Podcasts about genai

Might internal memos be a thing of the past?When you can just build something as fast as writing a memo about it, why wouldn't you just build the demo? In this episode of Everyday AI, we sit down with Google Cloud's Richard Seroter to break down five simple ways to use AI with Google. No technical background needed.We talk faster research, better learning, building ideas without overthinking, and why “demos over memos” might change how teams work.If you want practical, no-BS ways to actually use AI in your day‑to‑day, this one's worth a listen.5 Practical AI Workflows That Actually Matter -- An Everyday AI Chat with Jordan Wilson and Google's Richard Seroter (Replay)Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Five Practical AI Workflows with GoogleGemini Deep Research for Rapid AnalysisNotebookLM AI-Powered Knowledge ExplorationGemini CLI and Code Assist for DevelopersGoogle Jewels Autonomous Coding AgentsAI Change Management and Workflow AutomationGemini's Contextual Integration with Email and CalendarGemini and Agentic AI Across Google ProductsTimestamps:00:00 "Simple AI Strategies for Workflows"06:14 "Embracing AI-First Thinking"08:49 "Effective Strategies for Deep Research"11:24 "Context Engineering with LLMs"15:32 "Unlocking AI's Business Potential"17:33 Simplifying Complexity with AI21:21 "Everyone's a Builder Now"24:54 "Building AI Tools for Everyone"28:06 "Communicating Intent to AI Agents"30:16 "AI: The Smarter Interface"33:30 "Everyday AI: Wrap-Up & Subscribe"Keywords:Gemini Deep Research, Google AI, generative AI, AI workflows, Google Cloud, NotebookLM, AI strategies, AI transformation, change management, contextualized AI, agentic work, AI-powered research, personalized AI, deep research tools, collaborative AI agents, AI in business, AI for analysis, large language models, AI for everyday business leaders, Gemini CLI, code assist, AI coding agent, Google Jewels, autonomous AI, background AI teammate, context engineering, integrating AI in workflows, AI for HR, marketing AI, AI-powered knowledge management, learning with AI, AI onboarding, student AI tools, spec driven development, Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

Most people are still "chatting" with AI. They put in a prompt, they get an answer, and they move on. But while the rest of the world is dabbling, the top 1% of marketers are building Agentic Workflows. They aren't just using AI to write; they are using it to act.Today, I'm joined by Matt Collette, founder of Sequencr.ai. Matt has a background at Ogilvy and Edelman, and he's here to show us how to move from being an AI novice to an AI architect. We're talking about the "Micro-Agency of One"—a way to use autonomous agents to scale your output and strategy without ever hiring a team.Tune in to discover:The Expert Gap: Why 80% of marketers are "dabblers" and how to join the expert tier.Instruction Layering: The secret to using separate files to hardcode logic into your AI agents.Autonomous Research: Why tools like Manus.im are the new gold standard for deep business analysis.The Synthetic Audience Hack: How to use the Code Interpreter to "game out" your marketing strategy across dozens of segments in seconds.Key Highlights:[08:15] Why most users are severely under-utilizing Gen AI.[16:40] Chat Hygiene: How to prevent your AI from getting "confused" over time.[22:10] Creating "If-Then" logic for reliable marketing execution.[36:20] Using Code Interpreter to scale your message testing 50x.[42:15] The 2026 Edge: How to maintain strategic differentiation in an AI world.Guest Links:Sequencr.aiConnect with Matt on LinkedInLearn More: Buy Digital Threads: https://nealschaffer.com/digitalthreadsamazon Buy Maximizing LinkedIn for Business Growth: https://nealschaffer.com/maximizinglinkedinamazon Join My Digital First Mastermind: https://nealschaffer.com/membership/ Learn about My Fractional CMO Consulting Services: https://nealschaffer.com/cmo Download My Free Ebooks Here: https://nealschaffer.com/books/ Subscribe to my YouTube Channel: https://youtube.com/nealschaffer All My Podcast Show Notes: https://podcast.nealschaffer.com

The following article of the Tech industry is: “Can It Write a Symphony? Pros and Cons of GenAI in Music Creation” by Alexis Langagne, Advisory Board Member, Softtek.

Bet you didn't know you could do THAT in Google Sheets.

**NotebookLM HAS TAKEN OVER THE TRENDING COMMUNICATOR. AGAIN.** Generative AI is shaking up the world of communications—and the debate is on. In this special takeover episode of The Trending Communicator, Abel and Iris weigh the promise and pitfalls of AI adoption for comms professionals. Is AI truly a strategic superpower, or does it risk eroding hard-won wisdom and trust? Our hosts tackle big questions about originality, efficiency, brand voice, and the critical role of human judgment. From allegations of “AI slop” to the growing expectation that professionals must adapt or become obsolete, Iris and Abel challenge each other—and the industry—to find balance between bold innovation and ethical responsibility. Whether you're in the excitement camp or a skeptic, this episode delivers sharp insights, real-world examples, and a call to lead with empathy and rigor as AI rewrites the rules of communication. Listen in and hear about: How generative AI is transforming communication strategy and the debate over its real value Why AI-created content risks diluting professional wisdom and brand trust Ways communicators are leveraging legacy content to maintain originality with AI Ongoing concerns about AI amplifying existing flaws and spreading "AI slop" The evolving role of communicators as quality filters in an AI-driven workflow Challenges organizations face with AI adoption, from poor change management to role uncertainty Leadership's new responsibility to use AI as a strategic partner while preserving empathy and judgment Timestamps 0:00:00 Podcast Takeover & Introduction0:00:26 GenAI and the Big Debate in Comms0:00:38 Does Generative AI Add or Destroy Value?0:01:06 Risks, Disruption & Trust in AI Adoption0:01:25 Augmentation vs. Automation—Strategic Value0:02:13 AI Hype & Human Element Concerns0:02:39 AI Slop, Trust Issues, and Expertise Erosion0:03:24 Strategic Upside: AI as Enabler0:04:05 Human Judgment as the Quality Filter0:04:40 Speed vs. Quality & Distinctive Human Insight0:05:03 Changing Roles: Prompting, Critiquing, Synthesizing0:05:31 Institutional Readiness, Ethics, Trust & Systemic Risks0:06:43 Empathy & Perspective: Irreplaceable Human Advantages0:07:06 AI for Reputation Management, Context, & Scale0:07:32 Ethics vs. Efficiency: Risks in Sensitive Fields0:08:04 Senior Communicators, AI as Validation & Infrastructure0:08:41 Broadening Strategic Functions; AI as Audience0:09:14 Organizational Readiness & Leadership Challenges0:10:01 Leadership Opportunity: AI as Strategic Sparring Partner0:10:52 Human Wisdom & Navigating Disruption0:11:36 Closing Remarks & Podcast Outro Audio generated by NotebookLM, based on the transcripts from all episodes of The Trending Communicator in 2025. Notes and timestamps generated by Castmagic. Intro and outro music generated by Suno. Outro voice generated with Elevenlabs. Graphic depiction of Abel and Iris generated with Gemini (Nanobanana); any similarity to any individual, living or dead, is unintentional. Learn more about your ad choices. Visit megaphone.fm/adchoices

One of the scariest parts of AI?

SentinelOne announced a series of new innovative designations and integrations with Amazon Web Services (AWS), designed to bring the full benefits of AI security to AWS customers today. From securing GenAI usage in the workplace, to protecting AI infrastructure to leveraging agentic AI and automation to speed investigations and incident response, SentinelOne is empowering organizations to confidently build, operate, and secure the future of AI on AWS. SentinelOne shares its vision for the future of AI-driven cybersecurity, defining two interlinked domains: Security for AI—protecting models, agents, and data pipelines—and AI for Security—using intelligent automation to strengthen enterprise defense. With its Human + AI approach, SentinelOne integrates generative and agentic AI into every layer of its platform. The team also unveils the next evolution of Purple AI, an agentic analyst delivering auto-investigations, hyperautomation, and instant rule creation—advancing toward truly autonomous security. Visit https://www.securityweekly.com/swn for all the latest episodes! Show Notes: https://securityweekly.com/swn-542

SentinelOne announced a series of new innovative designations and integrations with Amazon Web Services (AWS), designed to bring the full benefits of AI security to AWS customers today. From securing GenAI usage in the workplace, to protecting AI infrastructure to leveraging agentic AI and automation to speed investigations and incident response, SentinelOne is empowering organizations to confidently build, operate, and secure the future of AI on AWS. SentinelOne shares its vision for the future of AI-driven cybersecurity, defining two interlinked domains: Security for AI—protecting models, agents, and data pipelines—and AI for Security—using intelligent automation to strengthen enterprise defense. With its Human + AI approach, SentinelOne integrates generative and agentic AI into every layer of its platform. The team also unveils the next evolution of Purple AI, an agentic analyst delivering auto-investigations, hyperautomation, and instant rule creation—advancing toward truly autonomous security. Show Notes: https://securityweekly.com/swn-542

בפרק חדש ווירטואלי, יוני אירח את יונתן גור זאב, Co-Founder & CPO @ Weavy (Figma Weave) לשיחה פרקטית על הדרך לבניית מוצר מ-0 ל-1 בעולם שבו הטכנולוגיה משתנה בקצב מהיר מאוד והציפיות רק עולות כל הזמן. ---------- דיברנו על: - איך ניגשים לתכנן את הגרסה הראשונה במוצרי AI? - איך אוספים פידבק ממשתמשים פוטנציאליים כבר בשלבים מוקדמים? - מהן ההשפעות של מגבלות המודלים והטכנולוגיה על המוצר שיצרו? - ומה הדרך האפקטיבית לייצר אסטרטגיית Go-To-Market לקהל מקצועי ולא מתפשר?

