentives The principles of generative systems — those built on trust, reciprocity, transparency, and sustainability Whether you're a leader, change agent, team member, or simply someone trying to work with integrity in a system that feels out of sync, this episode offers a clear-eyed perspective on what's possible—and where to start. Want to connect with Yvette? You can reach out to her at: LinkedIn Want to connect with Edwin? You can find him at: LinkedIn Want to go deeper? Explore related themes and leadership development tools at the IFB Academy — where future-forward leaders grow.

Aditya Vasudevan, Cohesity's cyber recovery expert, shares battle-tested insights from defending Fortune 100 companies against AI-powered cyberattacks.Topics Include:Cohesity protects 85% of Fortune 100 data with battle-tested cyber recovery experienceTop 10 cyber adversaries target organizations; Cohesity has defended against most major threatsGenAI adopted by 100 million users in two months, creating unprecedented security challengesNew AI threats include prompt injection, synthetic identities, shadow AI, and supply vulnerabilitiesAttackers now use AI for sophisticated phishing, automated malware, and accelerated attack chainsReal companies completely banned AI after code leaks, misuse incidents, and data concernsThree-pillar security approach: fight AI with AI, enhanced training, and automated workflowsSecure AI design requires private deployments, complete traceability, and role-based access controlsAmazon Bedrock offers built-in guardrails, private VPCs, and enterprise monitoring capabilitiesCohesity's Gaia demonstrates secure AI with RAG architecture and permission-aware data accessResilience strategy combines immutable backups, anomaly detection, and recovery automation for incidentsProper AI security reduces cyber insurance premiums and prevents costly downtime disastersParticipants:Aditya Vasudevan - GVP of Cyber Resiliency, Cohesity Further Links:Cohesity: Website | LinkedIn | AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Our ongoing discussion of the difficulty in integrating the journey on the way of the life of faithfulness to the evengalion of Jesus, The Christ, the Orthodox Christian way of life, into contemporary western culture continues as Jim & Fr Symeon talk about the tower of babel as the proto-story of humanity's quest for control over our own destiny & God, repeatedly, making us aware we're not, He is.Our culture is in the grip of two competing civil religions, two ideologies, which manifest themselves as politics. One is openly anti-Christian, the other uses Christian language, but is in no way advocating actual traditional Christian culture.Let us know what you think!Particularly let us know if you prefer this video format to the side by side.This is, again, part one of two. The second half of this conversation will go live in two weeks, on October 2nd.Reference materials for this episode: - Saints Who Show Sympathy to Communism     - https://mountthabor.com/blogs/the-professors-blog/question-27-orthodox-fathers-on-communism?srsltid=AfmBOopmpsDSl8enxknhEb-3mzRs589BiTPq7agS0YoTbJp13OMtRTy1Scripture citations for this episode:- Tower of Babel    - Genesis 11The Christian Saints Podcast is a joint production of Generative sounds & Paradosis Pavilion with oversight from Fr Symeon KeesParadosis Pavilion - https://youtube.com/@paradosispavilion9555https://www.instagram.com/christiansaintspodcasthttps://twitter.com/podcast_saintshttps://www.facebook.com/christiansaintspodcasthttps://www.threads.net/@christiansaintspodcastIconographic images used by kind permission of Nicholas Papas, who controls distribution rights of these imagesPrints of all of Nick's work can be found at Saint Demetrius Press - http://www.saintdemetriuspress.comAll music in these episodes is a production of Generative Soundshttps://generativesoundsjjm.bandcamp.comDistribution rights of this episode & all music contained in it are controlled by Generative SoundsCopyright 2021 - 2023

Dave, Esmee, and Rob are strapping in for another season of bold, brain-bending conversations—and they're bringing the flux capacitor with them from Back to the Future.Season 5 beams in global leaders and innovators who challenge how we think about technology, business, and humanity. From AI disruption to digital sovereignty, from leadership to culture—this season's guests are ready to shake things up.Our first full episode drops on September 25, but before we hit 88 miles per hour, here's a quick trailer to set the timeline straight, or at least bend it a little.HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/'Cloud Realities' is an original podcast from Capgemini

Ioana explores how AI is transforming the role of designers from creators to curators and editors of machine-generated outputs.This episode was recorded in partnership with ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Wix Studio.⁠In this episode: • When did you first notice AI design outputs starting to look the same?• If our role shifts to curation—similar to art curators—what qualities define a design curator?• Are we still truly creating, or have we become editors and directors of AI-generated work? Are we building solutions as before, or primarily guiding and shaping AI outputs?Check out these links:Join Anfi's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Job Search community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠The community includes 3 courses, 12 live events and workshops, and a variety of templates to support you in your job search journey.Ioana's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AI Goodies Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ioana's Domestika course ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Create a Learning Strategy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Enroll in Ioana's AI course ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠"**AI-Powered UX Design: How to Elevate Your UX Career"**⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ on Interaction Design Foundation with a 25% discount.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Into UX design⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ online course by Anfisa⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠❓Next topic ideas:Submit your questions or feedback anonymously ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow us on Instagram to stay tuned for the next episodes.

