In this episode of Open Tech Talks, we delve into the critical topics of AI security, explainability, and the risks associated with agentic AI. As organizations adopt Generative AI and Large Language Models (LLMs), ensuring safety, trust, and responsible usage becomes essential. This conversation covers how runtime protection works as a proxy between users and AI models, why explainability is key to user trust, and how cybersecurity teams are becoming central to AI innovation.
Chapters
00:00 Introduction to AI Security and eIceberg
02:45 The Evolution of AI Explainability
05:58 Runtime Protection and AI Safety
07:46 Adoption Patterns in AI Security
10:51 Agentic AI: Risks and Management
13:47 Building Effective Agentic AI Workflows
16:42 Governance and Compliance in AI
19:37 The Role of Cybersecurity in AI Innovation
22:36 Lessons Learned and Future Directions
Episode # 166
He's founded a next-generation AI cybersecurity company that's revolutionizing how we approach digital defense. With a strong background in enterprise tech and a visionary outlook on the future of AI, Alexander is doing more than just developing tools — he's restoring trust in an era of automation.
What Listeners Will Learn:
Keywords:
AI security, generative AI, agentic AI, explainability, runtime protection, cybersecurity, compliance, AI governance, machine learning
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