podcast_episode / 1d ago
<p>What does AI adoption actually look like inside Pfizer, a London specialty insurer, and Procter & Gamble? Three practitioners share real deployments — from AI-driven drug discovery and digital twin manufacturing to agentic underwriting and enterprise-wide upskilling — revealing where the technology delivers and where culture still stalls.</p><p>WHAT THIS PANEL COVERS</p>Pfizer is embedding AI across the entire drug lifecycle — target discovery, clinical trial optimization, digital twin manufacturing, and personalized prescriber outreach — to compress a 10-15 year pipelineA London specialty insurer built agentic AI to extract submission data from unstructured documents and resolve entity matching, cutting underwriting time from day...
podcast_episode / 1d ago
<p>The ITU's AI for Good initiative and Deloitte's global research converge in a new report mapping where AI creates real impact — from detecting diabetes through voice analysis to predicting disasters that cost $460 billion annually. This fireside chat unpacks sovereign compute, the global skills gap, and why access to infrastructure, not talent, is the real barrier to AI equity.</p><p>WHAT THIS PANEL COVERS</p>Sovereign AI is now a corporate issue, not just a government one — new models consume 40x more compute tokens than a year ago, making hyperscaler dependency a strategic riskAn Estonian startup can detect blood suga...
podcast_episode / 1d ago
<p>Professor Vijay Gurbaxani makes a bold claim: most companies are approaching AI myopically, treating it as an efficiency tool rather than the next industrial revolution. Drawing on his transformation flywheel framework and examples from Reuters to a two-clinic veterinary startup that caught the attention of a 700-location PE firm, he argues the winners will be those who rethink their entire value proposition — not just their processes.</p><p>WHAT THIS PANEL COVERS</p>The AI transformation flywheel starts with vision, not efficiency — companies must ask 'what more can I be doing?' rather than 'how do I cut costs?'Reu...
podcast_episode / 1d ago
<p>A philosopher, a Microsoft adoption leader, a Swisscom trust executive, and an innovation strategist walk into a fireside chat — and agree on one thing: the biggest barrier to AI-native organizations is not technology but the cognitive dissonance between the C-suite and the workforce. From Karuana Gatimu's blunt take on Copilot to a neuroscience-backed argument for slowing down, this panel challenges the 'move fast' orthodoxy.</p><p>WHAT THIS PANEL COVERS</p>The disconnect between C-suite strategy and frontline reality is the primary adoption blocker — leaders and workers are 'not living in the same reality'Microsoft's AI adoption lead argues speed kill...
podcast_episode / 1d ago
<p>From NVIDIA's AI factories to the EU AI Act's command-center approach, this panel maps the infrastructure layer that makes enterprise AI possible — or impossible. An NVIDIA public sector lead, a Microsoft Asia architect, a Visium CEO, and the architect of Europe's AI regulation debate what it really takes to move from isolated pilots to scalable, interoperable AI systems.</p><p>WHAT THIS PANEL COVERS</p>NVIDIA frames AI factories as the industrial revolution's new foundational asset — importing electricity and data, exporting intelligence — with sovereignty as a core design principleThe biggest enterprise mistake is focusing on isolated point solutions instead of bui...
podcast_episode / 1d ago
<p>MIT's Ramesh Raskar and Prof. Dr. Kathrin Kind map the enterprise of 2030-2035: organizations that shrink in headcount but expand in capability, where every employee creates their own AI models and the 'internet of AI agents' replaces today's siloed copilots. From automotive simulation at 21 million virtual miles to the first room-temperature quantum computing startup, this fireside chat moves fast from present deployments to frontier science.</p><p>WHAT THIS PANEL COVERS</p>Enterprise AI will evolve through three phases — mainframe era (centralized copilots), PC era (employees building their own models), and internet era (networked AI agents communicating across organizations)Pr...
podcast_episode / 1d ago
<p>With 40% of government workers set to retire within five years and China deploying dark factories that build hundreds of thousands of cars without humans, this closing session asks the room to name their industry's burning platforms — and stop pretending the fire is not already lit. From tariff shocks to the Klarna rehiring debacle, the urgency is personal, corporate, and geopolitical.</p><p>WHAT THIS PANEL COVERS</p>Europe's competitive position is eroding in real time — Chinese EVs are materially cheaper and better, and policy barriers are a temporary shield, not a strategy40% of government organization staff will retire within five...