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AI security and Zero Trust
AI is transforming security for both defenders and attackers. While AI tools can strengthen cyber defenses, they also introduce new threats that require a modern security framework. This whitepaper showcases why you should embrace Zero Trust to stay protected. Download your copy to learn how to adapt your security model to mitigate AI-driven risks while maintaining agility. Contact Intellam to discuss applying these insights to your business.
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What is the relationship between AI and Zero Trust?
AI and Zero Trust have a symbiotic relationship where each enhances the other. AI thrives in the secure environment created by Zero Trust, which focuses on protecting assets and data rather than relying on traditional network perimeters. As AI introduces new challenges, Zero Trust adapts to meet these needs, ensuring a more resilient security framework.
Why is data security more important with AI?
AI amplifies the value of data, making it a more attractive target for cyber attackers. As Generative AI (GenAI) relies heavily on high-quality data for training, organizations must prioritize data classification and protection to mitigate risks. Poorly managed data can lead to unauthorized access and data leaks, emphasizing the need for robust data security strategies.
What is the shared responsibility model for AI security?
The shared responsibility model for AI security involves collaboration between organizations and their AI providers. Depending on the deployment type—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), or Software as a Service (SaaS)—the responsibilities vary. Organizations must manage their own data and application security while leveraging the embedded controls provided by AI platforms to ensure comprehensive protection.
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