Executives of the Year: Bartley Richardson

Bartley Richardson, who joined CrowdStrike in June as its chief AI and autonomous systems officer, now leads the company's new Cyber Superintelligence Lab, an AI research lab whose first release is SafeMind, an agentic system that pairs an offensive cybersecurity model with a defensive one to create an autonomous loop of learning and remediation. Richardson, a former Nvidia engineer, said the lab is "giving the advantage back to the defender" through better automation, citing the asymmetry that "an attacker has to be right once, but the defender has to be right all the time.

Although AI is fundamentally changing cybersecurity, Bartley Richardson thinks the hackneyed IT refrain still rings true: “The best security is the security you don’t have to think about.” Richardson, a former Nvidia https://time.com/collection/time100-most-influential-companies/2026/nvidia/ engineer who joined cybersecurity company CrowdStrike https://time.com/collection/time100-most-influential-companies/2026/crowdstrike/ in June as its chief AI and autonomous systems officer https://www.crowdstrike.com/en-us/press-releases/crowdstrike-appoints-bartley-richardson-as-chief-ai-and-autonomous-systems-officer/ , says his title perfectly reflects his belief that once consumers trust AI, they’ll stop regarding it as “AI.” Instead, it will be just another autonomous tool making life better in the background, like a grammar check in word processing. Richardson is shepherding that transition as leader of CrowdStrike’s new Cyber Superintelligence Lab https://www.crowdstrike.com/en-us/press-releases/crowdstrike-establishes-cyber-superintelligence-lab/ . An AI research lab dedicated to building autonomous cybersecurity systems, its first release is SafeMind https://www.crowdstrike.com/en-us/press-releases/crowdstrike-launches-frontier-models-for-cybersecurity-with-nvidia/ , an agentic system that combats AI attacks by pairing an offensive cybersecurity model with a defensive one, creating an autonomous loop of learning and remediation. “An attacker has to be right once, but the defender has to be right all the time,” Richardson says. “We’re giving the advantage back to the defender, and we’re doing that with ... better automation.”