Understanding AI, Risk,
and the Future

Why Your CISO Shouldn't Be the Department of No

What if the person whose whole job is risk was the most excited one in the room about AI? That's Mea Clift, and it's a pretty refreshing way to walk into all this. She's the CISO of Cengage, where the data she's protecting belongs to students, so the stakes are real. But instead of bracing for what could go wrong, she leans in, she calls it being "risk excited." She and Mo get into why security is so much better as the Department of KNOW than the department of no, how she handles shadow AI without punishing people for being curious, why she'd tailor a framework she already has instead of building one from scratch, and how she ends up teaching security through Marvel and Monsters Inc. Which, it turns out, is every bit as fun as it sounds.

AI in Healthcare: Protecting Patient Data Without Falling Behind

Your doctor knows things about you that almost nobody else does. So what happens when AI gets access to all of it? Sandy Dunn has spent much of her career worrying about exactly that. She's a healthcare CISO, and her answer is calmer than you'd think: the things that can go wrong aren't new, it's how fast they happen and how far the damage spreads. In this episode, she and Mo get into why HIPAA has become paperwork that protects almost nobody, why the safest data is the data you never collected, and what happens to trust when AI is in the exam room.

The Former Google Cloud CISO's Take on AI, Agents, and What Comes Next

Former Google Cloud CISO Phil Venables on why attackers scaling up scare him more than new bugs, and what trust means when an agent does the work.

AI in Finance: From Money Laundering to Deepfakes

Dr. Janet Bastiman has been making convincing deepfakes since 2017, long before most people knew the word. Now the Chief Data Scientist at Napier AI, she joins Mo to get into why fraud is actually easier to catch than money laundering, how a deepfake already talked a finance team out of millions, and why the human analysts checking AI matter more than ever.

Afraid AI Will Replace You? Here's the One Skill It Can't

James Villarrubia went from building AI for NASA's drone and aerospace programs to becoming CTO of a travel tech company. In this episode, he and Mo get into why curiosity might be the most important skill in the AI era, what happens to our brains when we stop pushing back on the answers we get, and why the people most resistant to AI might actually be seeing something the rest of us are missing.

The Problem With AI Observability Nobody Wants To Admit

Most enterprises have guardrails. Far fewer have visibility into what their AI is actually doing. Alison Cossette, Founder and CEO of ClariTrace, joins Mo to talk about the risk debt quietly building inside agentic systems, why observability and traceability aren't optional anymore, and what leaders need to put in place before something forces their hand.

What Does It Actually Take to Build Unbiased AI?

Nobody told Tennisha Martin the importance of having a mentor, so she built a community of tens of thousands instead. As the Founder and Chairwoman of BlackGirlsHack, her whole mission has been making sure nobody else has to figure it out alone. In this episode, she and Mo get into AI bias, why it's already showing up in places that matter far beyond tech, and why the real fix starts with getting the right people in the room when these systems get built.

AI Governance Needs a Dungeon Master

David Wendt has spent 30 years building models and just as long running D&D campaigns. Turns out both taught him the same things about operating in uncertainty. He joins Mo to talk AI governance at enterprise scale, what real red teaming looks like, and why the smarter move is to stop measuring your AI and start measuring what you actually care about.

Your LLM Has No Idea What It's Doing

Diana Kelley, CISO at Noma Security and former Cybersecurity CTO at Microsoft, joins Mo to work through the real mechanics of LLM risk: why the context window flattens the trust boundary between system instructions and user data, why that makes reliable internal guardrails essentially impossible, and why agentic AI is less a new threat category and more a stress test for the hygiene debt organizations never fully paid off.