CAI-native application security platform Cycode has just released its 2026 State of Product Security for the AI Era. The study found what it terms to a stark security paradox: While AI adoption is now nearly universal, with basically 100% of Companies having AI-generated code, governance and visibility have failed to keep pace. The study found that 97% of organizations are already using or piloting AI coding assistants, and all confirm having AI-generated code in their codebases. Yet, despite this near-total adoption, 81% lack visibility into AI usage and 65% report an increased security risk associated with AI.
The key here is “Shadow AI,” which Cycode terms the Blind Spot. What it means here is that more than four out of five (81%) lack full visibility into how and where AI is being used across the software development lifecycle (SDLC).
“Today, I am proud to launch Cycode’s 2026 State of Product Security for the AI Era, where the data tells a clear story,” said Lior Levy, CEO and co-founder at Cycode. “100% are boosting their AI-related security budgets. So security could remain a blocker… but it shouldn’t. We’re entering an era where security cannot be a blocker. It must be an enabler and active participant in how AI products are developed and delivered. Done right, product security becomes a business advantage: faster releases, safer products, and greater trust.
The absence of oversight, confirmed by a survey of over 400 CISOs and security practitioners, has created a massive new “Shadow AI” problem, forcing a radical shift in enterprise security strategy as unmanaged AI becomes the top security concern. Levy emphasized shadow IT’s significance.
“The biggest risk in your AI strategy is the one you don’t know about: Shadow AI,” Levy stated. “Competitive pressure to innovate with AI has created massive, ungoverned blind spots for security.
“Cycode is fixing this,” Levy stated. Together with Cycode’s MCP server, our AI & ML Inventory and AI Bill of Materials (AIBOM) empower you to discover Shadow AI and gain complete visibility into every AI tool and model in your SDLC. It also lets you govern and report on AI, by implementing and enforcing security policies to easily generate an AIBOM to manage risk and ensure compliance. Cycode also facilitates secure AI development, where you can embed contextually aware security feedback directly into your AI-assisted and vibe coding workflows.
“This is how Cycode continues to lead the way in securing AI development from prompt to production,” Levy stressed
The AIBOM is a powerful new set of capabilities currently in early access to help organizations discover, govern, and secure their use of AI across the entire software development lifecycle.
”We give security teams a single source of truth to discover Shadow AI, establish controls, and empower developers to innovate securely,” said Devin Maguire, Product Marketing Manager at Cycode. It’s how you unlock the full potential of secure AI development, from prompt to production. Our solution is built on three key pillars. First, discover and map your entire AI footprint. Cycode gives you a comprehensive inventory of all AI and ML assets, automatically discovering and cataloguing everything from infrastructure, models, and coding assistants to the specific packages and secrets associated with them. Second, govern AI usage with enforceable policies and AI BOM. Visibility is the foundation, but control is the goal. Finally, the AI & ML inventory and AI BOM complement Cycode’s Model Context Protocol (MCP) server, designed to secure the outputs of AI coding assistants. Cycode’s MCP server achieves this by leveraging a deep understanding of the full code-to-runtime context. This comprehensive contextual awareness allows Cycode to validate and secure AI-generated code, ensuring it aligns with an organization’s security policies and standards. By understanding how code functions within the broader application environment, the MCP mitigates risks associated with AI-produced vulnerabilities and misconfigurations.
Cycode will flag the use of any model that violates the policy. This provides developers with clear guardrails for responsible AI innovation and allows security teams to manage AI risk proactively.
Other data from the report indicate that the role of AI is increasing: Nearly one-third (30%) of respondents state that AI now creates the majority of code in their organizations. The report shows why AI adoption is unstoppable. Participants overwhelmingly respond that AI increases productivity (78%), code quality (79%), and faster time to market (72%).
However, while AI boosts productivity, it also introduces significant risks. Despite near-universal AI adoption, most organizations (52%) lack a formal AI governance framework. This has led to a proliferation of Shadow AI, including the rapid, unmanaged spread of AI development tools, models, and coding assistants. Consequently, security leaders have identified AI-generated code vulnerabilities as both their biggest blind spot and their top security priority for the upcoming year.
“The findings make it clear: AI development is no longer a future trend; it is today’s reality. As security struggles to keep pace with this rapid adoption, the stage is set for a significant supply chain breach, with Shadow AI as the attack vector,” Levy concluded. “It’s no longer sufficient to just find vulnerabilities in AI-generated code. The rapid spread of Shadow AI demands a strategic response: we must gain complete visibility and governance over the entire AI toolchain. This imperative is why Cycode is empowering organizations with the essential visibility, policies, and controls needed to secure AI development from prompt to production.”
“As enterprises accelerate their use of AI in software development, the surface area for application security risk is expanding faster than traditional controls can manage,” said Katie Norton, Research Manager at IDC. “The rise of shadow AI compounds this challenge, creating new layers of exposure that often can’t be fully seen or governed. These market dynamics observed by IDC align with the findings of Cycode’s State of Product Security in the AI Era, highlighting the need for more unified and context-driven approaches to keep security aligned with the pace of AI-driven development.”