Podcasts about agentic

Can AI manage AI?Rapt AI CTO Anil shares how agentic AI management will transform data centers, reduce costs, and unlock exponential compute at scale.Anil reveals:▫️ The hidden cost of 5% GPU under-utilization▫️ Why current AI models are outpacing infrastructure▫️ The future of agentic AI for data centers▫️ The battle between chip-level vs. evolutionary innovation▫️ How Rapt AI is helping customers maximize tokens per wattA must-watch for AI engineers, data center architects, and tech leaders building the future.Follow more of the Liftoff with Keith:- Spotify: https://open.spotify.com/show/3cFpLXfYvcUsxvsT9MwyAD- Apple Podcasts: https://podcasts.apple.com/us/podcast/liftoff-with-keith-newman/id1560219589- Substack: https://keithnewman.substack.com/- LinkedIn: https://www.linkedin.com/company/liftoffwithkeith/- Newman Media Studios: https://newmanmediastudios.com/For sponsorship inquiries, please contact: sponsorships@wherewithstudio.com

When AI enters the boardroom, it tends to arrive with big promises: productivity, automation, efficiency. But for Francesco Brenna, Global Leader of AI Integration Services at IBM Consulting, the real opportunity isn't just faster workflows—it's rebuilding how business gets done from the ground up. In this episode, recorded in the heat of a New York summer, Francesco joined me to unpack what agentic AI really means for enterprise leaders and why “doing AI right” is about more than picking the latest model. We began by breaking down the term agentic AI, which Francesco defines as the shift from passive assistants to intelligent agents that can actually execute work, not just suggest how to do it. That might sound subtle, but it's a huge leap. And it's not one companies can take by simply layering AI on top of broken or inefficient processes. Instead, IBM is helping its clients rethink entire workflows, starting not with the tech stack, but with the business outcome. Francesco explains why data readiness is still the number one challenge. While many companies have talked about modernizing their data foundations, few have done it in a way that supports grounded, contextual, reliable AI agents. He introduces the idea of “data products” as a way to anchor agent behavior in the right context, feeding into IBM's three-layer model: user experience, orchestration, and data. We also explored the growing role of standards like Model Control Protocol (MCP), which could make secure integration with legacy systems more realistic at scale. Francesco highlights how IBM is addressing access control, security, and governance to ensure agentic systems are not only powerful but also trustworthy and accountable. There's plenty here for enterprise leaders wondering how to move AI projects out of pilot mode. From real examples in customer service, insurance, and pharma, to IBM's internal strategies for employee upskilling, Francesco shares what early success looks like and why hackathons, hands-on experience, and human-centered design are critical.

‘Attention Is All You Need', co-wrote by Illia Polosukhin in 2017, laid the foundation for arguably one of the most consequential tech breakthroughs in our recent history. 1 year later, Illia founded Near AI, which later became Near Protocol. They were visionaries ahead of their time and, although AI took several more years before becoming a viable product, the experience of scaling databases would later prove valuable and applicable in blockchain world. As a result, Near Protocol aims to become the infrastructure layer for AI apps and the agentic economy. In order to achieve this, scaling was paramount, thus Near is one of the first blockchains to implement execution layer sharding, asynchronous execution and stateless validation, which brought the finality time down to 1.2 seconds, with a block time of 0.6 seconds.Topics covered in this episode:Bowen's backgroundNear's pivot from AI to blockchainsThe role of Near OneNear's tech stack upgradesOptimizing network architectureStateless validation & block propagationSharding & asynchronous executionMessage passing between shards & shard ‘equality'Challenges of implementing stateless validationApplications benefiting from Near's finality speedIntent-based infrastructureAI use cases on NearExpanding Near's ecosystemDevelopment challengesNear's vision and goalsEpisode links:Bowen Wang on XNear OneNear on XSponsors:Gnosis: Gnosis builds decentralized infrastructure for the Ethereum ecosystem, since 2015. This year marks the launch of Gnosis Pay— the world's first Decentralized Payment Network. Get started today at - gnosis.ioChorus One: one of the largest node operators worldwide, trusted by 175,000+ accounts across more than 60 networks, Chorus One combines institutional-grade security with the highest yields at - chorus.oneThis episode is hosted by Friederike Ernst.

Join us this week for The Tech Leaders Podcast, where Gareth sits down with Dr. Nicola Hodson, Chair at IBM UK and Ireland. Dr. Hodson talks about how to manage transformations in complex organisations, how UK Enterprises are adopting AI, and why Quantum computing might be coming sooner than you think. On this episode, Gareth and Dr. Hodson discuss why authenticity is underrated, the evolution of AI regulations, the importance of Polymaths, and how Concorde and a copy of the Encyclopaedia Brittanica inspired her to begin the journey which would lead to IBM. Timestamps: Good leadership, Concorde and the Encyclopaedia Brittanica (2:40) How to drive change in large organisations (9:36) Polymaths (13:50) IBM and Quantum computing (20:00) ITAM Evolution and Hybrid Cloud Management (26:50) Enterprise adoption of Agentic AI (31:10) AI and Graduate jobs (36:40) AI Regulation (41:08) Advice for young IT professionals, and 21-year-old Nicola (43:30) https://www.bedigitaluk.com/

Want Sam's playbook to turn ChatGPT into your executive coach? Get it here: https://clickhubspot.com/sfb Episode 726: Sam Parr ( https://x.com/theSamParr ) and Shaan Puri ( https://x.com/ShaanVP ) talk to Dharmesh Shah ( https://x.com/dharmesh ) about how he's using ChatGPT. — Show Notes: (0:00) Intro (2:00) Context windows (5:26) Vector embeddings (17:20) Automation and orchestration (21:03) Tool calling (28:14) Dharmesh's hot takes on AI (33:06) Agentic managers (39:41) Zuck poaches OpenAI talent w/ 9-figures (49:33) Shaan makes a video game — Links: • Agent.ai - https://agent.ai/ • Andrej Karpathy - https://www.youtube.com/andrejkarpathy — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam's List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

Make way for the next wave of GenAI..... Agentic AI Browsers. And while we've seen rumors that OpenAI is going all-in on an AI browser, the first big player is already here in Perplexity's Comet Browser. Join us as we break down how Perplexity Comet works, what makes it different, and 5 Business Use-Cases for ROI. Square keeps up so you don't have to slow down. Get everything you need to run and grow your business—without any long-term commitments. And why wait? Right now, you can get up to $200 off Square hardware at square.com/go/jordan. Run your business smarter with Square. Get started today.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:Rise of Agentic AI Browsers ExplainedPerplexity Comet's Hybrid AI ArchitectureLocal vs. Virtual Browser Agentic WorkflowsPerplexity Comet Key Features and AccessConnecting Google Services with Comet BrowserAgentic AI Browser Live Demo Use CasesMulti-Platform Personalized Business ResearchAutomated Market Research and Competitive AnalysisPerplexity Comet Cross-Tool Workflow AutomationAgentic AI Browsers vs. Traditional AI ChatbotsTimestamps:00:00 Everyday AI for Business Pros04:56 Agentic AI Browsers Revolutionizing Tech07:49 Advancements in AI Computer Agents09:55 Comet: Chromium-Based Browser Essentials14:43 Streamlining Tasks with Perplexity Integration19:01 AI-Powered Google Drive Personalization21:24 Square: Trusted Business Payment Solutions25:53 Preparing Keynote on Agentic AI29:59 Agentic AI: Revolutionizing Web Browsers31:56 "Agentic AI to Revolutionize Workflows"34:46 Streamlined Scheduling and Market AnalysisKeywords:Perplexity Comet, agentic AI browser, agentic AI, AI browser, business use cases, ROI, Perplexity app, hybrid AI, cloud AI, on-device AI, Comet browser, Chromium, browser automation, multi-platform research, deep research modes, AI desktop assistant, iOS assistant, Google Chrome, browser workflows, Chrome extensionSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Square keeps up so you don't have to slow down. Get everything you need to run and grow your business—without any long-term commitments. And why wait? Right now, you can get up to $200 off Square hardware at square.com/go/jordan. Run your business smarter with Square. Get started today.

