AsembleAI brings you thought-provoking conversations at the nexus of artificial intelligence, innovation, and leadership. In each episode, hosts Mac and Sam, veterans in data and tech world, sit down with AI researchers, fast‑scaling founders, Fortune 500 executives, and pioneering technologists to reveal how AI is reshaping business strategy, sparking breakthrough product development, and guiding executive decisions. Tune in for actionable insights, compelling case studies, and forward‑looking perspectives on the promises and pitfalls of AI‑driven innovation.
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Inside AsembleAI: DeepTech, AI & Science is a technology podcast hosted by Mac & Sam, with 52 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.
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Mac & Sam hosts Inside AsembleAI: DeepTech, AI & Science, a technology show with 52 episodes published.
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Episode #55
Ep 55: Ai4 Podcast - Turning 35 Years of Paper Archives into AI Training Data | Dilo Wijesuriya, ARC
Aug 17, 20269 minS5
Recorded live from the Ai4 conference floor in Las Vegas, Sam sits down with Dilo Wijesuriya, President & COO of ARC Document Solutions, to talk about the unglamorous but essential layer of enterprise AI: getting decades of paper archives into a format models can actually learn from. What's Covered: The Technology — ARC holds patents for OCR on wide-format documents (architectural drawings, engineering blueprints) that standard scanning tools can't accurately process, backed by a 200-person engineering team in India. Security & Compliance — SOC 2, SOC 3, ISO 27001, and HIPAA compliant, running on AWS — built for regulated industries like healthcare and financial services. Will Paper Disappear? Dilo's view: not for a long time. Most organizations' most critical institutional knowledge still exists only on paper, meaning today's LLMs simply can't learn from it yet. The Book Destruction Debate — A direct response to recent controversy over companies destroying physical books after digitizing them, and why ARC's non-destructive robotic scanning preserves originals for high-value collections at universities, libraries, and museums. Looking Ahead — Why Dilo believes the next competitive advantage for most enterprises isn't a better model — it's finally accessing the data already sitting in their own archives. Key Quote: "The challenge isn't finding more data. It's making existing information accessible." Connect with Dilo and ARC: Dilo Wijesuriya: https://www.linkedin.com/in/dilo-wijesuriya/ ARC Document Solution: https://www.e-arc.com/ Subscribe: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube #Ai4Conference #DocumentDigitization #AIReadyData #EnterpriseAI #OCR #AsembleAI
EP 54: Ai4 Podcast - Enterprise AI's "Pilot Purgatory" — and the Deepfake Threat | Kathryn Harrison, Concentrix
Aug 17, 202631 min
This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Kathryn Harrison , Global VP of Strategy in AI Commercialization at Concentrix — and an exited founder who built and sold the B2B SaaS platform MakePay, founded Deep Trust Alliance, and previously helped lead IBM Blockchain — about what it actually takes to turn AI into measurable value across a global enterprise. What's Covered: Humans Plus AI, at Global Scale — Concentrix runs customer and technical support across 75 countries and 150 languages. Kathryn makes the case that the future workforce isn't AI replacing people — it's humans plus AI and automation — and what that looks like across 400,000 employees with segmented AI access. Three Rules for Commercializing AI — Kathryn's framework for doing it at scale: start with outcome-based use cases, redesign the work instead of bolting AI on, and build in guardrails, integration, compliance, observability, and humans-in-the-loop. Plus why she frames "tokenomics" as capital allocation. The Agentic Operating System — How Concentrix uses agentic workflows to recruit and onboard 50,000 hires a year, with a 21-day implementation goal — a real production system, not a demo. From Pilots to ROI — Why most AI stalls before it delivers, how to actually measure return, and where enterprise AI spend most often goes wrong. The Deepfake Threat — Drawing on her work founding Deep Trust Alliance, Kathryn on the rise of deepfake-driven fraud, how it differs from traditional cybersecurity, and the broader societal risks. The Coming Shakeout — Orchestration across messy client tech stacks, consolidation among AI startups, and where Kathryn sees AI and automation heading next. Connect with Kathryn: LinkedIn: https://www.linkedin.com/in/kathrynannharrison/ Concentrix: https://www.concentrix.com/ Deep Trust Alliance: https://www.deeptrustalliance.org/ Follow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack #Ai4Conference #AICommercialization #Deepfakes #AgenticAI #Concentrix #AsembleAI
EP 53: Ai4 Podcast - Revolutionizing Healthcare: AI in Drug Discovery | Alex Zhavoronkov, Insilico Medicine
Aug 17, 202641 minS5
This episode was recorded live from the Ai4 conference podcast pavilion, Sam sat down with Alex Zhavoronkov, Founder & CEO of Insilico Medicine , about what it actually takes to turn AI-generated molecules into approved drugs. What's Covered: From Laughed-Out-of-the-Room to 33 Candidates — Alex pitched generative AI for drug design in 2015 and got dismissed. Today: 33 developmental candidates in six years, zero failed toxicity studies, and deals with Eli Lilly, Takeda, Servier, and SK Bio at a pace of nearly one per month. The Real Bottleneck — "It's not about a story. Many people in our field love to tell a story, but they don't have a single drug in the clinic discovered by AI." Alex's direct take on separating hype from results in AI drug discovery. A Lucky Breakthrough — The story of how Insilico stumbled onto a novel, non-opioid pain mechanism that outperformed morphine in animal