SentinelOne announced a series of new innovative designations and integrations with Amazon Web Services (AWS), designed to bring the full benefits of AI security to AWS customers today. From securing GenAI usage in the workplace, to protecting AI infrastructure to leveraging agentic AI and automation to speed investigations and incident response, SentinelOne is empowering organizations to confidently build, operate, and secure the future of AI on AWS. SentinelOne shares its vision for the future of AI-driven cybersecurity, defining two interlinked domains: Security for AI—protecting models, agents, and data pipelines—and AI for Security—using intelligent automation to strengthen enterprise defense. With its Human + AI approach, SentinelOne integrates generative and agentic AI into every layer of its platform. The team also unveils the next evolution of Purple AI, an agentic analyst delivering auto-investigations, hyperautomation, and instant rule creation—advancing toward truly autonomous security. Visit https://www.securityweekly.com/swn for all the latest episodes! Show Notes: https://securityweekly.com/swn-542

SentinelOne announced a series of new innovative designations and integrations with Amazon Web Services (AWS), designed to bring the full benefits of AI security to AWS customers today. From securing GenAI usage in the workplace, to protecting AI infrastructure to leveraging agentic AI and automation to speed investigations and incident response, SentinelOne is empowering organizations to confidently build, operate, and secure the future of AI on AWS. SentinelOne shares its vision for the future of AI-driven cybersecurity, defining two interlinked domains: Security for AI—protecting models, agents, and data pipelines—and AI for Security—using intelligent automation to strengthen enterprise defense. With its Human + AI approach, SentinelOne integrates generative and agentic AI into every layer of its platform. The team also unveils the next evolution of Purple AI, an agentic analyst delivering auto-investigations, hyperautomation, and instant rule creation—advancing toward truly autonomous security. Show Notes: https://securityweekly.com/swn-542

Welcome to AI Unraveled (December 30th, 2025): Your strategic briefing on the business, technology, and policy reshaping artificial intelligence.Hardware & Industry ConsolidationNvidia's $20B Dominance Play: In a massive move to secure its inference future, Nvidia has agreed to acquire key assets and employees from AI chip startup Groq for $20 billion. The deal is structured as an asset purchase and non-exclusive licensing agreement—likely to navigate antitrust scrutiny—allowing Nvidia to integrate Groq's ultra-fast LPU (Language Processing Unit) technology into its "AI Factory" roadmap.Cursor Acquires Graphite:Model Breakthroughs & BenchmarksChina's Z.ai Takes the Crown: Z.ai's new GLM-4.7 model has topped open-source benchmarks, reportedly outperforming GPT-5.1 High in coding tasks and introducing "Preserved Thinking" to prevent context decay in long agentic workflows.Claude Opus 4.5's Stamina: A new analysis by evaluation firm METR reveals that Anthropic's Claude Opus 4.5 can successfully execute tasks that require nearly 5 hours of human work,Poetiq Crushes Reasoning Benchmarks:Policy, Risk & GeopoliticsChina's "Ideological Test": New regulations in China require AI chatbots to pass a rigorous 2,000-question ideological exam,Pentagon Partners with xAI: The Department of Defense will embed Grok-based AI systems directly into its GenAI.mil platform by early 2026,Italy vs. Meta:Society & The WorkforceThe "Slop" Epidemic: A new study finds that over 20% of videos recommended to new YouTube users are now "AI slop"—low-quality, generative content designed solely to farm views.OpenAI's "Head of Preparedness": Sam Altman is hiring a lead to secure "systems that can self-improve,"Sal Khan's 1% Solution: Khan Academy founder Sal Khan is proposing that companies donate 1% of profits to retrain workers displaced by the looming AI job apocalypse.Keywords: Nvidia, Groq, GLM-4.7, Z.ai, Claude Opus 4.5, AI Slop, GenAI.mil, Pentagon, xAI, Grok, ARC-AGI-2, Graphite, Sal Khan, AI Regulation, Antitrust.Host Connection & Engagement:Etienne on Linkedin: https://www.linkedin.com/in/enoumen

Samya est Generative AI Research Lead chez Pigment, la nouvelle licorne française qui a levé +230 millions de dollars.On aborde :

A year ago, AI was still moving faster than everyone else, outpacing companies, governments, and just about anyone trying to keep up. By the end of 2025, that finally started to change. In this episode, our host Leslie D'Monte and Shouvik Das recap 2025 - the year AI stopped being just a breakthrough story and became a governance story. As generative models gave way to agentic systems, and as frameworks like India's DPDP Act came into sharper focus, AI entered a new phase, one where rules, guardrails, and accountability mattered as much as capability. The conversation looks at how 2025 forced a reset. Enterprises rushed to deploy GenAI and agents, only to encounter hallucinations, broken integrations, and the limitations of legacy systems. At the same time, the question shifted from what AI can do to where it should actually be used. A big part of the episode zooms out to India's approach. Instead of heavy regulation, the focus has been on setting boundaries about content labeling, competition oversight, and applying existing laws while still pushing investments in GPUs, data centres, and Indic language models. The goal isn't dominance; it's relevance. And then there's the bigger test: can AI work outside the bubble? In a country where most people don't live in metros or use cutting-edge devices, success looks less like chatbots and more like IVRs, public services, healthcare tools, and systems that disappear into daily life. By the end, the takeaway is simple: 2025 wasn't about AI replacing humans or reaching artificial general intelligence. It was about learning where AI fits, where it fails, and how human judgment, guardrails, and local context still matter more than raw capability. Learn more about your ad choices. Visit megaphone.fm/adchoices

