Podcast: The Security Strategist podcast

Guest: Eric Schwake, Director of Cybersecurity Strategy, Salt Security

Host: Shubhangi Dua, Podcast Producer and B2B Tech Journalist

Adopting enterprise AI is often seen as a productivity boost. However, a subtler change is happening behind the scenes, and security leaders are still trying to understand it. Enterprises now not only optimise AI tools but are also bringing autonomous agents into their workplaces.

“We would call AI agents an additional workforce that enterprises are deploying,” says Eric Schwake, Director of Cybersecurity Strategy at Salt Security.

The description is more literal than it seems. These agents can access systems, interact with data, and perform multi-step tasks with little human input. Unlike employees, they lack intuition and caution.

In the recent episode of The Security Strategist podcast, Schwake sat down with Shubhangi Dua, Podcast Producer and B2B Tech Journalist to discuss AI agents, shadow AI, and API security challenges are transforming enterprise cybersecurity. Schwake explains how to secure autonomous AI systems at scale today.

Has AI Surpassed Experimentation Across Enterprises?

AI is no longer in the experimental stage. Leadership teams across industries are actively promoting its use to boost innovation. Executives like Jensen Huang, Founder, President & CEO of NVIDIA, are highlighting a larger trend where enterprises are measuring, incentivising, and expecting AI adoption.

This urgency creates a familiar tension. Speed provides a competitive edge, but it also shortens the time available for governance. “You want them to use this innovation to do their work,” Schwake tells Dua. “But you don't want sensitive data leaking and getting into the wrong hands.”

Also Watch: What Happens to API Security When AI Agents Go Autonomous?

Key Takeaways

1. AI agents behave like employees and need the same level of security oversight.
2. Most AI risk sits in the API layer where actions actually happen.
3. Faster AI systems can turn small security gaps into major threats.
4. Unmonitored “shadow AI” tools are quietly exposing sensitive data.
5. Continuous visibility is the foundation of securing any AI ecosystem.

Chapters

• 00:00 Introduction to AI and Cybersecurity
• 02:43 Insights from RSA Conference
• 06:30 The Role of AI Agents in Security
• 08:30 Transitioning from Discovery to Governance
• 12:03 Protecting Sensitive Data in AI Systems
• 15:21 Identifying Weak Points in AI Security
• 18:54 The Need for Measured Security Approaches
• 20:38 CISO Strategies for API Security
• 23:22 The Future of AI in Cybersecurity
• 25:14 Visibility as a Key Security Measure

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Enterprise AI, AI Security, Cybersecurity, API Security, Autonomous Agents, Agentic AI, Shadow AI, AI Governance, Enterprise Technology, Digital Transformation, Security Leadership, AI Risk, Data Protection, AI Compliance, Cyber Risk, CISO Strategy, AI Infrastructure, Emerging Technology, Enterprise Security, Salt Security

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