AI coding is putting software risk on steroids (www.techradar.com)

The rise of generative AI in software development has dramatically increased the speed at which applications are built, enabling tasks that once took days or weeks to be completed in just hours. While this acceleration promises enhanced productivity and rapid innovation, it has also intensified the risk landscape in software security. According to Veracode's recent report, 82% of organizations carry security debt, with 60% harboring critical vulnerabilities that could lead to significant damage, underscoring the urgent need for better governance in an AI-driven environment. As developers increasingly leverage open-source components, APIs, and third-party services, the complexity of software continues to grow, expanding the attack surface for potential threats. Traditional security governance methods—rooted in human-led processes—are becoming inadequate as software creation now operates at machine speed. To address this, organizations must adopt automated risk analysis, continuous dependency evaluation, and agile policy enforcement to keep pace with rapid software evolution. Effective governance will thereby serve as a trust mechanism, allowing organizations not only to scale their software capabilities but also to ensure accountability and reliability in the AI era, ultimately asking the critical question: "Can we trust what we've built?"