Show Notes
Ashish Rajan doesn’t sugarcoat what it means to be a security leader in the AI era. This is a moment where innovation is outpacing control. Where AI is being embedded into everything, often faster than organizations can understand, govern, or secure it.
Ashish is a CISO, trusted advisor, and host of both the Cloud Security Podcast and AI Security Podcast. He is also the author of the upcoming book AI Security Engineering - which he describes as a framework for building and monitoring secure AI systems.
In this episode, Ashish addresses how security leaders can get ahead of the accelerated use of AI in their organization.
What we cover:
What happens to your risk posture when non-technical employees start committing code
Why the built-in guardrails from your LLM or cloud provider aren't enough, and why assuming they are is your biggest blind spot
What most incident response playbooks are completely missing when it comes to AI
Practical advice for both security leaders and practitioners on how to get ahead of this
Why stick around: If your organization is moving fast on AI adoption, Ashish will tell you plainly what's already exposed, and what to do about it.
Episode resources:
Pre-order AI Security Engineering
Ashish Rajan linktr.ee
Cloud Security Podcast
AI Security Podcast
Ashish Rajan on LinkedIn
Dustin Childs on LinkedIn
Johnny Hand on LinkedIn
TrendAI on LinkedIn
About AI Security Brief
AI Security Brief is where security and technology leaders come to get ahead. Join us for real conversations on the AI trends, threats, and decisions that can't wait.
About TrendAI™
TrendAI™ empowers organizations to lead the future of AI with proactive security designed to inspire innovation and eliminate risk. TrendAI™. AI Fearlessly.
More from AI Security Brief
Your AI initiative gets the green light. But now all the parameters and guardrails you built into your plan need to be executed. Who owns AI once it goes live? Who’s watching as AI use expands? And if the AI workflow fails, can anyone still run the process it replaced?
The “AI trust paradox” in cybersecurity goes like this: organizations invest in AI automation, then hold back from fully implementing it. Yet as attackers continue to use AI to move faster, defenders need to leverage AI to fix things as fast as it finds them.
In traditional IT, isolating a compromised endpoint can stop an attack. In operational technology (OT) environments, that same action could disrupt control of a pipeline, cause a rupture, or trigger environmental damage.
There's no silver bullet when it comes to AI security strategy, and treating one model, tool, or vendor as the answer can limit an organization’s ability to adapt.
Is your organization truly AI native, or did you just bolt AI onto existing infrastructure? Your answer could be an indicator to how much risk you’re carrying without realizing it.