The Art of Data Leadership: Lessons from Taylor Culver

Why the most valuable asset in AI won't be the model — it'll be the layer that captures how your business actually makes decisions.

Why the loudest narratives in AI rarely hold up once you talk to the people actually building the technology. In this episode of AI Radicals, host Satyen Sangani talks with Victor Dey, AI and technology analyst contributing to Fast Company, Forbes, and the AI Journal, about what it takes to cut through the noise of enterprise AI — as a journalist who has interviewed the executives running nearly every major data and agent platform in real time. Victor and Satyen dig into how Victor's practitioner background in data science and NLP shapes the questions he asks CEOs, and why a practitioner's mindset increasingly matters for anyone selling, deploying, or building in AI. They unpack the story behind Victor's counter-narrative on the so-called "SaaS Apocalypse" — how one forthright conversation flipped the market narrative and sparked a wave of CEOs finally speaking up. They explore the race to own the AI "control plane," why competitors are simultaneously building and partnering on orchestration, and why context alone isn't enough: permissions, guardrails, and observability matter just as much. "What I think is more important than context, or equally important as context, is also permissions. What data did it touch? What points did it touch? Was it denied or was it told not to perform certain actions? I think that needs equal amount of light." Listen to this episode to learn: Why the SaaS Apocalypse narrative collapsed once a single CEO with conviction and customer evidence spoke up — and what that reveals about how market stories form and break Why the AI control plane is simultaneously the most contested and most collaborative space in enterprise tech, with competitors building rival products while partnering on the same capabilities Why context gets the headlines but permissions, guardrails, and observability deserve equal attention as agents proliferate and incidents mount

Data foundations are the real bottleneck for agentic AI, and most teams are governing the wrong layer.

Why "America's data steward" is more than a job title, and what it takes to keep fraud intelligence trustworthy in the age of AI agents. In this episode of AI Radicals, guest host Susan Wilson, Sales Leader at Alation, talks with Cara Tice, Chief Data Officer at Early Warning (the company behind Zelle), about what data stewardship really means when trillions of dollars in real-time payments, and the fraud intelligence protecting them, run on your data. Cara and Susan dig into why data products have replaced the "one data platform to rule them all" mentality, why integration and change management matter more than any single tool, and why AI doesn't create data problems, it just exposes the ones that were already there. "Your AI governance is reliant on your data management program. Make sure you've got data governance up and running, because AI is going to rely on your data management controls and the context you create." Listen to this episode to learn: Why "data products" — not centralized platforms — are the fastest path to trustworthy, reusable data Why AI governance is really just an extension of data governance, and why the two leaders need to be joined at the hip What a new CDO should fix (and what to leave alone) in their first 90 days on the job

Why AI agents fail at scale, and the systems-thinking fix nobody's building yet.