Original Release Date: November 13, 2025Live from Morgan Stanley's European Tech, Media and Telecom Conference in Barcelona, our roundtable of analysts discusses tech disruptions and datacenter growth, and how Europe factors in.Read more insights from Morgan Stanley.----- Transcript -----Paul Walsh: Welcome to Thoughts on the Market. I'm Paul Walsh, Morgan Stanley's European Head of Research Product. Today we return to my conversation with Adam Wood. Head of European Technology and Payments, Emmet Kelly, Head of European Telco and Data Centers, and Lee Simpson, Head of European Technology. We were live on stage at Morgan Stanley's 25th TMT Europe conference. We had so much to discuss around the themes of AI enablers, semiconductors, and telcos. So, we are back with a concluding episode on tech disruption and data center investments. It's Thursday the 13th of November at 8am in Barcelona. After speaking with the panel about the U.S. being overweight AI enablers, and the pockets of opportunity in Europe, I wanted to ask them about AI disruption, which has been a key theme here in Europe. I started by asking Adam how he was thinking about this theme. Adam Wood: It's fascinating to see this year how we've gone in most of those sectors to how positive can GenAI be for these companies? How well are they going to monetize the opportunities? How much are they going to take advantage internally to take their own margins up? To flipping in the second half of the year, mainly to, how disruptive are they going to be? And how on earth are they going to fend off these challenges? Paul Walsh: And I think that speaks to the extent to which, as a theme, this has really, you know, built momentum. Adam Wood: Absolutely. And I mean, look, I think the first point, you know, that you made is absolutely correct – that it's very difficult to disprove this. It's going to take time for that to happen. It's impossible to do in the short term. I think the other issue is that what we've seen is – if we look at the revenues of some of the companies, you know, and huge investments going in there. And investors can clearly see the benefit of GenAI. And so investors are right to ask the question, well, where's the revenue for these businesses? You know, where are we seeing it in info services or in IT services, or in enterprise software. And the reality is today, you know, we're not seeing it. And it's hard for analysts to point to evidence that – well, no, here's the revenue base, here's the benefit that's coming through. And so, investors naturally flip to, well, if there's no benefit, then surely, we should focus on the risk. So, I think we totally understand, you know, why people are focused on the negative side of things today. I think there are differences between the sub-sectors. I mean, I think if we look, you know, at IT services, first of all, from an investor point of view, I think that's been pretty well placed in the losers' buckets and people are most concerned about that sub-sector… Paul Walsh: Something you and the global team have written a lot about. Adam Wood: Yeah, we've written about, you know, the risk of disruption in that space, the need for those companies to invest, and then the challenges they face. But I mean, if we just keep it very, very simplistic. If Gen AI is a technology that, you know, displaces labor to any extent – companies that have played labor arbitrage and provide labor for the last 20 - 25 years, you know, they're going to have to make changes to their business model. So, I think that's understandable. And they're going to have to demonstrate how they can change and invest and produce a business model that addresses those concerns. I'd probably put info services in the middle. But the challenge in that space is you have real identifiable companies that have emerged, that have a revenue base and that are challenging a subset of the products of those businesses. So again, it's perfectly understandable that investors would worry. In that context, it's not a potential threat on the horizon. It's a real threat that exists today against certainly their businesses. I think software is probably the most interesting. I'd put it in the kind of final bucket where I actually believe… Well, I think first of all, we certainly wouldn't take the view that there's no risk of disruption and things aren't going to change. Clearly that is going to be the case. I think what we'd want to do though is we'd want to continue to use frameworks that we've used historically to think about how software companies differentiate themselves, what the barriers to entry are. We don't think we need to throw all of those things away just because we have GenAI, this new set of capabilities. And I think investors will come back most easily to that space. Paul Walsh: Emmet, you talked a little bit there before about the fact that you haven't seen a huge amount of progress or additional insight from the telco space around AI; how AI is diffusing across the space. Do you get any discussions around disruption as it relates to telco space? Emmet Kelly: Very, very little. I think the biggest threat that telcos do see is – it is from the hyperscalers. So, if I look at and separate the B2C market out from the B2B, the telcos are still extremely dominant in the B2C space, clearly. But on the B2B space, the hyperscalers have come in on the cloud side, and if you look at their market share, they're very, very dominant in cloud – certainly from a wholesale perspective. So, if you look at the cloud market shares of the big three hyperscalers in Europe, this number is courtesy of my colleague George Webb. He said it's roughly 85 percent; that's how much they have of the cloud space today. The telcos, what they're doing is they're actually reselling the hyperscale service under the telco brand name. But we don't see much really in terms of the pure kind of AI disruption, but there are concerns definitely within the telco space that the hyperscalers might try and move from the B2B space into the B2C space at some stage. And whether it's through virtual networks, cloudified networks, to try and get into the B2C space that way. Paul Walsh: Understood. And Lee maybe less about disruption, but certainly adoption, some insights from your side around adoption across the tech hardware space? Lee Simpson: Sure. I think, you know, it's always seen that are enabling the AI move, but, but there is adoption inside semis companies as well, and I think I'd point to design flow. So, if you look at the design guys, they're embracing the agentic system thing really quickly and they're putting forward this capability of an agent engineer, so like a digital engineer. And it – I guess we've got to get this right. It is going to enable a faster time to market for the design flow on a chip. So, if you have that design flow time, that time to market. So, you're creating double the value there for the client. Do you share that 50-50 with them? So, the challenge is going to be exactly as Adam was saying, how do you monetize this stuff? So, this is kind of the struggle that we're seeing in adoption. Paul Walsh: And Emmet, let's move to you on data centers. I mean, there are just some incredible numbers that we've seen emerging, as it relates to the hyperscaler investment that we're seeing in building out the infrastructure. I know data centers is something that you have focused tremendously on in your research, bringing our global perspectives together. Obviously, Europe sits within that. And there is a market here in Europe that might be more challenged. But I'm interested to understand how you're thinking about framing the whole data center story? Implications for Europe. Do European companies feed off some of that U.S. hyperscaler CapEx? How should we be thinking about that through the European lens? Emmet Kelly: Yeah, absolutely. So, big question, Paul. What… Paul Walsh: We've got a few minutes! Emmet Kelly: We've got a few minutes. What I would say is there was a great paper that came out from Harvard just two weeks ago, and they were looking at the scale of data center investments in the United States. And clearly the U.S. economy is ticking along very, very nicely at the moment. But this Harvard paper concluded that if you take out data center investments, U.S. economic growth today is actually zero. Paul Walsh: Wow. Emmet Kelly: That is how big the data center investments are. And what we've said in our research very clearly is if you want to build a megawatt of data center capacity that's going to cost you roughly $35 million today. Let's put that number out there. 35 million. Roughly, I'd say 25… Well, 20 to 25 million of that goes into the chips. But what's really interesting is the other remaining $10 million per megawatt, and I like to call that the picks and shovels of data centers; and I'm very convinced there is no bubble in that area whatsoever.So, what's in that area? Firstly, the first building block of a data center is finding a powered land bank. And this is a big thing that private equity is doing at the moment. So, find some real estate that's close to a mass population that's got a good fiber connection. Probably needs a little bit of water, but most importantly needs some power. And the demand for that is still infinite at the moment. Then beyond that, you've got the construction angle and there's a very big shortage of labor today to build the shells of these data centers. Then the third layer is the likes of capital goods, and there are serious supply bottlenecks there as well.And I could go on and on, but roughly that first $10 million, there's no bubble there. I'm very, very sure of that. Paul Walsh: And we conducted some extensive survey work recently as part of your analysis into the global data center market. You've sort of touched on a few of the gating factors that the industry has to contend with. That survey work was done on the operators and the supply chain, as it relates to data center build out. What were the key conclusions from that? Emmet Kelly: Well, the key conclusion was there is a shortage of power for these data centers, and… Paul Walsh: Which I think… Which is a sort of known-known, to some extent. Emmet Kelly: it is a known-known, but it's not just about the availability of power, it's the availability of green power. And it's also the price of power is a very big factor as well because energy is roughly 40 to 45 percent of the operating cost of running a data center. So, it's very, very important. And of course, that's another area where Europe doesn't screen very well.I was looking at statistics just last week on the countries that have got the highest power prices in the world. And unsurprisingly, it came out as UK, Ireland, Germany, and that's three of our big five data center markets. But when I looked at our data center stats at the beginning of the year, to put a bit of context into where we are…Paul Walsh: In Europe… Emmet Kelly: In Europe versus the rest. So, at the end of [20]24, the U.S. data center market had 35 gigawatts of data center capacity. But that grew last year at a clip of 30 percent. China had a data center bank of roughly 22 gigawatts, but that had grown at a rate of just 10 percent. And that was because of the chip issue. And then Europe has capacity, or had capacity at the end of last year, roughly 7 to 8 gigawatts, and that had grown at a rate of 10 percent. Now, the reason for that is because the three big data center markets in Europe are called FLAP-D. So, it's Frankfurt, London, Amsterdam, Paris, and Dublin. We had to put an acronym on it. So, Flap-D. Good news. I'm sitting with the tech guys. They've got even more acronyms than I do, in their sector, so well done them. Lee Simpson: Nothing beats FLAP-D. Paul Walsh: Yes. Emmet Kelly: It's quite an achievement. But what is interesting is three of the big five markets in Europe are constrained. So, Frankfurt, post the Ukraine conflict. Ireland, because in Ireland, an incredible statistic is data centers are using 25 percent of the Irish power grid. Compared to a global average of 3 percent.Now I'm from Dublin, and data centers are running into conflict with industry, with housing estates. Data centers are using 45 percent of the Dublin grid, 45. So, there's a moratorium in building data centers there. And then Amsterdam has the classic semi moratorium space because it's a small country with a very high population. So, three of our five markets are constrained in Europe. What is interesting is it started with the former Prime Minister Rishi Sunak. The UK has made great strides at attracting data center money and AI capital into the UK and the current Prime Minister continues to do that. So, the UK has definitely gone; moved from the middle lane into the fast lane. And then Macron in France. He hosted an AI summit back in February and he attracted over a 100 billion euros of AI and data center commitments. Paul Walsh: And I think if we added up, as per the research that we published a few months ago, Europe's announced over 350 billion euros, in proposed investments around AI. Emmet Kelly: Yeah, absolutely. It's a good stat. Now where people can get a little bit cynical is they can say a couple of things. Firstly, it's now over a year since the Mario Draghi report came out. And what's changed since? Absolutely nothing, unfortunately. And secondly, when I look at powering AI, I like to compare Europe to what's happening in the United States. I mean, the U.S. is giving access to nuclear power to AI. It started with the three Mile Island… Paul Walsh: Yeah. The nuclear renaissance is… Emmet Kelly: Nuclear Renaissance is absolutely huge. Now, what's underappreciated is actually Europe has got a massive nuclear power bank. It's right up there. But unfortunately, we're decommissioning some of our nuclear power around Europe, so we're going the wrong way from that perspective. Whereas President Trump is opening up the nuclear power to AI tech companies and data centers. Then over in the States we also have gas and turbines. That's a very, very big growth area and we're not quite on top of that here in Europe. So, looking at this year, I have a feeling that the Americans will probably increase their data center capacity somewhere between – it's incredible – somewhere between 35 and 50 percent. And I think in Europe we're probably looking at something like 10 percent again. Paul Walsh: Okay. Understood. Emmet Kelly: So, we're growing in Europe, but we're way, way behind as a starting point. And it feels like the others are pulling away. The other big change I'd highlight is the Chinese are really going to accelerate their data center growth this year as well. They've got their act together and you'll see them heading probably towards 30 gigs of capacity by the end of next year. Paul Walsh: Alright, we're out of time. The TMT Edge is alive and kicking in Europe. I want to thank Emmett, Lee and Adam for their time and I just want to wish everybody a great day today. Thank you.(Applause) That was my conversation with Adam, Emmett and Lee. Many thanks again to them. Many thanks again to them for telling us about the latest in their areas of research and to the live audience for hearing us out. And a thanks to you as well for listening. Let us know what you think about this and other episodes by living us a review wherever you get your podcasts. And if you enjoy listening to Thoughts on the Market, please tell a friend or colleague about the podcast today.

A $20 billion AI deal while you were away?

In this meta installment of Adventures in Advising, Matt and Ryan toss two wildly different previous podcast episodes into the digital cauldron of Google NotebookLM to see what kind of AI-brewed concoction bubbles up. Unpack the AI-generated “deep dive,” marvel at its narrative gymnastics, side-eye its dramatic metaphors, and wrestle with questions that higher ed is still learning to ask. Can advising frameworks tame the chaos of GenAI? Can trust survive the algorithmic whirlwinds? And should we be concerned when robots create podcasts about podcasts?Follow the podcast on your favorite podcast platform!The Instagram, and Facebook handle for the podcast is @AdvisingPodcastAlso, subscribe to our Adventures in Advising YouTube Channel!Connect with Matt and Ryan on LinkedIn.

The startup game has completely changed. If you are still building with the 2018-2022 B2B SaaS playbook, you are already behind. In this episode, we break down exactly how the GenAI shift has altered value creation, competition, and business models forever. This isn't just about adding AI to your product—it's about rethinking your entire reason to exist. If you want to know where the massive, uncrowded opportunities are right now (and why Service-as-Software is the next gold rush), this is your blueprint.Why You Should ListenWhy "incremental value" startups are no longer fundable.The 3 new threats killing your "time-to-market" moat.Why the B2B SaaS playbook is dead and what's replacing it.The massive "Service-as-Software" opportunity most founders are missing.Moving beyond "per seat" pricing: The new revenue models winning today.Keywordsstartup podcast, startup podcast for founders, GenAI startups, product market fit, service as software, B2B SaaS, AI business models, startup competition, seed stage, founder advice00:00:00 Intro 00:01:57 Pre-Gen AI vs Post-Gen AI Eras 00:03:23 The Trap of Incremental Value Props 00:06:58 Gen AI Unlocks Undeniable Value 00:08:50 The New Triple Threat Competition 00:11:50 Why Time in Market Is Dead 00:13:14 Cycle Speed Is the Only Moat Left00:15:00 Rethinking B2B SaaS Business Models 00:16:45 The Service as Software OpportunitySend me a message to let me know what you think!