testing — now targeting a $70 billion market. Why Abu Dhabi — Not for speed, but for geopolitical neutrality. Alex explains why Insilico built a 60-person AI lab in the UAE, and how two drugs now trace their origin to the Middle East for the first time in modern history. Quantum-Generated Drugs — A December 2025 Nature Biotechnology cover story: a molecule generated on a real IBM quantum computer, validated experimentally, with the University of Toronto. Pharmaceutical Superintelligence vs. AGI — Where Alex thinks AI drug discovery already stands, and why he draws a hard line between a useful scientific partner and the "conscious AI God" version of AGI. Key Quote: "In terms of pharmaceutical superintelligence, we're very close to being there. In terms of AGI - the future AI God - we're still not there, and we might never get there." Connect with Alex: LinkedIn: https://www.linkedin.com/in/zhavoronkov/ Insilico Medicine Website: https://insilico.com/ Alex's published manuscript about longevity medicine in the Nature journal: https://www.nature.com/articles/s43587-020-00020-4 Follow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack #Ai4Conference #InsilicoMedicine #DrugDiscoveryAI #Longevity #AsembleAI
EP 52: Shadow AI: Why $10.3M is Costing Your Organization More Than You Know
Jul 14, 202645 minS5
Shadow AI is costing organizations $10.3 million a year—more than malicious insider threats combined. Employees are using AI tools nobody approved, on data nobody's tracking, and most leadership teams have no idea it's happening at this scale. Banning AI doesn't work. You can't solve this with another policy PDF nobody reads. You need real behavioral change. In this episode, hosts Sam Dey and Mac Goswami sit down with Kate Marshall-founder of TheGrai and author of AI at Work—to expose why most enterprise AI rollouts fail at the most critical layer: getting people to actually adopt and stick with new tools and processes. What You'll Learn: 🔹 The $10.3M Shadow AI Problem — What that number actually represents and why banning AI just drives it underground 🔹 The Maturity Model Trap — Why organizations get stuck between Level 1 (Awareness) and Level 2 (Shadow AI), with leadership presenting vendor demos while employees silently use unapproved tools 🔹 Why Generic Training Fails — The fatal flaw of all-hands lunch-and-learn sessions and what role-specific, sticky AI training actually looks like in practice 🔹 The Habit Layer™ Framework — Kate's proprietary methodology for turning one-time training into lasting behavior change 🔹 Data Hygiene as the Foundation — Why cleaning up your downloads folder, emails, and redundant files is where AI transformation actually begins 🔹 The Book: AI at Work — Why Kate wrote a 3-chapter workbook for non-technical professionals instead of another theory-heavy guide Kate's Closing Insight: "Adoption is not a training day. It's a habit. You have to give employees not just access to tools, but time, space, and role-specific guidance to actually learn how to use them." Key Takeaway: The gap between knowing about AI and actually using it effectively is the difference between organizations that transform and those that waste millions on failed pilots. Connect with Kate Marshall: Website: katemarshall.ai LinkedIn: https://www.linkedin.com/in/kate-b-marshall/ Book: AI at Work Subscribe: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube #ShadowAI #AIAdoption #HabitLayer #AIatWork #ChangeManagement #EnterpriseAI #AsembleAI
EP 51: AI-Native Software Development: Building Production Systems with Multi-Agent AI
Jun 21, 202636 minS5
"AI native software development" gets thrown around everywhere right now—and almost nobody can define it clearly. Not a chatbot bolted on. Not Copilot autocomplete. We mean production-grade systems where AI agents write, orchestrate, and ship the work end-to-end. In this episode, hosts Sam Dave and Mac Goswami sit down with Mohamed Faker -engineering leader at Vanguard Group and co-founder/CTO of Hirin, a fractional leadership hiring platform built almost entirely by orchestrating specialized AI agents. Key Insights: What AI-Native Actually Means — Every line of code in Hirin was AI-produced. Mohamed's role: architect, decision-maker, final say on direction—not the one typing code. From Solo Orchestrator to Manager of Agents — How he evolved from manually prompting individual AI chats (architect, UX expert, engineer) to building agent hierarchies with sub-agents and dedicated "audit" agents reporting directly to him. Where Agents Fail — Spotting when an agent burns tokens without progress, takes conversations sideways, or simply isn't suited to the task—and knowing when to stop. Validation at Scale — Building internal "audit department" agents that verify other agents did exactly what was asked, nothing more, nothing less. Product Management Is the New Core Skill — Knowing how to break down features, prioritize by dependency and complexity, matters more than knowing how to code. Biggest AI Adoption Mistakes — Rushing to adopt AI without defining real ROI, plus strategies that fail because the workforce isn't trained or willing to execute them. Human-AI Collaboration — Why the human must always stay in the loop as critical thinker and decision-maker, even as the agent-to-human ratio shifts dramatically. The Horse-and-Carriage Analogy — Entire industries can disappear in 15 years, but the people who adapted earned more by managing the new technology rather than resisting it. Mohamed's takeaway: "The future is you managing a subset of AI agents. Think about it-you're going to have multiple versions of yourself working together." Connect with Mohamed Faker: https://www.linkedin.com/in/mohamed-faker/ Check out Hyern: https://hyern.com/ Subscribe: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube #AINative #MultiAgentAI #SoftwareDevelopment #AIAdoption #ProductManagement #AsembleAI
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