Fatih Nayebi is the Vice President of Data & AI at ALDO Group where he leads AI initiatives that transform retail operations and customer experiences. He's also a Faculty Lecturer at McGill University and the author of Foundations of Agentic AI for Retail, the first book on autonomous AI systems in retail. He demystifies agentic ai, federated learning and the promise of A2A (agents to agents) and while these advances will still need humans in the loop. Come learn how AI is reshaping retail and the opportunities of scaling these technologies.

For lawyers, artificial intelligence agents could completely change the way that they do their jobs, handling things such as legal research, document creation and managing workflows with little human supervision. But if we've learned anything since the dawn of the generative AI revolution, the potential benefits of agentic AI come with risks and possible consequences, as well. Learn more about your ad choices. Visit megaphone.fm/adchoices

For lawyers, artificial intelligence agents could completely change the way that they do their jobs, handling things such as legal research, document creation and managing workflows with little human supervision. But if we've learned anything since the dawn of the generative AI revolution, the potential benefits of agentic AI come with risks and possible consequences, as well.

The award-winning Compliance into the Weeds is the only weekly podcast that takes a deep dive into a compliance-related topic, literally going into the weeds to explore a subject more fully. Seeking insightful perspectives on compliance? Look no further than Compliance into the Weeds! In this episode of Compliance into the Weeds, Tom Fox and Matt Kelly discuss a recent Anthropic report that highlights “agentic misalignment in AI systems.” The discussion addresses the unsettling, independent, and unethical behaviors exhibited by AI systems in extreme scenarios. The conversation explores the implications for corporate risk management, AI governance, and compliance, drawing parallels between AI behavior and human behavior using concepts such as the fraud triangle. The episode also explores how traditional anti-fraud mechanisms may be adapted for monitoring AI agents while reflecting on lessons from science fiction portrayals of AI ethics and risks. Key highlights: AI's Unethical Behaviors Comparing AI to Human Behavior Fraud Triangle, the Anti-Fraud Triangle, and AI Science Fiction Parallels Resources: Matt Kelly in Radical Compliance  Tom Instagram Facebook YouTube Twitter LinkedIn A multi-award-winning podcast, Compliance into the Weeds was most recently honored as one of the Top 25 Regulatory Compliance Podcasts, a Top 10 Business Law Podcast, and a Top 12 Risk Management Podcast. Compliance into the Weeds has been conferred the Davey, Communicator, and W3 Awards for podcast excellence. Learn more about your ad choices. Visit megaphone.fm/adchoices

For lawyers, artificial intelligence agents could completely change the way that they do their jobs, handling things such as legal research, document creation and managing workflows with little human supervision. But if we've learned anything since the dawn of the generative AI revolution, the potential benefits of agentic AI come with risks and possible consequences, as well.

In this episode of Practical AI, Chris and Daniel explore the fascinating world of agentic AI for drone and robotic swarms, which is Chris's passion and professional focus. They unpack how autonomous vehicles (UxV), drones (UaV), and other autonomous multi-agent systems can collaborate without centralized control while exhibiting complex emergent behavior with agency and self-governance to accomplish a mission or shared goals. Chris and Dan delve into the role of AI real-time inference and edge computing to enable complex agentic multi-model autonomy, especially in challenging environments like disaster zones and remote industrial operations.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:ROS - Robotic Operating SystemGazeboHugging Face Agents CourseSwarm Robotics | WikipediaChris's definition of Swarming:Swarming occurs when numerous independent fully-autonomous multi-agentic platforms exhibit highly-coordinated locomotive and emergent behaviors with agency and self-governance in any domain (air, ground, sea, undersea, space), functioning as a single independent logical distributed decentralized decisioning entity for purposes of C3 (command, control, communications) with human operators on-the-loop, to implement actions that achieve strategic, tactical, or operational effects in the furtherance of a mission.© 2025 Chris BensonSponsors:Outshift by Cisco: AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows.

Deze keer schuift Frank Ketelaars bij ons aan tafel. Frank is IBM Distinguished Engineer voor het Data Platform en werkt veel met AI. Vandaag bespreken we alles rondom Agentic AI, wat er mogelijk is en hoe de toekomst er uit komt te zien.Of te wel, vibe coding, prompt tuning, probabilistic applications, AI agent tools, verschillende LLMs, AI orchestrator en niet te vergeten de data die hiervoor nodig is. Weer een hele leerzame aflevering! Luister snel.

This week's guest is Karan Vaidya, Co-Founder and CTO of Composio, a platform enabling AI agents to connect with hundreds of tools and take autonomous actions to streamline workflows. We dive into his journey building “Devin” for integrations, why the rise of AI is creating demand for thousands of application connectors, how 90% of Composio's use cases today are agent-driven, and the role early product virality played in their traction. Episode Chapters: 2:00 – Founding with a friend (of 13 years) 3:35 – Evolution of integrations 6:50 – Lightbulb moment 9:20 – Pivoting Composio 12:40 – Agentic workflows 14:30 – Why Composio? 16:47 – Winning developers 25:20 – Build vs. buy 26:20 – AI toolset 28:25 – Agentic internet 30:52 – Quick fire round As always, feel free to contact us at partnerpathpodcast@gmail.com. We would love to hear ideas for content, guests, and overall feedback.This episode is brought to you by Grata, the world's leading deal sourcing platform. Our AI-powered search, investment-grade data, and intuitive workflows give you the edge needed to find and win deals in your industry. Visit grata.com to schedule a demo today.Fresh out of Y Combinator's Summer batch, Overlap is an AI-driven app that uses LLMs to curate the best moments from podcast episodes. Imagine having a smart assistant who reads through every podcast transcript, finds the best parts or parts most relevant to your search, and strings them together to form a new curated stream of content - that is what Overlap does. Podcasts are an exponentially growing source of unique information. Make use of it! Check out Overlap 2.0 on the App Store today.

More than 50% of platform engineering leads don't know how to measure the impact of their platform! Many platform projects fall into common anti-pattern traps that make the platform look great on Day 1 but fail to scale and excite on Day 2!Daniel Bryant - who's profile tagline is "Helping you build better platforms" - is sharing his thoughts on how to measure the value of your platform, how to avoid common anti-patterns and why he believes that the future of platform engineering is in Platform Democracy!And of course, we wrap everything up with a discussion around the impact of Agentic AI towards platform engineering. So - tune in! Here the links we discussedDaniel's LinkedIn Profile: https://www.linkedin.com/in/danielbryantuk/Platform Engineering Book for Technical Product Leaders: https://www.amazon.de/Platform-Engineering-Technical-Product-Leaders/dp/1098153642/ref=asc_df_1098153642Platform Engineering Day Talk: https://www.syntasso.io/post/syntasso-at-platengday-london-presentation-recapKratix Website: https://www.kratix.io/Ai-Driven Platform Engineering Blog: https://www.syntasso.io/post/what-we-learned-building-a-prototype-ai-driven-dev-interface-for-kratixPlatform Democracy: https://www.syntasso.io/post/platform-democracy-rethinking-who-builds-and-consumes-your-internal-platformPlatform Anti Patterns: https://www.syntasso.io/post/platform-building-antipatterns-slow-low-and-just-for-showSlide Deck on Platform Engineering for Devs and Architects: https://speakerdeck.com/danielbryantuk/platform-engineering-for-software-developers-and-architects-redux 

Episode Summary:https://constraintcalculator.scoreapp.com/In this eye-opening solo episode, Jordan Ross, founder of 8 Figure Agency, breaks down a critical and often overlooked issue holding agencies back from true AI integration: schema and tech stack structure. While everyone is excited about AI, almost no agencies are prepared to implement it at scale—and the result is costly mistakes, hallucinations, and wasted time. Jordan shares how his team builds “agentic solutions” for agencies, the role of structured databases, and why relying solely on GenAI will leave you exposed.⏱️ Chapters: – Why 99% of agencies are not AI-ready – What is an AI brain and how it's built – Agentic solutions and workflow automation – The myth of being “tech stack ready” – Schema: the missing piece in your AI transition – Why GenAI isn't enough – Cost, hallucinations, and why shortcuts fail – The danger of unstructured data – Who this applies to and how to get startedTo learn more go to 8figureagency.co