Rakesh Doddamane is a seasoned technology leader with over 25 years of experience specializing in Generative AI, UX Design, and Digital Transformation. Currently serving as Leader of Gen AI & UX at Philips, he has established the Generative AI Centre of Excellence and spearheaded AI governance frameworks across global organizations. On The Menu: Value-driven approach to scaling generative AI solutionsStrategic AI investments across Philips' business functionsCloud infrastructure governance and cost optimization frameworksGen AI Ninja Certification: three-tier upskilling programCustomer insights leveraging AI for product innovationFuture of autonomous agents and orchestration governanceNavigating EU AI Act compliance in regulated industries

In this episode, we talk about Resident Evil 4, Stranger Things 5, Fallout Season 2, our Top 10 Games of 2025, and more.~Welcome to the Travis & Damian Podcast! Just another 2 dudes on the internet talking about video games. Your co-hosts, Travis & Damian, share a love for video games and they use this podcast as a chance to talk about events within the industry. From PlayStation to Nintendo, anything related to video games will be discussed on this podcast. They'll also talk about other pop culture topics like superheroes movies & anime but the main focus of this podcast is video games. New episode out every other week.~Graphics by @tevinvuong (https://tevinvuong.com/)~Important Timestamps~04:03 Travis played Resident Evil 4 Original & Damian played Resident Evil 4 Remake, 13:19 Fallout Season Episode 1 & 2 Spoiler Discussion, 24:48 Stranger Things 5 Vol. 2 Review (Ep. 5, 6, & 7 Spoilers), 01:08:42 Larian Studios on using genAI & Expedition 33 lose Indie Game Awards Game of the Year after AI usage surfaces, 01:20:22 Our Top Games Games of 2025 (Expedition 33, Donkey Kong Bananza, Dispatch, Split Fiction, & more)

A lot changed in the world of Cloud and AI this year. And then it changed some more, and some more, and so more. The only constant was change. SHOW: 988SHOW TRANSCRIPT: The Cloudcast #988 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW NOTESIT WAS AN INTERESTING YEAR IN CLOUD AND AI TECHNOLOGYAI has become a mainstream technology, political and social talking pointAI went through 7yrs of news cycles in 1 yrDeepSeek - Maybe NVIDIA chips aren't needed?NVIDIA acquihired Grok and their technologyMaybe AWS' lead in the cloud is now in questionGoogle got their act together with GenAI, after inventing the technology in 2017Microsoft and OpenAI sort of broke up, or at least they are seeing other peopleOpenAI forecasts 100x their current revenue in future computing needsThe US Gov't either bailed out, or socialized IntelBitcoin - 94k, up to 125k, down to 84kFEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

Et si on arrêtait de faire porter la responsabilité du numérique aux seuls parents ?Dans ce débrief de l'épisode, Mick Lévy et Cyrille Chaudoit résument l'idée clé défendue par Virginie Sassoon : les écrans ne sont pas le cœur du problème.- Le vrai scandale, c'est l'absence de régulation efficace des géants de la tech.- Le vrai danger, c'est un modèle numérique conçu pour capter toujours plus l'attention.- Et le vrai malaise, c'est de voir les parents sommés d'éduquer seuls… dans un monde qui ne joue pas franc-jeu.

This is a recap of the top 10 posts on Hacker News on December 26, 2025. This podcast was generated by wondercraft.ai (00:30): Rob Pike goes nuclear over GenAIOriginal post: https://news.ycombinator.com/item?id=46392115&utm_source=wondercraft_ai(01:50): How uv got so fastOriginal post: https://news.ycombinator.com/item?id=46393992&utm_source=wondercraft_ai(03:11): Package managers keep using Git as a database, it never works outOriginal post: https://news.ycombinator.com/item?id=46391514&utm_source=wondercraft_ai(04:31): Rob Pike Goes Nuclear over GenAIOriginal post: https://news.ycombinator.com/item?id=46389444&utm_source=wondercraft_ai(05:52): FFmpeg has issued a DMCA takedown on GitHubOriginal post: https://news.ycombinator.com/item?id=46394327&utm_source=wondercraft_ai(07:12): Seven Diabetes Patients Die Due to Undisclosed Bug in Abbott's Glucose MonitorsOriginal post: https://news.ycombinator.com/item?id=46388040&utm_source=wondercraft_ai(08:33): My insulin pump controller uses the Linux kernel. It also violates the GPLOriginal post: https://news.ycombinator.com/item?id=46395184&utm_source=wondercraft_ai(09:53): Experts explore new mushroom which causes fairytale-like hallucinationsOriginal post: https://news.ycombinator.com/item?id=46393936&utm_source=wondercraft_ai(11:14): I'm a laptop weirdo and that's why I like my new Framework 13Original post: https://news.ycombinator.com/item?id=46391410&utm_source=wondercraft_ai(12:34): Rob Pike got spammed with an AI slop "act of kindness"Original post: https://news.ycombinator.com/item?id=46394867&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

Effective Gen AI adoption relies on tracking AI skills development. Data-driven learning, personalized training, and real-world metrics ensure employees confidently apply Gen AI to drive measurable business impact. That's the key take-away message of this episode of the Wise Decision Maker Show, which discusses what tracking Gen AI skills can teach us about the future of work.This article forms the basis for this episode: https://disasteravoidanceexperts.com/what-tracking-gen-ai-skills-can-teach-us-about-the-future-of-work/

From all of us at Cloud Realities, MERRY CHRISTMAS!!!! Back in our December 2022 Christmas special, we explored the far reaches of reality, asking whether we live in a simulation and if that even matters. Now, we return to that question with fresh perspectives and new challenges…In this last Cloud Realities podcast of 2025, Dave, Esmee and Rob return to the simulation with Anders Indset, philosopher, author, and long-time friend of the show, revisiting a question that's been quietly running underneath everything we've discussed since 2022: If reality itself is information and what does that mean for being human? TLDR:00:58 – It's Christmas!08:32 – Major announcement and reflections on the Cloud Realities podcast journey15:32 – Celebrating three big wins: B2B Marketing Awards (Best Content, Best Customer Retention) and The Drum (Best Creative Audio)22:55 – Is there a next thing?23:30 – Welcoming Anders Indset, who shares his vision for practical philosophy and the future of human/AI co-evolution32:02 – Exploring the Quantum Economy and the Singularity Paradox58:10 – Deep dive into the Simulation Hypothesis, revisiting the 2022 discussion and Rob is again confused...01:27:45 – Anders enjoying Christmas in the Norwegian wilderness01:29:40 – Edit pointGuestAnders Indset: https://www.linkedin.com/in/andersindset/ or andersindset.comAdditional information: thequantumeconomy.com and tomorrowmensch.comHostsDave Chapmanger: https://www.linkedin.com/in/chapmandr/Esmee van de Gluhwein: https://www.linkedin.com/in/esmeevandegiessen/Rob Snowmananahan: https://www.linkedin.com/in/rob-kernahan/ProductionDr Mike van Der Buabbles: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapmanger: https://www.linkedin.com/in/chapmandr/ SoundBen Jingle: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Snow:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Cloud Realities' is an original podcast from Capgemini

Regular, collaborative check-ins help leaders navigate AI disruption by aligning teams, fostering psychological safety, and driving continuous improvement—turning Gen AI experimentation into real business results. That's the key take-away message of this episode of the Wise Decision Maker Show, which describes how to tame the Gen AI disruption with regular check-ins.This article forms the basis for this episode: https://disasteravoidanceexperts.com/taming-the-gen-ai-disruption-with-regular-check-insDr. Gleb Tsipursky bio https://disasteravoidanceexperts.com/glebtsipursky   Dr. Gleb Tsipursky LinkedIn (send message when connecting) https://www.linkedin.com/in/dr-gleb-tsipursky/   Dr. Gleb Tsipursky's latest books:   "ChatGPT for Thought Leaders and Content Creators: Unlocking the Potential of Generative AI for Innovative and Effective Content Creation" is available at https://amzn.to/3YI2vuc   "Returning to the Office and Leading Hybrid and Remote Teams: A Manual on Benchmarking to Best Practices for Competitive Advantage" is available at https://disasteravoidanceexperts.com/hybrid/   "Never Go With Your Gut: How Pioneering Leaders Make the Best Decisions and Avoid Business Disasters" is available at https://disasteravoidanceexperts.com/nevergut   "The Blindspots Between Us: How to Overcome Unconscious Cognitive Bias and Build Better Relationships" is available at https://disasteravoidanceexperts.com/blindspots   

