Application Security

OpenAI-Backed Adaptive Security Joins Fortune’s Cyber 60

OpenAI-Backed Adaptive Security Joins Fortune’s Cyber 60

Adaptive Security, the first and only cybersecurity company backed by the OpenAI Startup Fund, has been named to Fortune’s annual Cyber 60, recognizing the most promising cybersecurity startups shaping the future of digital defense.

The Fortune Cyber 60, created in partnership with Lightspeed Venture Partners, AWS, and the NYSE, spotlights innovators addressing the most urgent challenges in cybersecurity. This year’s list reflects a clear theme: the growing influence of artificial intelligence on both sides of the security equation. Adaptive Security earned its place for pioneering AI-powered social engineering prevention – training organizations to detect and defend against emerging attacks such as deepfakes, voice cloning, and generative AI phishing.

Evolving Threats Require Adaptive Defenses

Founded by CEO Brian Long and Chief Product Officer Andrew Jones, Adaptive Security is building an AI-native defense platform – combining next-generation security awareness training, realistic AI attack simulations, and real-time employee risk analysis to counter AI-driven threats.

“AI has changed the pace of cyberattacks,” Long said. “Most companies still train employees on legacy threats – but that’s not how people are being breached anymore. Companies have to prepare for next-generation attacks like deepfakes, OSINT-powered spear phishing, and AI voice cloning.”

Adaptive’s platform is trusted by Fortune 500 corporations, healthcare systems, financial institutions, and technology firms. In September, the company announced an expanded $55 million Series A funding round, including an additional investment from the OpenAI Startup Fund, which has continued to back Adaptive as its sole cybersecurity holding. The round underscores growing confidence in Adaptive’s approach to human-centered protection at a time when AI is transforming not just how organizations operate – but how they’re attacked.

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