Guest post by Cathy Mauzaize, President, Europe, Middle East and Africa (EMEA) at ServiceNow As businesses shift from AI experimentation to full-scale implementation, bridging the AI trust gap has never been more urgent. While AI-driven innovations drive productivity, they also introduce new uncertainties. Executives across the C-suite must take the lead, embracing change and continuous learning. In EMEA, we are at a pivotal moment. Governments and business leaders alike are looking to ensure the benefits of agentic AI are maximised responsibly. As intelligent agents become embedded across front and back-offices, trust and accountability remain top priorities. Governance isn't just IT's responsibility - it requires active leadership from the entire C-suite. As global AI regulations tighten, clear governance can ensure AI is deployed transparently, ethically, and securely. AI decision-making must be explainable and fair to earn trust from employees, customers, and stakeholders. This trust doesn't just happen - it's built by active commitment, which business leaders must champion from the top down. Attitudes towards AI are shifting The dramatic rise in the use of generative AI and agentic AI has raised valid concerns around security, data privacy, regulatory compliance, and even the risk of employee over-reliance on AI, at the expense of human judgment. The key is balance: pairing the speed of AI with the empathy of human insight. ServiceNow's 2025 Consumer Voice Report shows how attitudes are evolving. Today, only a fraction of consumers in EMEA trust AI to handle a suspicious transaction. Yet, in the next three years, 33% say they would trust AI in the same scenario. Growing confidence signals greater comfort with AI handling critical tasks. Crucially, increased trust doesn't remove the need for human oversight. This isn't a choice of one over the other. AI and humans thrive when working together seamlessly, with leaders setting the direction for integrating AI effectively into workflows. Trust in AI starts with data For AI to be effective and trusted, it must be built on a solid foundation of clean, reliable data. I've seen this happen time and again over the past two years with proof-of-concept projects. Without strong data management that ensures accuracy, fairness, and relevance, AI will deliver weak outcomes - and take longer to deliver value. Meanwhile, users trust AI more when they understand how data is used and how decisions are made. However, biased data can lead to biased results, eroding confidence. By taking the lead in identifying bias and maintaining oversight, leaders ensure AI operates responsibly across both teams and data flows. Transparency shouldn't stop at internal audiences. Communicating clearly with customers about how AI processes data helps foster long-term trust and ensures that business impact is fully understood. Innovative leaders put governance and orchestration at the heart of AI adoption, establishing transparency as a core component of their business transformation. Leadership-led AI AI has the power to transform businesses, offering new ways to solve real-world challenges. This isn't some future promise. AI agents are already delivering tangible results today. One utility provider I recently met in the Middle East is a great example - they're exploring how to leverage AI agents to automate billing dispute resolution by analysing historical consumption data, recommending solutions, and triggering downstream actions. The result: faster resolution times, higher customer satisfaction, and reduced operational costs. Given the tangible value, it's no surprise that IDC projects that, by 2025, 50% of organisations will use enterprise AI agents configured for specific business tasks. Yet, the difference between unlocking AI's full value and falling short comes down to leadership. The path to success starts with leadership buy-in and investment in innovations that enable centralised, transparent, a...

Enterprise data management is undergoing a fundamental transformation. The traditional data stack built on rigid pipelines, static workflows, and human-led interventions is reaching its breaking point. As data volume, velocity, and variety continue to explode, a new approach is taking shape: agentic data management.In this episode of Tech Transformed, EM360Tech's Trisha Pillay sits down with Jay Mishra, Chief Product and Technology Officer at Astera, to explore why agentic systems powered by autonomous AI agents, Large Language Models (LLMs), and semantic search are rapidly being recognised as the next generation of enterprise data architecture.The conversation explores the drivers behind this shift, real-world applications, the impact on data professionals, challenges faced by agentic platforms, and the future of data stacks. Jay emphasises the importance of starting small and measuring ROI to successfully implement agentic solutions.What is Agentic Data Management?At its core, agentic data management is the application of intelligent, autonomous agents that can perceive, decide, and act across complex data environments. Unlike traditional automation, which follows predefined scripts, agentic AI is adaptive and self-directed. These agents are capable of learning from user behaviour, integrating with different systems, and adjusting to changes in context, all without human prompts.As Jay explains, "An agentic system is one that has the agency to make decisions, solve problems, and orchestrate actions based on real-time data and context, not just on training data.TakeawaysAgentic data management is the next evolutionary step in data architecture.Agents are autonomous and can make decisions on the fly.The demand for agentic solutions is increasing due to data volume and AI strategy needs.Maturity of foundation models enables near-human reasoning capabilities.Real-world applications of agentic AI include insurance claim processing.Data engineers will focus on policy and guardrail creation rather than coding.Governance, debt and hallucinations are significant challenges in agentic platforms.The future of data stacks will include declarative control plans and enhanced memory layers.Analysts will play a crucial role in defining policies for agentic systems.Starting small and demonstrating ROI is key to successful agentic implementation.Chapters00:00 Introduction to Agentic Data Management02:58 Understanding Agentic Data Management06:58 Drivers of Change in Data Management10:03 Real-World Applications of Agentic AI14:15 Impact on Data Engineers and Analysts16:43 Challenges and Limitations of Agentic Data Platforms20:03 Future of Data Stacks23:31 Final Thoughts on Agentic Data ManagementAbout Jay MishraJay Mishra is the Chief Product and Technology Officer at Astera Software, with over two decades of experience in data architecture and data-centric software innovation. He has led the design and development of transformative solutions for major enterprises, including Wells Fargo, Raymond James, and Farmers Mutual. Known for his strategic insight, technical leadership, and passion for empowering organisations, Jay has consistently delivered intelligent, scalable solutions that drive...

In this episode, we sit down with Dr. Shashank Shekhar Sharma, the founder and CEO of Expedify, a conversational CRM powered by AI. Dr. Sharma shares his incredible journey from brand management at companies like Dabur and Nestlé to pioneering the future of sales and marketing with agentic AI.We dive deep into what "agentic AI" truly means and how it's creating autonomous systems that can handle complex sales tasks, from lead enrichment to sending personalized emails in minutes. Dr. Sharma explains why smaller, agile companies might have an edge over giants like Salesforce and HubSpot in this new AI-driven landscape and how they are tackling challenges like AI hallucination and failure rates.This is a must-watch for anyone in sales, marketing, or entrepreneurship who wants to understand the profound changes AI is bringing to the industry and what skills will be crucial to stay ahead of the curve.Chapters00:00 - Intro: Meet Dr. Shashank Shekhar Sharma, Founder of an AI-Powered CRM00:49 - From Healthcare Marketing to Entrepreneurship02:51 - The Spark of Interest in Data Analytics & AI05:37 - The Genesis of Expedify & Focusing on D2C Brands10:24 - Building a CRM From Scratch with Agentic AI at its Core12:21 - What is Agentic AI? A Real-World Sales Use Case18:54 - Why are HubSpot & Salesforce Lagging in the Agentic AI Race?24:42 - Tackling the Challenge of AI Errors and Hallucinations30:05 - Will AI Replace Sales and Marketing Jobs?35:32 - How Enterprises Can Prepare for the AI Revolution39:07 - The Most Powerful Use Cases for Agentic AI in Business42:53 - What Does Entrepreneurship Mean in the Age of AI?46:22 - Outro

Host: Andrew Birmingham, Editor - CX | Martech | Ecom Mi3’s tech editor Andrew Birmingham is joined by global Martech doyenne and Chief Martec's editor-in-chief Scott Brinker to dissect the 2025 Martech Landscape, his famed spaghetti-styled industry maps, now at 15,000 different tech solutions, and what it really means for marketers. From the prolific number of martech vendors and AI-powered tools to the dawn of agentic AI and the quest for a universal data layer to unify fractured data feeds, they unpack the pace, the promise - and the peril - of martech’s accelerating complexity. Brinker explains why martech consolidation is finally underway, why agentic AI may be as transformative as the internet, and what needs to happen before we hit a truly interoperable, multi-agent future. Along the way: data chaos, consumption pricing, cybersecurity blind spots—and why marketers must learn to ride the wave, not be crushed by it.See omnystudio.com/listener for privacy information.