The intersection of AI and cybersecurity is changing faster than anyone expected, and that pace is creating both incredible innovation and brand-new risks we're only beginning to understand. From deepfake ads that fool even seasoned security professionals to autonomous agents capable of acting on our behalf, the threat landscape looks very different than it did even a year ago. To explore what this evolution means for everyday people and for enterprises trying to keep up, I'm joined by Chris Kirschke, Field CISO at Tuskira and a security leader with more than two decades of experience navigating complex cyber environments. Chris talks about his unconventional path into the industry, how much harder it is for new professionals to enter cybersecurity today, and the surprising story of how he recently fell for a fake Facebook ad that showcased just how convincing AI-powered scams have become. He breaks down the four major waves of InfoSec from the rise of the web, through mobile and cloud, to the sudden, uncontrollable arrival of generative AI. He then explains why this fourth wave caught companies completely off guard. GenAI wasn't something organizations adopted thoughtfully; it appeared overnight, with thousands of employees using it long before security teams understood its impact. That forced long-ignored issues like data classification, permissions cleanup, and internal hygiene to the forefront. We also dive into the world of agentic AI which is AI that doesn't just analyze but actually acts and the incredible opportunities and dangers that come with it. Chris shares how low-code orchestration, continuous penetration testing, context engineering, and security "mesh" architectures are reshaping modern InfoSec. Chris spends a lot of time talking about the human side of all this and why guardrails matter, how easy it is to over-automate, and the simple truth that AI still struggles with the soft skills security teams rely on every day. He also shares what companies should think about before diving into AI, starting with understanding their data, looping in legal and privacy teams early, and giving themselves room to experiment without turning everything over to an agent on day one. Show Notes: [00:00] Chris Kirschke, Field CISO at Tuskira, is here to explore how AI is reshaping cybersecurity and why modern threats look so different today. [03:05] Chris shares his unexpected path from bartending into IT in the late '90s, reflecting on how difficult it has become for newcomers to enter cybersecurity today. [06:18] A convincing Facebook scam slips past his defenses, illustrating how AI-enhanced fraud makes traditional red flags far harder to spot. [09:32] GenAI's sudden arrival in the workplace creates chaos as employees adopt tools faster than security teams can assess risk. [12:08] The conversation shifts to AI-driven penetration testing and how continuous, automated testing is replacing traditional annual reports. [15:23] Agentic AI enters the picture as Chris explains how low-code orchestration and autonomous agents are transforming security workflows. [18:24] He discusses when consumers can safely rely on AI agents and why human-in-the-loop oversight remains essential for anything involving transactions or access. [21:48] AI's dependence on context becomes clear as organizations move toward context lakes to support more intelligent, adaptive security models. [25:46] He highlights early experiments where AI agents automatically fix vulnerabilities in code, along with the dangers of developers becoming over-reliant on automation. [29:50] AI emerges as a support tool rather than a replacement, with Chris emphasizing that communication, trust, and human judgment remain central to the security profession. [33:35] A mock deposition experience reveals how AI might help individuals prepare for high-stress legal or compliance scenarios. [37:13] Chris outlines practical guardrails for adopting AI—starting with data understanding, legal partnerships, and clear architectural patterns. [40:21] Chatbot failures remind everyone that AI can invent policies or explanations when it lacks guidance, underscoring the need for strong oversight. [41:32] Closing thoughts include where to find more of Chris's work and continue learning about Tuskira's approach to AI security.  Thanks for joining us on Easy Prey. Be sure to subscribe to our podcast on iTunes and leave a nice review.  Links and Resources: Podcast Web Page Facebook Page whatismyipaddress.com Easy Prey on Instagram Easy Prey on Twitter Easy Prey on LinkedIn Easy Prey on YouTube Easy Prey on Pinterest Tuskira Chris Kirschke -LinkedIn

Awards organizer cites ‘hard stance' on gen AI. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Send us a textJust Peaches in the team room for a straight-up Daily Drop—no guests, no fluff, no pretending this is anything other than a military news brain dump with commentary. He rips through the latest Army, Navy, Air Force, Marine Corps, and Space Force headlines, calls out public affairs stories that say nothing, breaks down AI hype in the DoD, reacts to V-22 updates, joint exercises, NATO tech, recruiting wins, Space Force moves, and why interoperability is still hard as hell. This isn't polished. It's not scripted. It's one operator reading the news, connecting dots, and telling you what actually matters. If you want clean narratives, look elsewhere. If you want context and blunt takes, this one's for you. ⏱️ Timestamps: 00:00 Ones Ready Daily Drop—solo and unsupervised 01:15 What a Daily Drop actually is 04:30 Why military PA stories say everything and nothing 10:40 Army, Guard, and international partnership headlines 18:20 Flood response, disaster relief, and why it matters 24:00 Navy deployments, drones, and unmanned systems 32:00 AI, GenAI, NipperGPT, and why prompts expose ignorance 40:30 Joint exercises and interoperability reality 48:10 V-22 updates and aviation trust issues 54:30 Fitness standards, innovation wins, and Spark Tank 01:02:00 Space Force moves and leadership shifts 01:09:30 Final thoughts, accountability, and sign-off

ChatGPT ads are coming y'all.

In this episode of Transform Your Workplace, Brandon Laws sits down with Kate McKinnon, a fractional Chief People Officer with deep experience in high-pressure, high-visibility environments across sports and entertainment. Kate shares what it takes to protect culture when speed and stress are constant, how to address burnout and disengagement without pretending everything is fine, and why "stop, start, continue" feedback loops can help leaders turn frustration into action. They also unpack generational friction, the reality of AI reshaping HR and leadership work, and why developing first-time managers before they step into leadership is one of the most overlooked levers for performance. The conversation closes with practical ways to build belonging without huge budgets, and a reminder that grace and kindness still matter in modern workplaces. 0:00 Welcome to Transform Your Workplace + episode overview 2:00 Meet Kate McKinnon and why her background matters 4:00 Protecting culture in high-pressure, high-performance environments 6:00 Burnout, disengagement, and the power of "stop, start, continue" 9:00 Generational friction at work and how leaders can bridge the gap 11:00 Gen AI, new grads, and the future of work 13:00 Making work more human in an AI-driven workplace 15:00 Why great performers struggle as new managers 17:00 The future of learning and development: microlearning vs in-person 20:00 Belonging without big budgets: practical, low-cost ideas 22:00 Leadership lessons from crisis, M&A, and COVID 25:00 What sports culture teaches us about performance and growth 27:00 Using data, feedback, and scorecards to drive engagement 29:00 Bridging the gap from college (and military) to career 32:00 What the next decade of culture and leadership will demand 34:00 Final thoughts: grace, kindness, and what leaders should remember   A QUICK GLIMPSE INTO OUR PODCAST Podcast: Transform Your Workplace, sponsored by Xenium HR Host: Brandon Laws In Brandon's own words: "The Transform Your Workplace podcast is your go-to source for the latest workplace trends, big ideas, and time-tested methods straight from the mouths of industry experts and respected thought-leaders. About Xenium HR Xenium HR is on a mission to transform workplaces by providing expert outsourced HR and payroll services for small and medium-sized businesses. With a people-first approach, Xenium helps organizations create thriving work environments where employees feel valued and supported. From navigating compliance to enhancing workplace culture, Xenium offers tailored solutions that empower growth and simplify HR. Whether managing employee relations, payroll processing, or implementing impactful training programs, Xenium is the trusted partner businesses rely on to elevate their workplace experience. Discover how Xenium can transform your workplace: Learn more [https://www.xeniumhr.com/] Connect with Brandon Laws: LinkedIn [https://www.linkedin.com/in/lawsbrandon] Instagram [https://www.instagram.com/lawsbrandon] About [https://xeniumhr.com/about-xenium/meet-the-team/brandon-laws] Connect with Xenium HR: Website [https://xeniumhr.com/] Learning & Development Programs [https://xeniumhr.com/learning-development] LinkedIn [https://www.linkedin.com/company/xenium-hr] Facebook [https://www.facebook.com/XeniumHR] Twitter [https://twitter.com/XeniumHR] Instagram [https://www.instagram.com/xeniumhr] YouTube [https://www.youtube.com/user/XeniumHR]

Doug Green, Publisher of Technology Reseller News, spoke with Raj Darji, Founder & CEO of Aarav Solutions, about the company's launch of two generative AI accelerators—InsightForge and Omni360—designed to help communications service providers modernize billing operations, sales workflows, and customer engagement. Aarav Solutions is a long-standing Oracle Communications implementation partner with more than a decade of domain expertise across Oracle BRM and related telecom platforms. Darji explained that this deep operational knowledge is embedded directly into Aarav's GenAI accelerators, enabling CSPs to adopt AI without disrupting existing infrastructure. “We are not experimenting with AI—we are applying it where telecom operators feel the most pain, inside billing and operations,” said Darji. InsightForge is a GenAI accelerator purpose-built for Oracle BRM that allows business, finance, and operations teams to query complex billing data using natural language—without writing SQL or relying on back-office specialists. By translating plain-language questions into database queries, InsightForge delivers real-time visibility into invoices, balances, taxes, and discrepancies, significantly reducing operational dependencies and response times. Omni360 extends this capability with an AI-driven CRM and CPQ platform tightly integrated with BRM. Designed for mid-market CSPs, MVNOs, and enterprise connectivity providers, Omni360 unifies CRM and billing into a single pane of glass and enables sales teams to generate products, pricing, and quotes through natural-language prompts. Introduced at Mobile World Congress, both solutions drew strong interest for demonstrating how GenAI can deliver immediate, practical value rather than remain a conceptual buzzword. Learn more about Aarav Solutions at https://www.aaravsolutions.com/. Software Mind Telco Days 2025: On-demand online conference Engaging Customers, Harnessing Data

You're winding down for the year?

It's YOUR time to #EdUp with Dr. Anne Leftwich, Associate Vice President for Learning Technologies, & Dr. Justin Hodgson, Strategic Director of GenAI, Faculty Initiatives, Indiana UniversityIn this episode, part of our Academic Integrity Series, sponsored by ⁠Integrity4EducationYOUR cohost is Thomas Fetsch, CEO, Integrity4EducationYOUR host is ⁠Elvin Freytes⁠How does a university respond to a 30% increase in academic misconduct cases by transforming faculty from reactive policing to proactive AI empowerment through programs like the Digital Gardener Initiative & the Generative AI Faculty Fellows Program?What happens when faculty development becomes a game where professors complete challenges & compete while learning to use AI as a partner in teaching, research & service?How can higher education partner with tech companies to influence AI model training & ensure data reflects thoughtful consideration of humanity's best interests rather than just sources like Reddit?Listen in to #EdUpThank YOU so much for tuning in. Join us on the next episode for YOUR time to EdUp!Connect with YOUR EdUp Team - ⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠Elvin Freytes⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠& ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Dr. Joe Sallustio⁠⁠⁠⁠⁠● Join YOUR EdUp community at ⁠The EdUp Experience⁠We make education YOUR business!P.S. Want to get early, ad-free access & exclusive leadership content to help support the show? Then ⁠⁠​subscribe today​⁠⁠ to lock in YOUR $5.99/m lifetime supporters rate! This offer ends December 31, 2025!

