CrowdStrike strengthens security across AI ecosystem

CrowdStrike has announced innovations with Amazon Web Services (AWS), Intel, Meta, NVIDIA, and Salesforce to secure the future of enterprise AI. 

CrowdStrike is extending Falcon protection across the AI ecosystem through:

- AWS: Securing the full cloud AI lifecycle, from build to test, deployment, and runtime, with native integrations in Amazon SageMaker, Amazon Bedrock, and AWS Marketplace.

- Intel: Protecting data at the source with Falcon Data Protection on Intel neural processing unit (NPU) technology, and with Dell’s AI PCs.

- Meta: Launching CyberSOCEval, a new suite of benchmarks for evaluating how AI systems perform in real-world security operations. 

- NVIDIA – Securing the full AI lifecycle for LLMs and Enterprise AI Factories – from build to runtime to posture management – with the Falcon platform and NVIDIA AI.

- Salesforce: Integrating Falcon Shield into Salesforce Security Center and bringing CrowdStrike Charlotte AI into Salesforce Agentforce for Security to help customers protect their AI agent, workflows, and applications. 

“Securing AI is not just about technology – it’s about securing the full ecosystem where AI is built, deployed, and used,” said Daniel Bernard, Chief Business Officer at CrowdStrike. 

“By embedding protection with the world’s AI leaders, we’re giving enterprises the confidence to adopt AI, innovate with AI, and secure AI, all while delivering revolutionary outcomes.”

According to CrowdStrike, AI lives across the ecosystem where models are built in the cloud and in AI factories, where adoption happens on PCs and endpoints, and where autonomous agents take action. As AI transforms how work gets done, adversaries look for every weak point in the enterprise. Models can be stolen, data poisoned, agents manipulated, and cloud workloads hijacked. 

By embedding unified protection with the companies driving the AI revolution, CrowdStrike is the cybersecurity centre of the AI ecosystem. The Falcon platform delivers the foundation for securing AI – protecting the environments and models where AI runs, preventing sensitive data from leaving endpoints and cloud workloads, uncovering shadow AI apps and risky integrations, and securing AI agents across the software-as-a-service (SaaS) stack.

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