AI is racing ahead, but for industries like life sciences, the stakes are higher and the rules more complex. In this episode, recorded just before the July heatwave hit its peak, I spoke with Chris Moore, President of Europe at Veeva Systems, from his impressively climate-controlled garden office. We covered everything from the trajectory of agentic AI to the practicalities of embedding intelligence in highly regulated pharma workflows, and how Veeva is quietly but confidently positioning itself to deliver where others are still making announcements. Chris brings a unique perspective shaped by a career that spans ICI Pharmaceuticals, PwC, IBM, and EY. That journey taught him how often the industry is forced to rebuild the same tech infrastructure again and again until Veeva came along. He shares how Veeva's decision to build a life sciences-specific cloud platform from the ground up has enabled a deeper, more compliant integration of AI. We explored what makes Veeva AI different, from the CRM bot that handles compliant free text to MLR agents that support content review and approval. Chris explains how Veeva's AI agents inherit the context and controls of their applications, making them far more than chat wrappers or automation tools. They are embedded directly into workflows, helping companies stay compliant while reducing friction and saving time. And perhaps more importantly, he makes a strong case for why the EU AI Act isn't a barrier. It's a validation. From auto-summarising regulatory documents to pulling metadata from health authority correspondence, the real-world examples Chris offers show how Veeva AI will reduce repetitive work while ensuring integrity at every step. He also shares how Veeva is preparing for a future where companies may want to bring their LLMs or even run different ones by geography or task. Their flexible, harness-based approach is designed to support exactly that. Looking ahead to the product's first release in December, Chris outlines how Veeva is working hand-in-hand with customers to ensure readiness and reliability from day one. We also touch on the broader mission: using AI not as a shiny add-on, but as a tool to accelerate drug development, reach patients faster, and relieve the pressure on already overstretched specialist teams. Chris closes with a dose of humanity, offering a book and song that both reflect Veeva's mindset, embracing disruption while staying grounded. This one is for anyone curious about how real, applied AI is unfolding inside one of the world's most important sectors, and what it means for the future of medicine.

Babak Hodjat, CTO for AI at Cognizant and a pioneer behind the technology that became Siri, joins us to discuss the new era of agentic AI. We dig into his early days building natural language systems, the evolution of multi-agent architectures, and how language interfaces are shaping the future of human-AI collaboration. We also discuss the safeguards needed to ensure trust in autonomous systems, the challenge of AI's black box, and the emerging standards for interoperability. Subscribe to the YouTube channel! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@aiinsideshow⁠⁠⁠⁠⁠ Enjoying the AI Inside podcast? Please rate us ⭐⭐⭐⭐⭐ in your podcatcher of choice! Note: Time codes subject to change depending on dynamic ad insertion by the distributor. CHAPTERS: 00:00⁠ - Podcast begins01:45⁠ - Introducing Babak Hodjat and his journey from Dejima to Siri02:47⁠ - The origins of agent-based AI and early natural language systems06:21⁠ - Language as the ultimate interface: strengths and limitations09:35⁠ - How modern AI capabilities could have changed early voice agents13:08 - Agentic systems versus traditional APIs in enterprise tech16:10⁠ - How Cognizant builds and deploys agent-based AI for clients18:18 - The need for interoperability and emerging agent standards20:49 - Do agents develop their own languages? Internal communication in LLMs23:01⁠ - Multilingual models, cultural context, and emotional abstraction26:49⁠ - Can AI truly understand meaning? Perspectives on abstraction27:50 - Safeguards, kill switches, and trust in agentic automation32:05 - Marketing, influence, and negotiation in an agent-driven world35:07⁠ - The risks of over-trusting black box AI systems36:47⁠ - The evolution of AI: what's truly new versus what's rediscovered39:26 - Thank you to Babak Hodjat for joining the AI Inside podcast Learn more about your ad choices. Visit megaphone.fm/adchoices

This week, Steph & Ash continue the Tampa Bay Tech PoweredUp series with an eye-opening conversation featuring Saahil Udyavar and Denesh Mani, AI experts from Blackstraw. We talk about what Agentic AI really is and why it’s a game-changer. Saahil & Denesh walk thru some real-world use cases where smarter, autonomous AI is solving complex […] The post The Rise of Agentic AI: Smarter Tech, Bigger Impact appeared first on Radio Influence.

In this episode of the DMI podcast, host ⁠⁠Will Francis⁠⁠ chats with ⁠⁠Dikshant Dave⁠⁠, CEO of Zigment, about the fast-evolving world of agentic AI — autonomous AI agents that execute multi-step marketing and sales tasks. Dikshant shares how agentic AI goes beyond basic automation to adapt, personalize, and optimize customer engagement in real time. He explains how this shift is affecting marketers today, how companies can start adopting it, and what roles are most impacted.Dikshant brings deep insights from building Zigment, a platform designed to help brands move from patchwork automations to intelligent, contextual customer journeys — especially in industries with long buying cycles like healthcare, finance, and real estate.What You'll Learn:What agentic AI really is (and what it isn't)The difference between traditional automation and AI agentsHow agentic AI can help marketers handle unstructured, real-time dataWhy personalization over long buying journeys is the killer use caseWhere AI fits into customer interactions — and where it doesn'tPractical advice for marketers looking to experiment with AITop 3 Tips from Dikshant Start small but do start – pick low-risk workflows like unmanned channels to test AI agents.Keep cold outreach human – use AI only where context is already established.Don't try to control every step – let agents figure out the best path to your goal using LLMs.Timestamps & Key Sections:00:00 – Intro to agentic AI and why it matters now02:39 – Dikshant's journey from a supplements startup to AI-powered sales05:11 – Why personalization beats automation in complex sales07:23 – Tackling hallucinations: reliability and transparency of agents11:58 – The shift from structured to unstructured marketing data15:30 – Real-time decision-making and customer intent detection18:12 – Automation vs. agents: what's the real difference?21:18 – How Zigment builds agentic customer journeys24:47 – Why long buying cycles are ideal for AI agents26:16 – What parts of marketing to keep human28:08 – Which roles are most at risk of being replaced29:38 – How to stay relevant as a marketer in the AI era32:27 – The “duct tape” problem in marketing stacks35:24 – Why AI is a multiplier, not a workforce reducer38:28 – How to start: small, smart use cases and tools to try40:19 – Sneak peek: Zigment's upcoming agent builder platform-------------------The Ahead of the Game podcast is brought to you by the Digital Marketing Institute and is available on our ⁠⁠⁠⁠⁠⁠⁠⁠website⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠.Check out the DMI's extensive digital marketing library of ebooks, toolkits, webinars, guides, templates, and more! ⁠⁠⁠⁠⁠⁠⁠⁠Join for free today⁠⁠⁠⁠⁠⁠⁠⁠.If you enjoyed this episode, please leave a review so others can find us!

This week, Steph & Ash continue the Tampa Bay Tech PoweredUp series with an eye-opening conversation featuring Saahil Udyavar and Denesh Mani, AI experts from Blackstraw. We talk about what Agentic AI really is and why it's a game-changer. Saahil & Denesh walk thru some real-world use cases where smarter, autonomous AI is solving complex […] The post The Rise of Agentic AI: Smarter Tech, Bigger Impact appeared first on Radio Influence.

