🔗 AI security: 10 top risks and best practices in 2026

AI is now an integral part of technology, but it brings significant security risks. A recent report highlighted that 34% of tech firms struggle with managing security for their AI systems.

This article by Jess Lulka provides insight into the growing challenges of AI security, such as adversarial machine learning and prompt injections.

It reveals that threats are no longer limited to traditional vulnerabilities; they now extend to AI-specific weaknesses like model inversion and data poisoning.

The piece emphasizes the importance of adopting updated security practices, frameworks like those from NIST and ISO, and the need for cross-department collaboration.

As AI technologies evolve, understanding these risks is crucial for maintaining robust security measures and compliance in an increasingly AI-driven landscape.