4 tips for securing GenAI-assisted development

Gartner predicts that generative AI will become a critical workforce partner for 90% of companies by next year, with developers using code assistants like Github Copilot and Google Gemini Code Assist to build software at unprecedented speed. However, this increase in productivity also introduces new security challenges as large language models (LLMs) generate code within seconds, without adhering to organizational policies or best practices, and can unintentionally expose sensitive data. To address these concerns, organizations need to implement strategies for scaling up their application security programs, removing roadblocks with developer-first technology, using training to explain the "why" behind guardrails, creating processes that work alongside GenAI, updating policies to align with GenAI tools, and safely growing and scaling application security across the software development life-cycle. By doing so, organizations can ensure the continuous growth and safe use of GenAI while reducing risk and improving developer adoption.