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Organizations across various industries are increasingly seeking to harness generative AI's capabilities to enhance productivity and operational efficiency. But while generative AI technologies can provide organizations with multiple opportunities, there are also risks unless integration is carried out with caution. In this episode of Risk in Context, Marsh's Gregory Eskins and Mercer's Adriana O'Kain discuss the multiple opportunities that generative AI presents, look at how the use of these technologies is evolving, and provide actions that senior leaders should consider to address technical, process, and people implications. You can access a transcript of the episode here. Read our series on debunking AI-generated myths. For more insights and insurance and risk management solutions, follow Marsh on LinkedIn and X and visit marsh.com.

Podcast: Pipeliners Podcast (LS 39 · TOP 2% what is this?)Episode: Episode 404: Combining Gamification and Generative AI to Improve Training (with Survey) with Clint BodungenPub date: 2025-09-02Get Podcast Transcript →powered by Listen411 - fast audio-to-text and summarizationIn this episode of the Pipeliners Podcast, we revisit our conversation with Clint Bodungen of ThreatGEN. The discussion focuses on the application of gamification and generative AI in professional training, specifically for enhancing cybersecurity and incident response exercises. The episode also explores a PHMSA-sponsored R&D project that is adapting these advanced technologies for the unique operational needs of the pipeline industry, highlighting the development of AI-driven, multiplayer training environments.   Visit PipelinePodcastNetwork.com for a full episode transcript, as well as detailed show notes with relevant links and insider term definitions.The podcast and artwork embedded on this page are from Russel Treat, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.

On Saturday, tens of thousands of people rallied in Auckland calling for the government to sanction Israel for their actions and violence in Gaza.  While politicians across the spectrum have responded to the protests with a mix of support and disapproval, the New Zealand government is not expected to announce their official decision on the recognition of a Palestinian state until a General Assembly in New York next week.  Following the government's announcement to get rid of NCEA in favour of a new system, Education Minister Erica Stanford has revealed numerous subjects to join the senior school curriculum, which will include the incorporation of generative AI. Finally, the New Zealand Herald published information last week pertaining to MP Carl Bates' failure to disclose 25 properties to Parliament, against what has been argued as a ‘breach of public trust'. Wire Host Sara spoke with National MP Bates about all of these topics, starting with the pro-Palestine rally.

Sunday edition   The Book of Revelation

In this episode, Pavlé Sabic, Senior Director in Generative AI Solutions and Strategy at Moody's, joins Emerj Editorial Director Matthew DeMello to discuss how agentic AI is redefining workflows in financial institutions. Pavlé explains why large enterprises are turning to AI-driven automation to overcome persistent challenges — from fragmented data and manual inefficiencies to evolving regulatory demands. He shares practical examples, including credit memo automation that reduces production time by 60%, portfolio monitoring tools that detect emerging risks earlier, and sales intelligence workflows that deliver highly targeted client insights. Pavlé also outlines why proprietary data is a strategic advantage in regulated industries and how leaders can implement agentic AI without losing human oversight. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business' podcast! This episode is sponsored by Moody's. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

The AI landscape in recruiting is evolving rapidly, with vendors racing to add AI features and many employers eager to embrace transformation. But navigating this shift successfully requires understanding what questions to ask and which foundations to build. From vendor transparency to compliance, from bias auditing to data governance, the path to effective AI implementation is not a simple one. What do TA teams need to consider to adopt a responsible approach to AI?   My guest this week is Martyn Redstone, a highly experienced advisor on AI governance for HR and Recruitment. Martyn has spent the last 9 years working with AI in recruiting and has some incredibly valuable advice to share. In the interview, we discuss: Getting the foundations right Why false AI confidence is dangerous Four key vendor evaluation areas Third-party auditing Shadow AI and data breaches Generative versus decision-based AI Global regulatory landscape challenges Why guardrails actually accelerate innovation The task-based future of work Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