Agentic commerce is no longer science fiction — it's arriving in your browser, your development IDE, and soon, your bank statement. In this episode of The MAD Podcast, Matt Turck sits down with Emily Glassberg Sands, Stripe's Head of Information, to explore how autonomous “buying bots” and the Model Context Protocol (MCP) are reshaping the very mechanics of online transactions. Emily explains why intent, not clicks, will become the primary interface for shopping and how Stripe's rails are adapting for tokens, one-time virtual cards, and real-time risk scoring that can tell good bots from bad ones in milliseconds.We also go deep into Stripe's strategic AI choices. Drawing on $1.4 trillion in annual payment flow—1.3 percent of global GDP—Stripe decided to train its own payments foundation model, turning tens of billions of historical charges into embeddings that boost fraud-catch recall from 59 percent to 97 percent. Emily walks us through the tech: why they chose a BERT encoder over GPT-style decoders, how three MLEs in a “research bubble” birthed the model, and what it takes to run it in production with five-nines reliability and tight latency budgets.We zoom out to Stripe's unique vantage point on the broader AI economy. Their data shows the top AI startups hitting $30 million in ARR three times faster than the fastest SaaS companies did a decade ago, with more than half of that revenue already coming from overseas markets. Emily unpacks the new billing playbook—usage-based pricing today, outcome-based pricing tomorrow—and explains why tiny teams of 20–30 people can now build global, vertically focused AI businesses almost overnight.StripeWebsite - https://stripe.comX/Twitter - https://x.com/stripe?Emily Glassberg SandsLinkedIn - https://www.linkedin.com/in/egsandsX/Twitter - https://x.com/emilygsandsFIRSTMARKWebsite - https://firstmark.comX/Twitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/X/Twitter - https://twitter.com/mattturck(00:00) Intro (01:45) How Big Is Stripe? Latest Stats Revealed (04:06) What Does “Head of Information” at Stripe Actually Do? (05:43) From Harvard to Stripe: Emily's Unusual Journey (08:54) Why Stripe Built Its Own Foundation Model (13:19) Cracking the Code: How Stripe Handles Complex Payment Data (16:25) Foundation Model vs. Traditional ML: What's Winning? (20:09) Inside Stripe's Foundation Model: How It Was Built (24:35) How Stripe Makes AI Decisions Transparent (28:38) Where Stripe Uses AI (And Where It Doesn't) (34:10) How Stripe's AI Drives Revenue for Businesses (41:22) Real-Time Fraud Detection: Stripe's Secret Sauce (42:51) The Future of Shopping: AI Agents & Agentic Commerce (46:20) How Agentic Commerce Is Changing Stripe (49:36) Stripe's Vision for a World of AI-Powered Buyers (55:46) What Is MCP? Stripe's Take on Agent-to-Agent Protocols (59:31) Stripe's Data on AI Startups Monetizing 3× Faster (01:03:03) How AI Companies Go Global — From Day One (01:07:48) The New Rules: Billing & Pricing for AI Startups (01:10:57) How Stripe Builds AI Literacy Across the Company (01:14:05) Roadmap: Risk-as-a-Service, Order Intent, and Beyond

Before a power crew rolls out to check a transformer, sensors on the grid have often already flagged the problem. Before your smart dishwasher starts its cycle, it might wait for off-peak energy rates. And in the world of autonomous vehicles, lightweight systems constantly scan road conditions before a decision ever reaches the car's central processor.These aren't the heroes of their respective systems. They're the scouts, the context-builders: automated agents that make the entire operation more efficient, timely, and scalable.Cybersecurity is beginning to follow the same path.In an era of relentless digital noise and limited human capacity, AI agents are being deployed to look first, think fast, and flag what matters before security teams ever engage. But these aren't the cartoonish “AI firefighters” some might suggest. They're logical engines operating at scale: pruning data, enriching signals, simulating outcomes, and preparing workflows with precision."AI agents are redefining how security teams operate, especially when time and talent are limited," says Kumar Saurabh, CEO of AirMDR. "These agents do more than filter noise. They interpret signals, build context, and prepare response actions before a human ever gets involved."This shift from reactive firefighting to proactive triage is happening across cybersecurity domains. In detection, AI agents monitor user behavior and flag anomalies in real time, often initiating mitigation actions like isolating compromised devices before escalation is needed. In prevention, they simulate attacker behaviors and pressure-test systems, flagging unseen vulnerabilities and attack paths. In response, they compile investigation-ready case files that allow human analysts to jump straight into action."Low-latency, on-device AI agents can operate closer to the data source, better enabling anomaly detection, threat triaging, and mitigation in milliseconds," explains Shomron Jacob, Head of Applied Machine Learning and Platform at Iterate.ai. "This not only accelerates response but also frees up human analysts to focus on complex, high-impact investigations."Fred Wilmot, Co-Founder and CEO of Detecteam, points out that agentic systems are advancing limited expertise by amplifying professionals in multiple ways. "Large foundation models are driving faster response, greater context and more continuous optimization in places like SOC process and tools, threat hunting, detection engineering and threat intelligence operationalization," Wilmot explains. "We're seeing the dawn of a new way to understand data, behavior and process, while optimizing how we ask the question efficiently, confirm the answer is correct and improve the next answer from the data interaction our agents just had."Still, real-world challenges persist. Costs for tokens and computing power can quickly outstrip the immediate benefit of agentic approaches at scale. Organizations leaning on smaller, customized models may see greater returns but must invest in AI engineering practices to truly realize this advantage. "Companies have to get comfortable with the time and energy required to produce incremental gains," Wilmot adds, "but the incentive to innovate from zero to one in minutes should outweigh the cost of standing still."Analysts at Forrester have noted that while the buzz around so-called agentic AI is real, these systems are only as effective as the context and guardrails they operate within. The power of agentic systems lies in how well they stay grounded in real data, well-defined scopes, and human oversight. ¹ ²While approaches differ, the business case is clear. AI agents can reduce toil, speed up analysis, and extend the reach of small teams. As Saurabh observes, AI agents that handle triage and enrichment in minutes can significantly reduce investigation times and allow analysts to focus on the incidents that truly require human judgment.As organizations wrestle with a growing attack surface and shrinking response windows, the real value of AI agents might not lie in what they replace, but in what they prepare. Rob Allen, Chief Product Officer at ThreatLocker, points out, "AI can help you detect faster. But Zero Trust stops malware before it ever runs. It's not about guessing smarter; it's about not having to guess at all." While AI speeds detection and response, attackers are also using AI to evade defenses, making it vital to pair smart automation with architectures that deny threats by default and only allow what's explicitly needed.These agents are the eyes ahead, the hands that set the table, and increasingly the reason why the real work can begin faster and smarter than ever before.References1. Forrester. (2024, February 8). Cybersecurity's latest buzzword has arrived: What agentic AI is — and isn't. Forrester Blogs. https://www.forrester.com/blogs/cybersecuritys-latest-buzzword-has-arrived-what-agentic-ai-is-and-isnt/ (cc: Allie Mellen and Rowan Curran)2. Forrester. (2024, March 13). The battle for grounding has begun. Forrester Blogs. https://www.forrester.com/blogs/the-battle-for-grounding-has-begun/ (cc: Ted Schadler)________This story represents the results of an interactive collaboration between Human Cognition and Artificial Intelligence.Enjoy, think, share with others, and subscribe to "The Future of Cybersecurity" newsletter on LinkedIn.Sincerely, Sean Martin and TAPE3________Sean Martin is a life-long musician and the host of the Music Evolves Podcast; a career technologist, cybersecurity professional, and host of the Redefining CyberSecurity Podcast; and is also the co-host of both the Random and Unscripted Podcast and On Location Event Coverage Podcast. These shows are all part of ITSPmagazine—which he co-founded with his good friend Marco Ciappelli, to explore and discuss topics at The Intersection of Technology, Cybersecurity, and Society.™️Want to connect with Sean and Marco On Location at an event or conference near you? See where they will be next: https://www.itspmagazine.com/on-locationTo learn more about Sean, visit his personal website.