GenAI is one of the fastest-growing consumer tools in history. But what have we learned about competitive dynamics in the industry? Economists Andrea Asoni and Matteo Foschi join Jaclyn Phillips and Lexi Michaud to discuss what early economic insights can help us understand about the risks and benefits posed by the growth of AI. Listen to this episode to learn more about how the development of AI impacts market development. With special guests:Andrea Asoni, Vice President, Charles River Associates and Matteo Foschi, Vice President, Charles River Associates Related Links: Contested ground: Early competition and market dynamics in generative AI Hosted by: Jaclyn Phillips, Proskauer Rose and Lexi Michaud, Fried Frank

The Today in Manufacturing Podcast is brought to you by the editors of Manufacturing.net and Industrial Equipment News (IEN).This week's episode is brought to by Laserfiche. Generative AI is turbocharging modernization across the industrial sector by saving time, processing data, and increasing worker productivity during the implementation of new tools and technologies.This new paper from Manufacturing.net, "How AI Tackles Manufacturing's Top 5 Implementation Challenges," gives you the five key areas throughout the industrial enterprise where GenAI knocks over implementation hurdles. Download it right now.Every week, we cover the five biggest stories in manufacturing, and the implications they have on the industry moving forward. This week:- Ford Scraps Fully-Electric F-150 Lightning- Volkswagen Announces Unprecedented Plant Closure- Anheuser-Busch to Close Three U.S. BreweriesIn Case You Missed It- Largest U.S. Transformer Maker Faces Nearly $1 Million in OSHA Fines- Study Finds Drivers Struggle to Multitask When Using Dashboard Touch Screens- Manufacturing's Legacy Forms are Leaking DataPlease make sure to like, subscribe and share the podcast. You could also help us out a lot by giving the podcast a positive review. Finally, to email the podcast, you can reach any of us at David, Jeff, or Anna [at] ien.com, with “Email the Podcast” in the subject line.

Jeetu Patel knows a few AI secrets. As the President of one of the largest companies in the world, he's helped pave the AI adoption roadmap. At Cisco, they provide full-stack, enterprise AI solutions spanning infrastructure, security, observability, and operations to the world's largest companies. So naturally, Jeetu could write a legit playbook on what's slowing enterprises down in the AI fast lane and how they can overcome those bottlenecks. And naturally, Jeetu is gonna share it all with us. The 3 Big Obstacles Holding AI Adoption Back -- An Everyday AI Chat with Cisco President Jeetu PatelNewsletter: Sign up for our free daily newsletterMore on this Episode:Episode PageJoin the discussion on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Enterprise AI Adoption Rates & ChallengesAI Workflow Automation Phase ExplainedThree Big Obstacles to AI AdoptionInfrastructure Constraints for Enterprise AITrust Deficit in AI SystemsData Gaps Impacting AI SuccessMeasuring ROI on Enterprise AI DeploymentFuture Trends: Agentic AI and Original InsightsTimestamps:00:00 AI Adoption Challenges in Enterprise05:18 AI Adaptation: The Key Strength08:56 AI Infrastructure and Trust Challenges10:23 Building Trust and Harnessing Data13:27 Unsatiated Demand Signals Growth19:12 Proactive AI Model Safeguards22:07 AI Strategy and Business Growth26:09 Key Metrics for AI Success28:10 Guardrails for AI Vulnerabilities31:34 AI Unlocking Revolutionary DiscoveriesKeywords:AI adoption, obstacles to AI adoption, enterprise AI, generative AI, AI strategies, chatbots, autonomous agents, workflow automation, business productivity automation, infrastructure for AI, AI power consumption, data center capacity, compute capacity, GPUs, Nvidia, AMD, network bandwidth, CapEx in AI, AI bubble, national security and AI, economic growth and AI, AI trust deficit, securing AI, AI safety, AI hallucinations, large language models, model unpredictability, AI guardrails, algorithmic jailbreak, AI security stack, AI defense, company data as moat, AI data pipeline, data gap in AI, machine data, human data, synthetic data, time series data, data correlation, AI model training, AI ROI, trust in AI systems, agentic workflows, future of AI, robotics, humanoid AI, physical AI, original insights with AI, economic prosperity with AI, AI-generated knowledge, workflow automation with AI agents, scaling AI in enterprisesSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

Links James on LinkedIn (https://www.linkedin.com/in/jahuang/) Mike on LinkedIn (https://www.linkedin.com/in/dominucco/) Mike's Blog (https://dominickm.com) Show on Discord (https://discord.com/invite/k8e7gKUpEp) Alice Promo (https://go.alice.dev/data-migration-offer-hands-on) AI on Red Hat Enterprise Linux (RHEL) Trust and Stability: RHEL provides the mission-critical foundation needed for workloads where security and reliability cannot be compromised. Predictive vs. Generative: Acknowledging the hype of GenAI while maintaining support for traditional machine learning algorithms. Determinism: The challenge of bringing consistency and security to emerging AI technologies in production environments. Rama-Llama & Containerization Developer Simplicity: Rama-Llama helps developers run local LLMs easily without being "locked in" to specific engines; it supports Podman, Docker, and various inference engines like Llama.cpp and Whisper.cpp. Production Path: The tool is designed to "fade away" after helping package the model and stack into a container that can be deployed directly to Kubernetes. Behind the Firewall: Addressing the needs of industries (like aircraft maintenance) that require AI to stay strictly on-premises. Enterprise AI Infrastructure Red Hat AI: A commercial product offering tools for model customization, including pre-training, fine-tuning, and RAG (Retrieval-Augmented Generation). Inference Engines: James highlights the difference between Llama.cpp (for smaller/edge hardware) and vLLM, which has become the enterprise standard for multi-GPU data center inferencing.

GenAI now sits inside content workflows, SDR outreach, and competitive intelligence. Marketing teams are seeing real wins and real growing pains, and the open question is where to focus next. To answer that, Drew brings together Kelly Hopping, John McKinney (Cornerstone Licensing), and Brian Hankin (Altium Packaging) to share the AI plays they are running right now and how they're leading the charge. Here's how: In this episode: Kelly shows how AI weaves through content, SDR workflows, web chat, product work, and SEO, plus how OKRs and certifications lift AI fluency across the team. John uses AI agents for competitor tracking, outbound support, and coding, and treats AI as a sparring partner for strategy before it reaches the C suite. Brian runs an AI campaign engine that builds multi-touch programs in minutes and tracks lifts in engagement, qualified leads, proposals, and wins. Plus: How AEO connects to SEO and what needs to shift for LLM-driven discovery How leaders model AI use with internal knowledge bases and cross-functional pilots How to structure AI readiness Where CMOs can start Tune in if you want AI use cases you can put to work now and a clearer view of where to point your team next. For full show notes and transcripts, visit https://renegademarketing.com/podcasts/ To learn more about CMO Huddles, visit https://cmohuddles.com/

Douglas Matty is exiting his role as the Pentagon's chief digital and artificial intelligence officer and moving on to focus on the Trump administration's “Golden Dome for America” missile defense initiative, DefenseScoop has learned. Principal Deputy CDAO Andrew Mapes will lead the department's AI hub in an acting capacity until a new CDAO is hired. Ahead of reaching full operational capacity in 2022, the AI-accelerating office merged and integrated multiple technology-focused predecessor organizations at the Pentagon, including the Joint Artificial Intelligence Center (JAIC), Defense Digital Service (DDS), Office of the Chief Data Officer, and the Maven and Advana programs. The DOD's vision and priorities for the CDAO have been reconfigured several times since its inception. And while AI is a major priority for the U.S. government under President Donald Trump, the Pentagon's CDAO office has seen an exodus of senior leaders and other technical employees this year. Matty's departure also comes as the office is hustling to execute on a range of DOD-wide efforts to speed up the delivery and fielding of data analytics, automation, computer vision, machine learning and other next-generation AI capabilities for military and civilian personnel. Last week, Pentagon leaders unveiled a new purpose-built platform — GenAI.mil — to provide commercial options directly to most of its workforce on their desktops. The Centers for Medicare & Medicaid Services has tapped ID.me to verify the identities of beneficiaries on Medicare.gov, according to a Tuesday announcement from the identity-proofing company. ID.me will be available as an option for identity verification and sign-in on Medicare.gov starting in early 2026, per the release. The deal adds to the growing number of federal programs opting to use the digital identity service that leverages facial recognition technology and has been the subject of some controversy in the past. Already, ID.me is used at 21 federal agencies, including the Social Security Administration and Department of Veterans Affairs, per the release. Opting in means an ID.me user could sign in with the same credentials at any of the other federal, state or private-sector entities that use the service, the company said in a statement to FedScoop.

What happens when AI gets powerful, but verification becomes the bottleneck? In this candid, end-of-year conversation, Clearbrief Founder & CEO Jacqueline Schafer breaks down why accuracy, sourcing, and trust - not raw model power are the real constraints on legal AI adoption today. Listeners walk away with a clear mental model for where AI actually delivers ROI in law firms and corporate legal teams, and why the "last mile" is the battleground that matters now.  Hosted by David Cowen Key Topics Covered: Why AI output that can't be verified fast is worse than useless, and how verification time kills ROI The "last mile" framework: where legal workflows break down and why most tools stop too early How Clearbrief was built around mistake-catching before GenAI and why that design choice aged perfectly What customer discovery really looks like (200+ lawyer interviews, brutal feedback included) The shift toward insourcing: which litigation and investigation tasks stay in-house and which never will Why general-purpose chatbots help with drafting, but fail at delivery, defensibility, and trust A practical metaphor for AI adoption speed: the engine is fast, the road isn't, and lawyers are the drivers