In this episode of People of AI , we take you behind the scenes of "ANCESTRA," a groundbreaking film that integrates generative artificial intelligence into its core. Hear from the director Eliza McNitt and key collaborators from the Google DeepMind team about how they leveraged AI as a new creative tool, navigated its capabilities and limitations, and ultimately shaped a unique cinematic experience. Understand the future role of AI in filmmaking and its potential for developers and storytellers. Chapters: 0:00 - Introduction to Ancestra: AI in filmmaking 3:38 - The Origin Story of ANCESTRA 5:35 - Google DeepMind and Primordial Soup collaboration 11:47 - Veo and the creative process 20:21 - Behind the scenes: Making the film 28:47 - Generating videos: Gemini and Veo tools 38:11 - AI as a creative tool, not a replacement 47:41 - AI's impact and the future of the film industry 53:51 - Generative models: A new kind of camera 57:46 - Rapid fire & conclusion Resources: Ancestra → https://goo.gle/4mVScNW  Making of ANCESTRA → https://goo.gle/3JVJil1  Veo 3 → https://goo.gle/4mWn3Kz  Veo 3 Documentation → https://goo.gle/46qqFOV  Veo 3 Cookbook → https://goo.gle/3VMVFSZ  Google Flow → https://goo.gle/3VMVR4F  Watch more People of AI → https://goo.gle/PAI  Subscribe to Google for Developers → https://goo.gle/developers #PeopleofAI Speaker: Christina Warren, Ashley Oldacre,  Eliza McNitt, Ben Wiley, Corey Matthewson,  Products Mentioned: Google AI, Gemini, Veo 2, Veo 3

Episode 275 of the Hotel Marketing Podcast uncovers the secrets of Generative Engine Optimization, or GEO. Hoteliers have three primary customers online: people, search engines, and AI. Today we delve into how you can succeed in optimizing for AI engines such as ChatGPT, Gemini, Claude, CoPilot, and others. Get the full show notes at www.TravelBoomMarketing.com/podcast

Generative AI and Agentic AI are now raising the stakes on how companies deliver customer value and innovate to stay one step ahead. Accelerating with AI comes down to the long game: technology infrastructure, data, and talent. This episode will focus on practical insights into how top enterprise leaders should approach AI for long term investment, including building a modern tech stack, creating enterprise platform capabilities, proprietary data and AI solutions, and building and cultivating world-class AI talent. These best practices will be shared through the lens of Capital One's AI journey. 

Generative AI may be rewriting the rules, but Felicia Shakiba and Claurelle Rakipovic, Chief Product Officer at Pipe, break down what real product leadership looks like. From customer empathy to AI missteps, Claurelle shares sharp lessons on building products that can actually hold their ground. Chapters 00:00 Building Defensible Products in the Age of AI 01:50 Understanding Defensibility Beyond Automation 04:30 Learning from AI Missteps 09:26 Internal Testing and AI Adoption 14:39 New Competencies for Product Leaders 19:47 The Importance of Unique Data 23:49 Empathy in AI Product Development 27:39 Auditing AI for Value Delivery

AI seems to be the thing of the moment. Generative models are creating everything from pictures and movies to full songs. But is it any good? Turns out, not really. I tried my hand at making some different "AI Music" to see just how awful it is. And let me tell, it's really bad. Join me as I take a look at the future of music and why AI generated songs are total garbage. 

I'm comparing three popular generative AI tools and their ability to create unique designs based on best-selling Amazon print on demand products

SHOW SCHEDULE 8-20-25 GOOD EVENING. THE SHOW BEGINS IN ARTIFICIAL GENERATIVE INTELLIGENCE DEBATE OVER REGULATION AGI STATE BY STATE... CBS EYE ON THE WORLD WITH JOHN BATCHELOR FIRST HOUR 9:00-9:15 AI: REGULATING LLM - KEVIN FRAZIER, CIVITAS INSTITUTE 9:15-9:30 AI: REGULATING LLM - KEVIN FRAZIER, CIVITAS INSTITUTE CONTINUED 9:30-9:45 #UKRAINE: GUARANTEES AND CEASEFIRE - COLONEL JEFF MCCAUSLAND, USA (RETIRED) @MCCAUSLJ @CBSNEWS @DICKINSONCOL 9:45-10:00 #UKRAINE: TRILATERAL AND NATO - COLONEL JEFF MCCAUSLAND, USA (RETIRED) @MCCAUSLJ @CBSNEWS @DICKINSONCOL SECOND HOUR 10:00-10:15 PRC: EARTH-MOON SYSTEM LANDING 2030 - BRANDON WEICHERT, GORDON CHANG 10:15-10:30 INDIA: WANG YI IN DELHI - BLAINE HOLT, GORDON CHANG 10:30-10:45 PRC: CAPITAL FLIGHT - ANDREW COLLIER, GORDON CHANG 10:45-11:00 PRC: DRONE SUBS - RICK FISHER THIRD HOUR 11:00-11:15 INDIA: DC BREAK - SADANAND DHUME, WSJ 11:15-11:30 INDIA: CHINA ARRIVES 11:30-11:45 MAMET - EMINA MELONIC 11:45-12:00 RUSSIA: GAS TANK EMPTYING - MICHAEL BERNSTAM, HOOVER FOURTH HOUR 12:00-12:15 FRANCE: HEAT WAVE LIFTS - SIMON CONSTABLE 12:15-12:30 UK: MANSION TAX 12:30-12:45 CHICAGO: UNDERWATER - THOMAS SAVIDGE 12:45-1:00 AM CHICAGO: UNDERWATER - THOMAS SAVIDGE CONTINUED