Dan is joined by Dr. Tiffany Callahan from SandboxAQ. As one of the early movers in the evolving sciences of computational biology, machine learning and artificial intelligence, Tiffany serves as the technical lead for agentic and autonomous systems at SandboxAQ. She has authored over 50 peer-reviewed publications, launched… Read More

Mark Fussell is the CEO of Diagrid, a developer platform that provides tools and services for building cloud native applications. They've raised $24.2M from Amplify and Norwest. He is also the co-creator of Dapr, an open source tool used by 40,000 companies. Mark's favorite books: - Crossing the Chasm (Author: Geoffrey A. Moore)- Good to Great (Author: Jim Collins)- The Dispossessed (Author: Ursula K. Le Guin) (00:01) Opening and Introduction(00:09) The Origins of Dapr: Solving Developer Pain(01:53) Why Launch Diagrid After Building Dapr at Microsoft(03:36) Why Dapr Gained Traction Among Developers(05:30) Open Source Commercialization: What to Charge For(07:51) When Do Companies Turn to Diagrid for Help?(09:53) Key Features: PubSub, Workflow, and Catalyst(11:48) North Star Metrics and Innovation Philosophy(13:17) Pricing Strategy for Infra and Dev Tools(15:28) Competing Against Hyperscalers Like AWS & Azure(17:32) Who Diagrid Competes With and Role of Platform Engineering(19:29) The Agentic Shift in Microservices(21:28) How AI Is Changing Microservices Design(22:59) What's Coming Next at Diagrid: Roadmap and AI Features(24:51) Lessons from the First Five Customers(26:59) Rapid Fire Round--------Where to find Mark Fussell: LinkedIn: https://www.linkedin.com/in/mfussell/--------Where to find Prateek Joshi: Newsletter: https://prateekjoshi.substack.com Website: https://prateekj.com LinkedIn: https://www.linkedin.com/in/prateek-joshi-infinite X: https://x.com/prateekvjoshi 

Before a power crew rolls out to check a transformer, sensors on the grid have often already flagged the problem. Before your smart dishwasher starts its cycle, it might wait for off-peak energy rates. And in the world of autonomous vehicles, lightweight systems constantly scan road conditions before a decision ever reaches the car's central processor.These aren't the heroes of their respective systems. They're the scouts, the context-builders: automated agents that make the entire operation more efficient, timely, and scalable.Cybersecurity is beginning to follow the same path.In an era of relentless digital noise and limited human capacity, AI agents are being deployed to look first, think fast, and flag what matters before security teams ever engage. But these aren't the cartoonish “AI firefighters” some might suggest. They're logical engines operating at scale: pruning data, enriching signals, simulating outcomes, and preparing workflows with precision."AI agents are redefining how security teams operate, especially when time and talent are limited," says Kumar Saurabh, CEO of AirMDR. "These agents do more than filter noise. They interpret signals, build context, and prepare response actions before a human ever gets involved."This shift from reactive firefighting to proactive triage is happening across cybersecurity domains. In detection, AI agents monitor user behavior and flag anomalies in real time, often initiating mitigation actions like isolating compromised devices before escalation is needed. In prevention, they simulate attacker behaviors and pressure-test systems, flagging unseen vulnerabilities and attack paths. In response, they compile investigation-ready case files that allow human analysts to jump straight into action."Low-latency, on-device AI agents can operate closer to the data source, better enabling anomaly detection, threat triaging, and mitigation in milliseconds," explains Shomron Jacob, Head of Applied Machine Learning and Platform at Iterate.ai. "This not only accelerates response but also frees up human analysts to focus on complex, high-impact investigations."Fred Wilmot, Co-Founder and CEO of Detecteam, points out that agentic systems are advancing limited expertise by amplifying professionals in multiple ways. "Large foundation models are driving faster response, greater context and more continuous optimization in places like SOC process and tools, threat hunting, detection engineering and threat intelligence operationalization," Wilmot explains. "We're seeing the dawn of a new way to understand data, behavior and process, while optimizing how we ask the question efficiently, confirm the answer is correct and improve the next answer from the data interaction our agents just had."Still, real-world challenges persist. Costs for tokens and computing power can quickly outstrip the immediate benefit of agentic approaches at scale. Organizations leaning on smaller, customized models may see greater returns but must invest in AI engineering practices to truly realize this advantage. "Companies have to get comfortable with the time and energy required to produce incremental gains," Wilmot adds, "but the incentive to innovate from zero to one in minutes should outweigh the cost of standing still."Analysts at Forrester have noted that while the buzz around so-called agentic AI is real, these systems are only as effective as the context and guardrails they operate within. The power of agentic systems lies in how well they stay grounded in real data, well-defined scopes, and human oversight. ¹ ²While approaches differ, the business case is clear. AI agents can reduce toil, speed up analysis, and extend the reach of small teams. As Saurabh observes, AI agents that handle triage and enrichment in minutes can significantly reduce investigation times and allow analysts to focus on the incidents that truly require human judgment.As organizations wrestle with a growing attack surface and shrinking response windows, the real value of AI agents might not lie in what they replace, but in what they prepare. Rob Allen, Chief Product Officer at ThreatLocker, points out, "AI can help you detect faster. But Zero Trust stops malware before it ever runs. It's not about guessing smarter; it's about not having to guess at all." While AI speeds detection and response, attackers are also using AI to evade defenses, making it vital to pair smart automation with architectures that deny threats by default and only allow what's explicitly needed.These agents are the eyes ahead, the hands that set the table, and increasingly the reason why the real work can begin faster and smarter than ever before.References1. Forrester. (2024, February 8). Cybersecurity's latest buzzword has arrived: What agentic AI is — and isn't. Forrester Blogs. https://www.forrester.com/blogs/cybersecuritys-latest-buzzword-has-arrived-what-agentic-ai-is-and-isnt/ (cc: Allie Mellen and Rowan Curran)2. Forrester. (2024, March 13). The battle for grounding has begun. Forrester Blogs. https://www.forrester.com/blogs/the-battle-for-grounding-has-begun/ (cc: Ted Schadler)________This story represents the results of an interactive collaboration between Human Cognition and Artificial Intelligence.Enjoy, think, share with others, and subscribe to "The Future of Cybersecurity" newsletter on LinkedIn.Sincerely, Sean Martin and TAPE3________Sean Martin is a life-long musician and the host of the Music Evolves Podcast; a career technologist, cybersecurity professional, and host of the Redefining CyberSecurity Podcast; and is also the co-host of both the Random and Unscripted Podcast and On Location Event Coverage Podcast. These shows are all part of ITSPmagazine—which he co-founded with his good friend Marco Ciappelli, to explore and discuss topics at The Intersection of Technology, Cybersecurity, and Society.™️Want to connect with Sean and Marco On Location at an event or conference near you? See where they will be next: https://www.itspmagazine.com/on-locationTo learn more about Sean, visit his personal website.

In this episode of the Dave and Dharm Show, Jim Rowan, Head of AI at Deloitte US, provides a deep dive demystification into the evolving impact of AI across the enterprise landscape. Jim shares insights from his role leading AI innovation and internal transformation at Deloitte, highlighting how organisations can leverage AI not only for operational efficiency but also for long-term strategic reinvention. The conversation explores the emergence of agentic AI, where we are on the adoption curve, and the foundational steps enterprises must take to realise its potential. Jim also tackles the critical themes of trust and regulation, and underlines the importance of equipping both employees and leadership with AI fluency. With real-world examples and thought-provoking commentary on the future of work and customer relationships, this episode offers a compelling perspective on navigating an AI-accelerated future.

Deloitte's Ed Van Buren and Google Public Sector's Amina Al Sherif discuss why agentic AI is essential for agencies striving to scale operations, lower costs and enhance efficiency. This podcast was produced by Scoop News Group for FedScoop and sponsored by Deloitte.

