Recent headlines around AI-driven vulnerability discovery have focused heavily on open-source software. That makes sense given the visibility of public codebases and the growing attention around AI systems identifying flaws in widely used open-source projects. But the cybersecurity industry is overlooking a much larger and potentially more disruptive shift. Proprietary software is unlikely to remain insulated from these same forces for very long. For years, many organizations quietly operated under the assumption that proprietary software carried less security risk simply because its source code was not publicly available. The logic was straightforward: if attackers could not easily inspect the code, discovering vulnerabilities would naturally become harder. That assumption was always somewhat flawed, but AI is seemingly going to render it almost entirely incorrect. Modern AI systems are becoming capable of reverse engineering software behavior, analyzing binaries, identifying code patterns, and uncovering exploitable conditions without requiring direct access to source code. What once demanded large amounts of manual expertise, specialized tooling and time, can increasingly be automated and accelerated. This changes the equation for proprietary software vendors in a very significant way. The cybersecurity industry is entering a period where AI-assisted vulnerability discovery may become commonplace across both open source and closed-source environments. The distinction between the two begins to matter far less when AI can efficiently analyze compiled applications at scale. In many ways, proprietary software vendors may actually face unique challenges as this transition accelerates. Open source communities, despite frequent criticism, often benefit from extensive peer review, public scrutiny, and rapid collaborative remediation. Vulnerabilities are visible, discussed openly, and frequently patched by distributed communities of contributors. Closed-source ecosystems don’t always move with that same level of transparency, let alone speed. Many proprietary vendors still operate on slower release cycles. Some enterprise applications receive infrequent updates. Legacy commercial software often