On this episode of the Scouting For Growth podcast, Sabine VdL talks to Marinela Profi, Global Market Strategy Lead for AI, GenAI and Agentic AI at SAS, about the rise of agentic AI and how we will move from hype to real, reliable AI. In today's episode, we'll discuss: Why LLMs alone don't solve business problems – and what does, how governance is becoming the new frontier of AI trust, and what leaders should expect by 2026, as enterprises shift from experiments to autonomous, explainable intelligence. KEY TAKEAWAYS A generative AI chatbot is really good and answering questions, generating text, or summarising content. But, it typically stops when it comes to conversation. On the other hand, an AI agent goes beyond that, it can take action, it has goals, memory, reasoning capabilities and can orchestrate multi-set workflows using a combination of not just large-language models but also rules, data and analytics. Generative AI talks, and agentic AI does. The 5-step lifecycle of an agent is a framework I put together to help me and my customers understand what an agent actually does step-by-step in practice. 1. Perception 2. Cognition 3. Decisioning 4. Action, and 5. Learning. Governance boards in 2026 will act more like digital oversight committees, they will ensure that agents aren't just smart, but they are safe, explainable and accountable.  BEST MOMENTS  ‘Post action the agent learns from feedback from a human operative. It's important to monitor the learning loops, you cannot allow the agent to “self-update” in ways that are uncontrolled.'  ‘How autonomous should an agent be? 90% of the time it depends on the risk and impact of the task.' ‘Autonomy without accountability is a risk multiplier.' ‘Governance doesn't stop at deployment, performance must be continuously monitored.' ABOUT THE GUEST Marinela Profi helps organizations move from AI hype to trusted impact. As Global Market Strategy Lead for AI, GenAI and Agentic AI at SAS, she works with enterprises in financial services, healthcare, and government to build AI systems that don't just act fast—but act responsibly. With an MBA and a Master's in Statistics and AI, Marinela bridges two worlds: translating complex data science into clear business strategy. Her work focuses on how agentic AI—intelligent systems that perceive, reason, and act autonomously—can deliver governed, explainable decisions instead of black-box predictions. A frequent keynote speaker at international AI and analytics events, she shares insights on the evolution from generative to agentic AI and the new frontier of AI governance, trust, and human-AI collaboration. Marinela is also an Advisory Board Member for Wake Technical Community College's Data Science Program, helping shape future-ready curricula that connect classroom learning with real-world AI innovation. 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/

Our Head of Corporate Research Andrew Sheets and Chief Investment Officer for Morgan Stanley Wealth Management Lisa Shalett unpack what's fueling persistent U.S. inflation and how investors could adjust their portfolios to this new landscape.Read more insights from Morgan Stanley.----- Transcript -----Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Head of Corporate Credit Research at Morgan Stanley. Lisa Shalett: And I'm Lisa Shalett, Chief Investment Officer for Morgan Stanley Wealth Management. Andrew Sheets: Today, is inflation really transitory or are we entering a new era where higher prices are the norm? Andrew Sheets: It's Thursday, December 18th at 4pm in London. Lisa Shalett: And it's 11am in New York. Andrew Sheets: Lisa, it's great to talk to you again. And, you know, we're having this conversation in the aftermath of, kind of, an unusual dynamic in markets when it comes to inflation. Because inflation is still hovering around 3 percent. That's well above the Federal Reserve's 2 percent target. And yet the Federal Reserve recently lowered interest rates again. Fiscal policy remains very stimulative, and I think there's this real question around whether inflation will moderate? Or whether we're going to see inflation be higher for longer. And you know, you are out with a new report touching on some of the issues behind this and why this might be a structural shift higher in inflation. So, we'd love to get your thoughts on that, and we'll drill down into the various drivers as this conversation goes on. Lisa Shalett: Thanks Andrew. And look, I think as we take a step back, and the reason we're calling this a regime change is because we see factors for inflation coming from both the demand side and the supply side. For example, on the demand side, the role of the infrastructure boom, the GenAI infrastructure boom, has become global. It has caused material appreciation of many commodities in 2025. We're seeing it obviously in some of the dynamics around precious metals. But we're also seeing it in industrial metals. Things like copper, things like nickel. We're also seeing demand factors that may stem from the K-shaped economy. And the K-shaped economy, as we know, is really about this idea that the wealthiest folks are increasingly dominating consumption. And they are getting wealthy through financial asset inflation. On the supply side, there are dynamics like immigration, dynamics around the housing market that we can talk about. But perhaps the wrapper around all of it is how policy is shifting – because increasingly policymakers are being constrained by very high levels of debt and deficits. And determining how to fund those debts and deficits actually removes some of the degrees of freedom that central bankers may have when it comes to actually using interest rates to constrain demand. Andrew Sheets: Well, Lisa, this is such a great point because we're financial analysts. We're not political analysts. But it seems safe to say that voters really don't like inflation. But they also don't like some of the policies that would traditionally be assigned to fight inflation – be they higher interest rates or tighter fiscal policy. And even some of the more recent political shifts that we've seen – I'm talking about the U.S. around, say, immigration policy could arguably be further tightening of that supply side of the economy – measures designed to raise wages, almost explicitly in their policy goals. So how do you see that dynamic? And, again, kind of where does that leave, you think, policy going forward? Lisa Shalett: Yeah. I think the very short answer – our best guess is that policy becomes constrained. So, on the monetary side, we're already seeing the Fed beginning to signal that perhaps they're going to rely on other tools in the toolkit. And what are those tools in the toolkit? Well, they're managing the size of their balance sheet, managing the duration or the mix of things that they hold in the balance sheet. And it's actual, you know, returns to how they think about reserve management in the banking system. All of those things, all of those constraints may enable the U.S. government to fund debts, right? By buying the Treasury bill issuance, which is, you know, swollen to almost [$]2 trillion a year in terms of U.S. deficits. But on the fiscal side, right, the interest payments on debt, begins to crowd out other government spending. So, policy itself in this era of fiscal dominance becomes constrained – both in, you know, Washington, D.C. and from Congress – what they can do, their degrees of freedom – and what the central bank can do to actually control inflation. Andrew Sheets: Another area that you touch on in your report is energy and technology, which are obviously related with this large boom that we're seeing – and continue to expect in AI data center construction. This is a lot of spending on the technology. This is a lot of power needed to power that technology and U.S. data center electricity demand is growing at a rapid rate. And transmission constraints are causing prices to go up. A price that is a pretty visible price for a lot of people when they get their utility bill. So, how do these factors you think shape the story? And where do you think they're going to go as we look into the future? Lisa Shalett: Yeah, 100 percent. I mean, I think, you know, when we talk about, you know, who's going to dominate in Generative AI globally, one of the factors that we have to take into consideration is what is the cost of power? What is the cost of electricity? What is the age of the infrastructure to both generate that electricity and transport it? And transmit it? This is one of the areas where the U.S., at the minute, is facing genuine constraints. When you think about some of the forecasts that have been put out there in terms of $10 trillion of spending related to Generative AI, the number of data centers that are going to be built, and the power shortfall that has been forecast. We're talking about someone having to pay the price, if you will, to ration power until you can upgrade the grid. And in the U.S., that grid upgrade, to be blunt, has lagged some of the rest of the world. Not only because the rest of the world was slower to modernize and leapfrogged in many ways. But we know in China, for example, they have one of the lowest electricity generation costs on the planet. That is an advantage for them. So, we have to consider that power generation writ large is potentially a force for upward inflation, at least in the short term. Andrew Sheets: So we have the fiscal policy backdrop. We have an AI spending backdrop both contributing to the demand side of inflation. We have these supply constraints, whether it's housing or labor also, you know, potentially being more structural drivers of higher inflation. The question I'm sure that investors are asking you is, what should they do about it? So, can you walk us through the key strategies that investors might want to consider as they navigate a new inflationary regime? Lisa Shalett: Sure. So, the first thing that we think it's really important for folks to appreciate is that typically when we've been in these higher inflation regimes in the past, stocks and bonds become positively correlated. And what that means is that the power of a very simple 60-40 or stock-bond-cash portfolio to provide complete or optimal diversification fades. And it requires investors to potentially consider investing, especially beyond fixed income. Stocks very often are pro-inflationary assets; meaning many, many companies have the power to pass through price increases. If you are consuming income from a fixed income or a bond instrument, inflation is your enemy, right? Because it's eating into your real returns. And so, one of the things that we're talking with our clients a lot about in terms of portfolio construction are things like adding real assets, adding infrastructure assets, adding energy, transportation assets, adding commodities. Adding gold even, to a certain extent. You know, there may be cryptocurrencies that have lower correlations to their portfolios. Andrew Sheets: Just to play devil's advocate, you can imagine that some investors might say, ‘Well, I can look in the market at long-term inflation expectations.' And those long-term inflation expectations have been kind of stable and a bit above the Fed's target. But not dramatically. So, what do you say to that? And what do you think those markets either might be missing? Or how could investors leverage that more benign view that's out there in the market? Lisa Shalett: Yeah, so look, I think here's where the debate, right? Our perception has been that inflation expectations have remained extraordinarily anchored – because investors have actually reasonably short memories on the one hand, and we have, by and large, been in disinflationary times. Second, there's extraordinary faith in policy makers – that policy makers will fight inflation. And I think the third thing is that there's extraordinary faith in the deflationary forces of technology. Now, all three of those things may absolutely, positively be true. The problem that we have is that the alternate case, right? The case that we're making – that maybe we're in a new inflationary regime is not priced, and the risk is non-zero. And so, what we see, and what we're watching is – how steep does the yield curve get, right? As we look at yields in the 10-30-year tenure – what is driving those rates higher? Is it a generic term premium? Or are we starting to see an unanchoring, if you will, of inflation expectations. And it takes a while for people to appreciate regime change. And so, look, as is always the case, there's no absolutes in the market. There's no one theory that is priced and the other theory is not. But sometimes you want to hedge, and we think that we're going through a period where diversified portfolios and hedging for these alternative outcomes -- because there are such powerful structural crosscurrents – is the preferred path. Andrew Sheets: Lisa, thanks for sharing your insights Lisa Shalett: Of course, Andrew. That's my pleasure. Andrew Sheets: As a reminder, if you enjoy Thoughts on the Market, please take a moment to rate and review us, wherever you listen. It helps more people find the show.

Did AI end up being a political force this year?

Take charge of shifting tariffs with Gen AI. Learn how it delivers cleaner data, automates compliance, and empowers effective responses.

