Software Improvement Group (SIG) today launches AI Code Governance, a new capability in its Sigrid platform that enables users to govern AI-generated code and AI technologies across the entire software portfolio.
AI is now a standard part of professional software development. Yet, despite widespread adoption, only about a third of organizations see significant ROI from generative AI, and it is not hard to see why. Most have no clear picture of where AI-generated code sits in their portfolio. This doesn’t stop developers from using AI coding tools, often outside the line of sight on personal accounts.
The risks are concrete: SIG’s data shows that AI-generated code carries more maintainability and security issues than human-written code, meaning the speed gained in initial development is often offset by the technical debt that accumulates downstream.
You cannot govern what you cannot see.
Most of what goes wrong with AI in enterprise today has nothing to do with the technology. The instinct many organizations tend to follow is to go faster; the reality is they need designed speed, a harness to ensure rapid progress and productivity gains without creating more technical or architectural debt.
“AI amplifies what’s already there. Organizations with strong software foundations will go faster and build better with AI. Organizations with technical debt, poor architecture, and ungoverned portfolios will accumulate more problems, more quickly. That was already true with AI coding assistants. With agentic AI — systems that write, test, and deploy code autonomously — the stakes are becoming even higher. The productivity gained in initial code production could be lost in future maintenance, unless you can see what’s happening across your portfolio and act on it,” said Luc Brandts, CEO of Software Improvement Group.
AI Code Governance in the Sigrid platform addresses this directly.
Detect AI-generated code across your portfolio
Sigrid now detects AI-generated code at both the system and portfolio level, giving you a fact-based view of where AI-written code sits across your teams and systems. Sigrid identifies AI-generated code at the system and portfolio level with 95–99% accuracy, currently covering Java, Python, and C#.
See which applications use AI technologies
Beyond code detection, Sigrid shows you which systems rely on AI capabilities and how they connect to the rest of your landscape.
Combined, AI Code Governance gives engineering and IT leadership a real-time, portfolio-wide picture of AI code adoption across teams and systems and empowers engineering teams to boost productivity without sacrificing quality.
“I’m proud of what our R&D teams have built. AI Code Governance detects AI-generated code across the portfolio with 95–99% accuracy. It works through stylometric analysis, trained on 25 years of pre-AI enterprise code and on what frontier models produce today. It learns the delta between them. Now, teams can see whether AI is introducing risk and fix it before it ships. Leaders can see who’s using AI most, whether productivity gains are being eaten by quality and security debt, and where to focus training, tighten reviews, or adjust the definition of done. As agents start writing and deploying autonomously, AI Code Governance is part of the harness they run inside.” said Jasper Geurts, CTO of Software Improvement Group.
Upcoming releases will add capabilities to flag AI-specific security risks, measure the productivity impact of AI coding tools, and provide guidance for AI-assisted Modernization.
For more information, visit softwareimprovementgroup.com/ai-code-governance.