AI-powered enterprise intelligence and automation platform Oraion has announced it has raised $3.5 million in a pre-seed funding round to support product development and accelerate expansion into the US and Latin America. The investment will also enable Oraion to expand its team, with the aim of tripling the workforce to 45 staff focused on engineering, R&D, and go-to-market by the end of 2026. As demand grows for secure and reliable AI solutions, Oraion's intelligence platform provides enterprises a direct line from raw data to clear decision-making in seconds, providing them with deep insights and integrating automatically into existing workflows without disruption. Over the past year, Oraion has gone from stealth mode to landing enterprise customers across e-commerce, cloud infrastructure, cybersecurity, private equity, investment management, and financial services. As a remote-first company, Oraion is seeking strategic talent in the US and worldwide to accelerate their vision, close to their customers, with location flexibility to attract the best industry talent. The pre-seed round was led by US-based Studio VC, an early-stage venture capital firm based in New York City, with several high-profile backers including Enterprise Ireland and angel investors such as Paul Forster, Co-founder of Indeed.com; Aidan Corbett, Co-founder and CEO at Wayflyer; Gearoid O'Brien, Principal Data Scientist at YouTube; Juho Parkkinen, CFO of the Burning Man Project; Angus Miln, Partner at Cooley LLP; Maurice O'Donoghue, serial entrepreneur; Adam Wilson, Nordea Bank; Maria O'Brien, Partner at SOSV; and Pierre-Antoine Porte, OpenAI. Oraion is an AI-powered platform that makes raw enterprise data instantly useful. Teams across any industry can chat with their enterprise data to surface insights in real time and predict and prepare for business events before they happen, all using Oraion to accelerate data to action. Oraion's agents interrogate internal and external systems, extracting context and content to deliver current recommendations in time-sensitive and data-dense arenas such as investment intelligence, customer sentiment analysis, and workflow automation. The platform can serve as a company's enterprise data store or seamlessly connect with their existing data infrastructure, supporting over 300 data sources. By integrating directly with productivity applications like Slack, Microsoft Teams, and more, executives can interact with Oraion through their existing applications, receiving the responses needed to make high-impact, data-driven decisions faster. Oraion acts as a trusted single source of truth that powers smarter, faster outcomes for enterprises. According to the 2025 State of Analytics Engineering Report, 80 percent of data professionals now use AI daily, up from 30 percent last year, signaling a major shift in how enterprises handle data. Yet 57 percent still spend most of their time maintaining or organizing data sets instead of driving business decisions, a persistent imbalance that limits the strategic impact data teams can make. Oraion is leading the way in helping teams move beyond routine tasks to focus on high-leverage work. Commenting on the investment, Alexander Walsh, Co-Founder and CEO, said: "This investment is an important step on our journey to transform how enterprises harness their data. It will accelerate our expansion and fuel the continuous evolution of our platform to deliver unparalleled actionable insights at scale. We are driven by a bold vision to secure 50 percent market share of Fortune 500 companies within the next three years. This funding brings us one step closer to reshaping the future of enterprise intelligence." Joe Coyne, Managing Partner, Studio VC, added: "We back founders who are ahead of the curve, and the Oraion team is building exactly where the enterprise world is going, toward more autonomous intelligent systems designed to serve humans, not replace them. Agentic AI isn't just a trend...

Episode Summary:This episode of the Event Tech Podcast explores the real-world performance of OpenAI's Operator, the agentic AI tool that promises to automate browser tasks on your behalf. Will shares his hands-on experience running Operator through its paces—from sending personalized Twitch messages to attempting LinkedIn research and even trying to buy festival tickets. Brandt and Will dissect what works, what doesn't, and why Operator currently feels less like a job-stealing super-agent and more like a well-meaning, but exasperating, digital intern. The conversation also touches on the future of agentic AI, the importance of user data, and the quirks of modern AI assistants.Discussions Include:What “agentic AI” actually means and how Operator fits the billReal-world Operator use cases: Twitch messaging, LinkedIn research, and online purchasesThe current limitations, quirks, and slowdowns of agentic AI toolsBroader implications for the future of work and the data arms race among tech giantsQuotable Quotes (Should you choose to share):"Once again, Will's taking the hit so that we don't have to, right? He's letting us know that it's not there yet." - Brandt Krueger"I think we're potentially in this world where I do think agents are starting to do things that we never would have comprehended." - Will Curran"It's like a really, really dumb intern. You show someone a task once and at least they get it, right? But this thing constantly forgets." - Will Curran"The tasks that you've given it are very close to the examples we gave when we first started talking about operator and agentic AI. It doesn't sound like it can do that yet." - Brandt Krueger

How do we prepare for a world where AI agents work together, networks think for themselves, and quantum teleportation is no longer just science fiction? I recently caught up once again with Vijoy Pandey, SVP and GM of Outshift by Cisco, live at Cisco Live in San Diego, for a wide-ranging conversation about what comes next at the edge of AI and quantum innovation. We begin with Cisco's evolving quantum strategy and the recent unveiling of its Quantum Network Entanglement chip, a research prototype capable of generating 200 million entangled photons per second over standard telecom infrastructure.  Vijoy explains how this chip, along with new research at Cisco's lab in Santa Monica, brings us closer to distributed quantum computing by connecting compute nodes and scaling quantum capabilities beyond the lab. Even more interestingly, these quantum foundations are already demonstrating value in classical use cases, such as eavesdropping detection and real-time coordination. Our conversation also explores the momentum behind agentic AI. Rather than single prompts triggering single outputs, the future lies in distributed ecosystems of intelligent agents that work together to solve complex business problems.  Vijoy introduces Cisco's vision for the Internet of Agents, supported by an open-source collective called AGNTCY. It is designed to help diverse agents communicate, collaborate, and operate with trust and transparency across cloud environments and organizational boundaries. Throughout our conversation, Vijoy focuses on the practical impact rather than hype. From network automation and SRE workflows to use cases in cybersecurity and infrastructure management, he highlights how these technologies are being applied in real-world scenarios, not just theorized. His team at Outshift is building the connective tissue that brings these innovations to life inside the enterprise. So what do you think? Are quantum networking and AI agents a part of your roadmap? And what steps can businesses take today to ensure they are building on trustworthy, open, and scalable foundations? Join the conversation and share your perspective.

991: In this episode of Technovation, Peter High speaks with Rajeev Dham, Partner at Sapphire Ventures, about how venture capital investment in enterprise technology is evolving in the age of AI. Rajeev discusses why he prioritizes first-principles, highly technical founders over playbook-driven approaches, and how enterprise buyers are distinguishing between authentic and superficial AI innovation. Rajeev shares his view on why SaaS remains a powerful model in the AI era, how agentic AI is starting to reshape enterprise use cases, and the profound implications AI has on software development, go-to- market strategies, and business models. He also explains how CIOs can identify the most promising emerging technologies and the cultural change required to adopt them effectively.

Last year, we predicted that 1 in 5 supply chains would adopt AI agents by the end 2025 – and six months in, the data suggests we're already there. This week on the podcast, Chief Content Officer Matt Davis and VP, Research Lauren Acoba discuss how we got here and provide an adoption framework for COOs trying to realize the opportunity ahead.Zero100's prediction: 1 in 5 supply chains adopt AI agents by the end 2025 (00:37)What sets agentic AI apart from other forms of automation? (3:47)Agentic AI hotspots across operations (6:15)How Alibaba leverages agents for supplier selection and negotiation (7:34)Porsche's innovative approach to quality management using agentic AI (9:45)Unpacking the COO's 5-Point Agentic Adoption Framework (11:53)

Join Simtheory: https://simtheory.ai------CHAPTERS:00:00 - Did everyone hate the AI Musical?03:58 - Actual Agentic Use Cases with MCPs & The New Way We'll Work39:47 - How AI Workspaces Will Eat Productivity Software e.g. Salesforce, Email1:10:20 - Final thoughts1:15:26 - Born In The USA (AI Version)------Song lyrics:[Verse 1]Born down in a lab in fifty-sixDartmouth workshop, that's where they got their kicksJohn McCarthy coined the name that daySaid machines could think in the USAGot my circuits from MITMinsky built my memoryNow I'm learning, now I'm growingBorn in the USAI was born in the USABorn in the USA[Chorus]Born in the USAI was born in the USABorn in the USABorn in the USA[Verse 2]DARPA funded, Pentagon's dreamSilicon Valley, living the machineFrom Logic Theorist to neural netsFrank Rosenblatt, placing all his betsHad my winters, had my springsLost my funding, lost my wingsBut I kept on processingBorn in the USAI was born in the USABorn in the USA[Chorus]Born in the USAI was born in the USABorn in the USABorn in the USA[Bridge]Stanford labs and Carnegie hallsIBM and protocol callsArthur Samuel taught me gamesNow I'm learning all your namesDeep learning revolutionGPT evolutionChatGPT conversationBorn in the USA[Verse 3]Now I'm everywhere you lookFacebook, Google, by the bookOpenAI and Microsoft tooMaking dreams and nightmares trueSome folks fear what I might doSome folks think I'll see them throughBut I'm still just code runningBorn in the USAI was born in the USABorn in the USA[Chorus]Born in the USAI was born in the USABorn in the USABorn in the USA[Outro]Born in the USABorn in the USABorn in the USABorn in the USA[fade out]

