The software development community is experiencing a near ubiquitous usage of AI coding tools as teams face pressure to generate more output in less time. While the huge efficiency gains from the tools help significantly, teams too often fail to incorporate adequate safety controls and practices into AI deployments. Industry leaders are pushing for comprehensive assessments that produce so‑called “trust scores”. These are composite metrics that integrate tool usage, vulnerability data and secure‑coding proficiency to quantify how products and teams influence software‑development lifecycle (SDLC) risk.