Why Production AI Exposes Security Gaps Organizations Can't Ignore
Автор: AI Proving Ground Podcast
Загружено: 2026-02-11
Просмотров: 43
Описание:
As enterprises move AI from experimentation to production, security failures are no longer isolated incidents—they are systemic risks embedded deep in infrastructure, data flows, and decision-making systems. In this episode of the AI Proving Ground Podcast, WWT's Istvan Berko, Cisco's DJ Sampath and NVIDIA's Ofir Arkin discuss why as AI becomes core infrastructure, security becomes the mechanism that determines whether that infrastructure scales or undermines itself.
Enterprise AI has crossed an important threshold. It's no longer confined to research teams or isolated innovation clusters. Boards now expect AI to deliver measurable ROI, operational efficiency and competitive advantage. That shift has exposed a fundamental weakness: most security architectures were never designed for non-deterministic systems.
AI workloads behave differently. Models evolve. Agents act on behalf of users and other agents. Decisions are distributed across systems that don't fail loudly when something goes wrong. A minor compromise in training data or identity controls can quietly cascade into degraded accuracy, wasted compute, and eroded trust — often long after the root cause is buried.
This is why security in AI factories cannot be treated as a bolt-on. In this episode of the AI Proving Ground Podcast, experts from WWT, Cisco and NVIDIA discuss how Cisco's Secure AI Factory with NVIDIA is redefining what it means to secure AI at scale — embedding security into the infrastructure itself so enterprises can move AI into production without sacrificing performance, visibility or trust.
"If some attacker can get into that and poison that dataset, you've not only tainted the outcome—you've lost a huge amount of compute over time."
Istvan Berko
#EnterpriseAI #NVIDIA #Cisco #AISecurity #SecureAI #AIInfrastructure #AIAtScale #AIGovernance #CyberResilience #AIFactory #DigitalTrust #TechLeadership
Support for this episode provided by: Rubrik
Chapters:
0:00 Why AI Security Suddenly Matters
2:36 When AI Stops Being Predictable
4:10 Why Risk Models Break
5:09 Inside The AI Factory
7:56 Tiny Flaws. Massive Impact.
10:44 Identity and Data Under Fire
13:53 Platforms Beat Point Tools
16:59 Leaving the Lab for Reality
20:35 Securing AI at GPU Scale
25:27 Security Moves into Hardware
28:36 Resilience in Real Operations
32:32 What Secure AI Really Looks Like
36:20 Old Attacks. New AI Targets.
39:48 Watching AI Make Decisions
43:22 The Ethics Line AI Can’t Cross
45:36 The One Thing That Matters
This is part 3 of a 6-part series, to watch the next episode click here: • The Network Is Becoming the Real Unit of A...
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About WWT:
World Wide Technology (WWT) is a global systems integrator that provides digital strategy, innovative technology, and supply chain solutions to large public and private organizations.
For more about the AI Proving Ground Podcast, visit: https://www.wwt.com/events/ai-proving...
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