Decoding AI Risk explores the critical challenges organizations face when integrating AI models, with expert insights from Fortanix. In each episode, we dive into key issues like AI security risks, data privacy, regulatory compliance, and the ethical dilemmas that arise. From mitigating vulnerabilities in large language models to navigating the complexities of AI governance, this podcast equips business leaders with the knowledge to manage AI risks and implement secure, responsible AI strategies. Tune in for actionable advice from industry experts.
Decoding AI Risk
Claim This Podcastby Fortanix
9 episodes
Updated Daily
Accepts GuestsHas SponsorsLocation 🇪🇺
26
Podcast Authority
BetaPoorBased on show quality, social media presence, reviews, charts, and more
Quality52
Social0
YouTube0
Engagement0
Podcast Overview
Decoding AI Risk explores the critical challenges organizations face when integrating AI models, with expert insights from Fortanix. In each episode, we dive into key issues like AI security risks, data privacy, regulatory compliance, and the ethical dilemmas that arise. From mitigating vulnerabilities in large language models to navigating the complexities of AI governance, this podcast equips business leaders with the knowledge to manage AI risks and implement secure, responsible AI strategies. Tune in for actionable advice from industry experts.
Language
🇺🇲
Publishing Since
3/26/2025
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26
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Recent Episodes
April 17, 2025
Securing AI: Insider Threats and Confidential Computing
<p>In this episode, we unpack one of the most overlooked but dangerous risks in AI deployment—insider threats. While organizations often focus on securing data at rest and in transit, there's a blind spot few talk about: data in use.</p><p>Imagine a secure, on-prem AI system running in your data center. It sounds safe—but what if a trusted insider with just enough access could dump memory and expose raw, unencrypted sensitive data? </p><p>For industries like finance and healthcare, where data privacy is mission-critical, this is a nightmare scenario.</p><p>We dive into real-world concerns from companies handling PII, financial transactions, and medical records. They’re skeptical of SaaS AI and even cautious about internal data sharing. </p><p>So what’s the fix? It's not just about where AI runs—it's how it's built.</p><p>This episode explores why Confidential Computing is critical for <a href="https://www.fortanix.com/platform/armet-ai" target="_blank" rel="noopener noreferer">truly secure AI</a>. From in-memory encryption to secure enclaves and built-in guardrails, we discuss what a next-gen AI platform must include to defend against insider misuse and keep data secure through every stage of processing.</p><p>If you're responsible for AI security or data governance, this episode is your wake-up call.</p>
April 17, 2025
Building Trustworthy AI for Sensitive Industries
<p>In this thought-provoking episode, we explore a major obstacle standing in the way of AI innovation: the complete lack of an enterprise-grade AI platform that meets the unique demands of high-trust industries. </p><p>From banking and intelligence to healthcare, organizations are eager to deploy AI—but only if it guarantees the highest levels of privacy, security, and compliance.</p><p>We walk through real-world use cases—a top global bank, a national intelligence agency, and a major healthcare network—all of whom could benefit immensely from AI, yet remain stuck due to the absence of secure, controllable infrastructure. </p><p>Their needs go beyond what today’s AI tools offer. No public cloud API, generic enterprise setting, or patched-together framework can meet their standards for data sovereignty, zero-trust architecture, offline operability, or air-gapped deployment.</p><p>This episode dives into why today’s AI offerings fall short, what’s really needed to unlock the most sensitive and high-value use cases, and what it will take to build a <a href="https://www.fortanix.com/platform/armet-ai" target="_blank" rel="noopener noreferer">trustworthy AI foundation</a> for the future.</p><p>If your organization handles sensitive data and is serious about secure AI, this conversation is essential.</p>
April 15, 2025
AI Accountability: Responsibility When AI Goes Wrong
<p>In this episode, we tackle one of the most pressing questions in today’s AI-driven world: Who’s responsible when generative AI gets it wrong? </p><p>As enterprises increasingly adopt GenAI for productivity, content creation, and analytics, the stakes rise just as fast. But with those benefits come real challenges—AI hallucinations, misinformation, data privacy breaches, and regulatory risks.</p><p>We dive into the rising concerns surrounding AI-generated falsehoods and the legal, ethical, and reputational fallout for businesses. </p><p>Who should be held accountable—CISOs, compliance officers, AI developers, or executive leadership? The truth is, responsibility is shared—and avoiding risk means building strong governance from the ground up.</p><p>This episode explores the urgent need for AI accountability frameworks, Zero Trust principles in AI deployments, and the role of advanced platforms in securing data, governing models, and preventing harmful outputs. </p><p>If you're wondering how to use GenAI safely and responsibly—this conversation is a must-listen and check out the Zero Trust <a href="https://www.fortanix.com/platform/armet-ai" target="_blank" rel="noopener noreferer">AI platform for secure and compliant GenAI deployments</a>.</p>
9 total episodes available
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- What is Decoding AI Risk?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
No, this podcast does not typically feature guests.
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