When Every Cybersecurity Company Sounds the Same, How Do You Build Trust? - Cybersecurity Insiders
As AI capabilities become commonplace in cybersecurity, companies face increasing difficulty in distinguishing themselves through technical advantages alone.
Cybersecurity is experiencing rapid innovation with new AI capabilities and evolving products, yet many companies describe their offerings using similar language promising intelligence, automation, visibility and control. This makes it difficult for organizations to distinguish between solutions when making high-stakes decisions about technology and partners responsible for protecting their businesses.
As AI accelerates product development and makes competitive advantages harder to sustain, brand differentiation and storytelling are becoming increasingly important for earning customer confidence. When every company claims to be AI-powered, the terminology alone rarely communicates meaningful differentiation.
Commodity Capabilities
For years, technology companies could differentiate through advantages that took competitors months or years to replicate. AI is changing that equation, making it more difficult to rely on technical superiority alone. As Ari Yablok, VP of Marketing at Picture Capital, explains: 'The capability is now the commodity. And it's really a matter of why should you matter? Why should you be the one that I should trust and feel like I will have the best experience and outcome if everyone's going to be saying and claiming that?'
When a word and the tech it represents becomes so commonplace across an entire industry, it loses its ability to articulate what makes it special. It's just noise. In the world of cyber, AI is clearly that word.
Human-Centric Positioning
Simply finding new ways to describe similar capabilities won't solve the problem. Companies need a clear perspective and a promise they can substantiate. For Dave Howell, CMO at Legit Security, this became relevant as the company evolved its positioning around agentic application security.
As AI-generated code became more prevalent, Legit sharpened its focus on helping organizations secure code created by AI agents without slowing developers down. The challenge was communicating that evolution beyond technical specifications.
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