What if the choices we make about AI security today determine who holds power tomorrow?
Erica L. Shoemate brings over a decade of experience from the FBI and U.S. Intelligence Community, followed by senior leadership roles at Twitter, Amazon, and Meta shaping AI policy, cyber strategy, and regulatory readiness. As founder of The EN Strategy Group, she operates at the intersection where national security, emerging technology, and human-centered design collide.
In this episode, David Moulton and Erica...
What if the choices we make about AI security today determine who holds power tomorrow?
Erica L. Shoemate brings over a decade of experience from the FBI and U.S. Intelligence Community, followed by senior leadership roles at Twitter, Amazon, and Meta shaping AI policy, cyber strategy, and regulatory readiness. As founder of The EN Strategy Group, she operates at the intersection where national security, emerging technology, and human-centered design collide.
In this episode, David Moulton and Erica explore how AI is fundamentally reshaping the security landscape, from compressed decision-making timelines and asymmetric threat capabilities to the erosion of trust that creates strategic vulnerabilities.
You'll learn:
- Why AI governance can't be an afterthought—and how building policy alongside innovation creates competitive advantage, not friction
- How the "new security order" is lowering disruption costs while amplifying ambiguity, enabling smaller actors to generate outsized impact
- Why human-centered design isn't about empathy as a value—it's about operational clarity that prevents cognitive overload from becoming a security risk
- The framework for balancing innovation and restraint: treating policy as guardrails, not brakes, while red-teaming AI systems before deployment
- How trust functions as a national security asset—and why overconfidence is the fastest way to lose it
Erica brings rare perspective from both classified intelligence operations and private sector AI deployment at scale. She challenges the assumption that speed and security are trade-offs, arguing instead that ethical AI systems are more durable, more resilient, and ultimately more profitable than those built without accountability.
With AI compressing the timeline from detection to decision to response, the margin for error has never been smaller. This conversation reveals why the choices security leaders make right now—about governance, diversity, transparency, and human oversight—will define who is protected, who is exposed, and who maintains strategic advantage in an AI-driven future.
This episode is essential listening if you're:
- A CISO or security leader deploying AI-enabled systems who needs to balance innovation velocity with governance rigor
- A policy professional struggling to keep pace with AI deployment timelines and seeking frameworks that enable rather than block
- Anyone responsible for building trust in AI systems—whether with users, regulators, or boards—who recognizes transparency as competitive advantage
Related Episodes:
- Securing AI in the Enterprise with Tanya Shastri - Deep dive into AI governance frameworks and platformization strategies
- How to Scale Responsible AI in the Enterprise with Noelle Russell - Building AI systems with fairness, accuracy, and security as foundational design choices
- From Policy to Cyber Interference with Tom Bossert - Bridging national security policy and operational cybersecurity
#AISecurity #CyberGovernance
About Threat Vector
Threat Vector by Palo Alto Networks is your premier podcast for security thought leadership. Join us as we explore pressing cybersecurity threats, robust protection strategies, and the latest industry trends.
The podcast features in-depth discussions with industry leaders, Palo Alto Networks experts, and customers, providing crucial insights for security decision-makers.
Whether you're looking to stay ahead of the curve with innovative solutions or understand the evolving cybersecurity landscape, Threat Vector equips you with the knowledge needed to safeguard your organization.
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