Don't lie -- when you open ChatGPT, you're looking for a quick copy-and-paste solution. We've all been there. What if I told you that was kinda the worst way possible to use some of the world's most powerful technology. Spoiler alert: it kinda is. Make sure to catch today's episode for some creative frameworks to change how you use LLMs. Creative Frameworks for Problem-Solving with Generative AI -- An Everyday AI Chat with Jordan Wilson (PS - Was hoping to have the PT. 2 Roadmap review ready to go, but feeling under the weather. Pt 2 will drop soon!)Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion:Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Creative Frameworks for Generative AI Problem SolvingHuman Agency vs. AI Efficiency DebateUsing Large Language Models as Thought PartnersPrompt Engineering vs. Context Engineering EvolutionGeneric Parts Technique for Abstract ThinkingSCAMPER Framework for Business InnovationHuman-AI Collaboration: Enhancing Creative OutputsOvercoming Cognitive Biases in AI-Assisted StrategyTimestamps:00:00 "Using AI as Thought Partner"04:06 "AI's Role in Creative Problem-Solving"08:13 "Broadening Problem-Solving Approaches"13:11 "Using Multiple Tools for Insight"15:07 "SCAMPER Framework Explained"17:32 "Rethinking Problems with SCAMPER"22:24 "Embracing Difference in Expertise"24:45 "Building Creative Confidence"Keywords:Generative AI, problem solving frameworks, creative frameworks, large language models, AI thought partner, augmenting human intelligence, creative problem solving, prompt engineering, context engineering, agency over output, human-AI partnership, divergent thinking, convergent thinking, psychological distance, cognitive bias, creative confidence, creative agency, generic parts technique, SCAMPER framework, substitute, combine, adapt, modify, put to another use, eliminate, reverse, creative velocity, innovation, agentic capabilities, iterative problem solving, model reasoning, human in the loop, decision making, strategy, domain transfer, abstraction, functionally fixated thinking, solution exploration, pain point analysis, authentication, friction reduction, workflow improvement, technology product management, practical AI use cases, collaborative AI techniques, business problem solving, structured problem solving, metacognition, challenging output quality,Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

In this special episode, host Cindi Howson pulls together the most useful, and hard-won, lessons from a year of conversations with Data Chiefs leading the GenAI charge. With generative and agentic AI no longer a side experiment, this episode spotlights five practices early adopters can rely on to move from pilots to profit. Expect straight talk on what to prioritize, how to bring people with you, and how to scale AI with the trust, literacy, and guardrails that make impact stick.Key Moments:Tying AI to Real Dollars with Anand Iyer, Ecolab (02:10): Anand cuts through the GenAI FOMO and brings everything back to a simple survival test: if you can't draw a straight line from an AI initiative to top-line growth or bottom-line savings, it won't last. His lesson is a sharp reminder that “cool” doesn't scale, value does. Leading Through Ambiguity with Karen Stroup, WEX (06:01): Karen names what everyone's feeling: ambiguity is paralyzing. She explains how leaders earn trust by shrinking the unknown into learnable, bite-sized experiments and creating the psychological safety people need to engage instead of resist.Building Practical AI Literacy at Scale with Josh Cunningham, Lloyds Banking Group (12:42):  Josh shares how Lloyds Banking Group makes literacy impactful by meeting people where they are. Rather than one-size-fits-all training, they pair broad fundamentals with role-specific learning so every business unit can build confidence in ways that match their actual work. Scaling Responsible Agentic AI with Noelle Russell, AI Leadership Institute (25:09): Noelle steps in with a practical framework for building agentic systems that don't go rogue. She walks through the POET framework and stresses that responsible AI isn't a final checkpoint. It's something you embed from the first idea to production, with guardrails that protect people and outcomes.Embedding AI Where Work Happens with Ilan Twig, Navan (32:35): Ilan tells a classic early-adopter story: start with a business problem, move fast, and be ruthless about what needs building versus buying. His lesson is that AI wins when it's inside the workflow, supporting decisions at the point of impact rather than living in a separate tool. Don't Let Perfection Stall Progress with Ketan Karkhanis, ThoughtSpot (40:59): Ketan shares a culture gut-check: waiting for perfect metrics, perfect KPIs, or perfect clarity is how progress dies. He argues for visible, trust-building iteration, because in AI, speed to learning beats speed to certainty. Key Quotes:“One thing that people sometimes forget is that at the end of the day, it's all about are we either saving money or making money? And are you able to show that in the bottom line or the top line in a measurable way?” - Anand Iyer“I don't think there's any chief anything officer that should not be considering AI today. I think if you're not considering AI, you are at the risk of being disrupted because you're not going to be learning at the pace with the rest of the industry, and there's someone out there looking for a better way.” - Karen Stroup“It's trying your best to meet people where they are… Finding a way to anchor the [AI] learning to something that's relevant to their day-to-day role is always going to make it land better.” - Josh Cunningham“ When people lose 70% of their trust in you, they just don't buy from you, they don't work for you, they don't talk about you… and your business starts to die. I think that trust component is a human component… and it is underpinning all the other philosophies that I have.” - Noelle Russell“When you asked me about how to educate yourself on AI, I think that companies must make a decision, and quickly, this or that.” - Ilan Twig“ Don't let perfection be the enemy of progress.” - Ketan KarkhanisGuest Bios Anand IyerAnand Iyer is the SVP, Chief Data Officer at Ecolab, where he leads the company's global data and analytics strategy. Based in Mechanicsburg, Pennsylvania, he oversees enterprise data governance, business intelligence, engineering, and advanced analytics to accelerate Ecolab's digital transformation. Since joining in 2018, Anand has held several senior roles, including VP of Enterprise Architecture and VP of Architecture for Commercial Digital Solutions, helping to scale IoT and data-driven platforms across the organization.Karen StroupKaren joined WEX in 2022 as Chief Digital Officer, a newly created role. She brings more than 15 years of experience leading product management, digital, and innovation organizations focused on software as a service offerings, primarily in financial services.Josh CunninghamJosh Cunningham is the Group Head of Data and AI Culture at Lloyds Banking Group, where he leads the Data Culture Pillar—one of five strategic pillars in the Group's data strategy. He is focused on embedding data-driven mindsets across the organization and empowering teams to unlock the full value of data.Noelle RussellNoelle Russell is a multi-award-winning speaker, author, and AI Executive who specializes in transforming businesses through strategic AI adoption. She is a revenue growth + cost optimization expert, 4x Microsoft Responsible AI MVP, and named the #1 Agentic AI Leader in 2025. She has led teams at NPR, Microsoft, IBM, AWS and Amazon Alexa, and is a consistent champion for Data and AI literacy and is the founder of the "I ❤️ AI" Community teaching responsible AI for everyone.Ilan TwigIlan Twig is the co-founder and Chief Technology Officer (CTO) of Navan, the leading modern travel and expense management platform, globally. As CTO, Ilan drives Navan's product development and engineering efforts, leveraging cutting-edge technologies — including AI — to enhance user experience and operational efficiency. Ketan KarkhanisKetan Karkhanis is the CEO of ThoughtSpot, the Agentic Analytics Platform company. Prior to joining the company in September 2024, Ketan was the Executive Vice President and General Manager of Sales Cloud at Salesforce. He returned to Salesforce in March 2022 after his time as the COO of Turvo, an emerging supply-chain collaboration platform.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

We don't do AI predictions lightly. Everyday AI is trusted by millions each year to help guide them through the muddy AI waters. So in the same way you'd want transparency out of your AI models, we're rolling back the clock on our January 2025 AI predictions we dished with our Roadmap Review. We're busting out the receipts. At the time, these AI predictions seemed nutty. So, did we lead you astray? Or, did we pave the road to paydirt? Let's dive in y'all. 2025 AI Roadmap Rewind: From AI Agent Orchestrators to Deepfakes. The New Tech Order -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion:Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:AI Agent Orchestrators as Job TitleAI Agents in Company Hiring TrendsEnterprise Reasoning Data Collection GrowthAI Driving Professional Services Pricing CrisisUniversal Basic Income and AI Job LossOpen Source AI Models Surpassing ProprietaryChinese AI Model Global Market ImpactPerplexity Answers Engine Business PivotFrontier AI API Price DropsVC Funding Surge in Embodied AIAdvancements in AI Video Generation ToolsAI's Disruption of Traditional Internet ModelsSocial Media Deepfake Misinformation SurgeTimestamps:00:00 "2025 AI Predictions Explained"04:02 "2025 AI Predictions Insights"08:49 AI Agents Classified as Employees11:23 "Transformers vs. Reasoning Models"16:15 AI Impact on Consulting Jobs18:51 "AI Impacts Jobs, Spurs UBI"23:12 Open Models Surge in AI27:13 "Perplexity's AI Pivot Journey"29:23 "Embodied AI Sector Growth"31:36 "Embodied AI Transforms Logistics"36:42 "AI-Driven Internet Future"39:16 Deepfake Fraud Crisis Escalates42:25 AI Success Roadmap RevealedKeywords:Agent orchestrators, AI agent orchestration, AI job titles, orchestration engineer, AI agent architect, human-AI collaboration leader, Adobe agent orchestrator, AO, AI agents, digital FTEs, digital full time employees, AI agent hiring, agent compute costs, Agent Force, hiring digital labor, reasoning models, company reasoning data collection, reasoning token consumption, synthetic data generation, private reasoning engines, unstructured data, proprietary data, professional services pricing crisis, law sector AI disruption, consulting AI transformation, accounting Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

Weird week in AI.

Trump makes a major announcement on Chinese chips, the US military unveils its new AI platform, and tens of thousands of migrant kids who went missing under Biden have been found. Get the facts first with Evening Wire. - - - Ep. 2527 - - - Wake up with new Morning Wire merch: https://bit.ly/4lIubt3 - - - Privacy Policy: https://www.dailywire.com/privacy morning wire,morning wire podcast,the morning wire podcast,Georgia Howe,John Bickley,daily wire podcast,podcast,news podcast Learn more about your ad choices. Visit podcastchoices.com/adchoices