AI-Generated Code Is Everywhere. Security Visibility Is Not According to a New Report

At RSA Conference 2026, a new survey from Lineaje highlights a growing risk inside enterprise software pipelines: companies are rapidly adopting AI-generated code, but most lack the visibility required to secure it.

The findings point to a widening gap between perceived security readiness and actual control over AI-driven development environments. That gap is quickly becoming one of the most important cybersecurity challenges facing enterprise teams in 2026.

Enterprises Move Fast on AI Code, but Oversight Lags

According to the survey of 100 cybersecurity professionals at RSAC, AI-assisted development is no longer experimental. It is operational.

More than four out of five respondents said they are already using AI-generated code in production workflows. Yet despite this widespread adoption, only a small fraction reported having full visibility into the code being generated and deployed.

This imbalance is creating what security leaders describe as a dangerous illusion of control.

“Confidence without visibility is a false sense of security. The findings reveal that while enterprises are racing to embrace AI-driven speed, they are doing so with a significant blind spot,” said Javed Hasan, CEO and co-founder of Lineaje. “To bridge this 'confidence gap,' organizations need more than manual oversight; they need an autonomous policy orchestrator that provides a complete AI Bill of Materials. Only by embedding governance directly into the development workflow can enterprises ensure their agentic AI applications are secure-by-design.”

The numbers reinforce that warning. While nearly nine in ten respondents believe they can secure AI-generated code, fewer than one in five actually have full visibility into it. More than half acknowledge that adoption is moving faster than their ability to monitor and control it.

Governance Becomes the Next Battleground

Security leaders are already looking ahead to what comes next, and the answer is not more AI, but better control of it.

AI governance emerged as the top concern for 2027 among those surveyed, reflecting a shift away from experimentation toward operational risk management. The challenge is compounded by fragmented oversight across development environments. Nearly half of respondents reported only partial visibility into their codebases, while more than a third said they have little to no transparency at all.

This fragmentation makes it difficult to enforce consistent policies, detect vulnerabilities, or even understand what code is running across the enterprise.

The rise of agentic AI systems, which can autonomously generate, modify, and deploy code, is accelerating the urgency. These systems expand the attack surface in ways traditional application security tools were not designed to handle.

Trust in AI Slows as Risk Awareness Grows

The survey also signals a cooling in enterprise enthusiasm for AI.

Seven in ten respondents said their trust in AI has not improved over the past year. A notable portion reported that their confidence has actually declined. The shift suggests that organizations are moving out of the early hype cycle and into a more cautious phase focused on accountability and risk.

This change mirrors broader trends across the cybersecurity industry, where leaders are increasingly questioning how to validate and secure outputs generated by large language models and autonomous agents.

From SBOM to AI Governance

The data reflects a rapid evolution in how organizations think about software supply chain security.

In 2024, many enterprises were still struggling to implement a Software Bill of Materials. By 2025, attention shifted toward using AI to improve visibility into software components. In 2026, that optimism has given way to a more complex reality.

The problem is no longer just tracking open source dependencies. It is governing dynamic, AI-generated code that may not have a clear lineage or audit trail.

Security teams are now being asked to manage an entirely new layer of the software supply chain, one that includes models, prompts, generated outputs, and autonomous decision-making systems.

Demand Builds for a Unified Control Plane

One theme in the survey stands out clearly. Enterprises want consolidation.

Nine out of ten respondents said a unified platform that combines governance, security, and policy enforcement is essential. The idea of a centralized control plane for AI systems is quickly moving from a long-term goal to an immediate requirement.

In response to that demand, Lineaje is positioning its UnifAI platform as an answer to the visibility gap. The company describes it as an autonomous policy orchestration layer designed to map an AI Bill of Materials, monitor AI-generated assets, and enforce security controls in real time.

Whether platforms like this can keep pace with the speed of AI development remains an open question. What is clear is that the industry is entering a new phase where visibility, not just capability, will define success.

The Bottom Line for Security Leaders

The takeaway from RSAC 2026 is not that AI adoption is slowing. It is accelerating.

What is changing is the level of scrutiny.

Enterprises are realizing that deploying AI-generated code without governance creates a new class of software supply chain risk. The next phase of cybersecurity will be defined by how effectively organizations can see, understand, and control the systems they are increasingly relying on to build their software.

Right now, most cannot.