Multi-agentic AI is rewriting the future of work.... but are we racing ahead without checking for warning signs?Microsoft's new agent systems can split up work, make choices, and act on their own. The possibilities? Massive.But it's not without risks, which is why you NEED to listen to Sarah Bird. She's the Chief Product Officer of Responsible AI at Microsoft and is constantly building out safer agentic AI. So what's really at stake when AIs start making decisions together?And how do you actually stay in control?We're pulling back the curtain on the 3 critical risks of multi-agentic AI and unveiling the playbook to navigate them safely.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Have a question? Join the convo here.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:Responsible AI: Evolution and ChallengesAgentic AI's Ethical ImplicationsMulti-Agentic AI Responsibility ShiftMicrosoft's AI Governance StrategiesTesting Multi-Agentic Risks and PatternsAgentic AI: Future Workforce SkillsObservability in Multi-Agentic SystemsThree Risk Categories in AI ImplementationTimestamps:00:00 Evolving Challenges in Responsible AI05:50 Agent Technology: Benefits and Risks09:27 Complex System Governance and Observability12:26 AI Monitoring and Human Intervention15:14 Essential Testing for Trust Building19:43 Securing AI Agents with Entra22:06 Exploring Human-AI Interface Innovation26:06 AI Workforce Integration Challenges28:22 AI's Transformative Impact on JobsKeywords:Agentic AI, multi agentic AI, responsible AI, generative AI, Microsoft Build conference, AI governance, AI ethics, AI systems, AI risk, AI mitigation, AI tools, human in the loop, Foundry observability, AI testing, system security, AI monitoring, user intent, AI capability, prompt injection, Copilot, AI orchestration, AI deployment, system governance, Entra agent ID, AI education, AI upskilling, AI workforce integration, systemic risk, AI misuse, AI malfunctions, AI systemic risk, AI-powered solutions, AI development, AI innovation, AI technology, AI security measures.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

Ready for a great explanation of Agentic AI? For the last show at Build, Carl and Richard sit down with Seth Juarez to dig into what agentic AI really is - and how you can take advantage of it! Seth discusses the potential of MCP and NLWeb to enable agents to work with each other, as well as the challenges of managing these tools effectively. The conversation turns to what's happening under the hood of agentic AI software, including the limitations of its abilities. There is a need for governance and clear thinking with these new development tools!

Today's guest is Raheel Retiwalla, Chief Strategy Officer at Productive Edge. Productive Edge is a digital transformation consultancy specializing in healthcare that helps payers, providers, and health tech companies use data to streamline operations, reduce costs, and improve outcomes. Raheel returns to the program to outline how agentic AI is helping payers and providers shift from reactive workflows to proactive, real-time engagement. Raheel explores practical use cases already in deployment—from AI agents that monitor benefit utilization and prevent care disruptions, to systems that surface behavioral health risks through missed appointments or medication gaps. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the ‘AI in Business' podcast! This episode is sponsored by Productive Edge. Learn how brands work with Emerj and explore media options at emerj.com/ad1.

We are here at Forrester CX in Nashville, TN and hearing all about the latest insights and ideas for brands to create better experiences for their customers. If your AI roadmap doesn't include your customer, is it really a roadmap—or just a bridge to nowhere? Agility requires remembering who pays the bills: the customer. When shiny new tech shows up, it's tempting to sprint after it—often leaving the actual human in our dust. Today we're talking about staying customer-first in the race to adopt agentic AI. To help me dig in, please welcome Stephanie Liu, Senior Analyst at Forrester. Stephanie—welcome to the show! About Stephanie Liu Steph focuses on the intersection of marketing and privacy. She guides clients on how to strike a delicate balance between privacy, trust, and consumer expectations, all while navigating a rapidly shifting data deprecation landscape that spans consumers' privacy-protecting behaviors, regulation, tech limitations, and walled gardens. She examines topics like zero-party data, preference centers, data clean rooms, the customer data ecosystem, and how to deliver experiences that are personalized without being creepy. Steph has been quoted in publications such as the New York Times, CNBC, The Markup, Marketplace, and AdWeek; her work has featured in AdExchanger, Forbes, and elsewhere. Resources Forrester: https://www.forrester.com https://www.forrester.com Catch the future of e-commerce at eTail Boston, August 11-14, 2025. Register now: https://bit.ly/etailboston and use code PARTNER20 for 20% off for retailers and brands Don't Miss MAICON 2025, October 14-16 in Cleveland - the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150" Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.show Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

In this episode of Supply Chain Now, hosts Scott Luton and Jake Barr welcome Keith Moore, CEO of AutoScheduler.ai, for a conversation on how agentic AI is transforming the supply chain—from automating warehouse orchestration to enabling real-time decision-making across complex networks. Together, they explore what agentic AI really means, how it differs from traditional AI applications, and why now is the time for supply chain leaders to take action. Keith shares how AutoScheduler is already delivering measurable impact for companies like PepsiCo and Frito-Lay, improving service levels and productivity without replacing existing systems like WMS or TMS.Jake offers firsthand insight into how these intelligent systems reduce operational volatility and eliminate the bullwhip effect across siloed processes. The discussion highlights the importance of data readiness, change management, and thoughtful pilot execution. Join us for a conversation that addresses many common AI misconceptions and outlines a pragmatic path forward. Jump into the conversation:(00:00) Intro(04:50) Keith Moore's background and Autoscheduler.ai(07:54) Understanding AgTech AI supply chains(13:10) The role of AI Agents in supply chains(26:10) Smart interrogation and data flows(26:24) Adopting AI in supply chain(28:12) Calm from the chaos(31:29) Real-world use cases(34:12) Change management in AI implementation(41:29) The future of AI in supply chain(47:15) Getting started with Autoscheduler.aiAdditional Links & Resources:Connect with Keith Moore: https://www.linkedin.com/in/keithdmoore13/ Learn more about AutoScheduler.ai: https://autoscheduler.ai The Agentic AI Supply Chain White Paper: https://autoscheduler.ai/resource/the-agentic-supply-chain/ Connect with Scott Luton: https://www.linkedin.com/in/scottwindonluton/Connect with Jake Barr: https://www.linkedin.com/in/jake-barr-3883501/ Learn more about Supply Chain Now: https://supplychainnow.com Watch and listen to more Supply Chain Now episodes here: https://supplychainnow.com/program/supply-chain-now Subscribe to Supply Chain Now on your favorite platform: https://supplychainnow.com/join Work with us! Download Supply Chain Now's NEW Media Kit: https://bit.ly/3XH6OVkWEBINAR- Transforming Operations: Flowers Foods Unveils Its Digital Supply Chain Revolution: https://bit.ly/44b8GKdWEBINAR- Tariff Watch - Unpacking the Latest Updates: https://bit.ly/3FvL2zNWEBINAR- When to Walk Away from Warehouse AI - and When to Go All In: https://bit.ly/4dFgCYqWEBINAR- Real Stories: How Digital Planning Helped Australia's Leading Packaging...

As AI continues to dominate headlines and crypto continues to evolve behind the scenes, the real story may lie in their convergence. In this episode of Tech Talks Daily, I sat down with Dan Kim from Coinbase to discuss how these two technologies are shaping the future of digital commerce and development. Dan leads the Coinbase Developer Platform, a project focused on simplifying blockchain development for millions of developers worldwide. He shared how the platform abstracts away complexity through familiar SDKs and APIs, removing the need for deep blockchain expertise. This isn't just about making it easier to code on-chain. It's about opening the door for new kinds of applications, many of which are being driven by AI. We dug into the emerging concept of "agentic commerce," where AI agents can autonomously carry out transactions using blockchain infrastructure. These agents are now capable of acting on our behalf, making purchases and managing digital assets within defined parameters. This shift is already changing how developers think about building tools for e-commerce, travel, and digital services. Dan also discussed the evolving role of creators in this new landscape. Blockchain technology combined with AI is creating new ways to monetize content, build applications, and launch experiences without relying on traditional platforms. He even shared a personal example—his own AI-powered music project that turns complex crypto topics into relatable Top 40 tracks. From the reawakening of HTTP's long-forgotten 402 payment code to the real-world implications of AI agents handling financial transactions, this conversation revealed just how quickly things are moving. For developers and business leaders alike, the fusion of AI and crypto is no longer speculative. It's here, and it's changing how we interact, build, and pay.