Generative AI (GenAI) technologies based on large language models (LLM) are incredibly powerful, capable of rapidly producing text, code, and other outputs in response to any prompt. As a result, they have already demonstrated genuine potential to redefine many aspects of modern life. Yet comparatively few of these technologies have reached full production status.
For example, a recent Amazon Web Services (AWS) Public Sector survey found that just 12% of government executives said their organizations had formally adopted GenAI, while only another 16% planned to do so soon. In many cases, concerns about LLM reliability, accuracy, fairness, security, and accountability held them back.
Delivering GenAI’s full potential will require dynamic, intelligent guardrails to continuously monitor and assess performance and channel responses toward desired or acceptable outcomes. This imperative makes the use of AI observability tools increasingly critical for federal agencies and other organizations that want to deploy GenAI for critical mission requirements.