Why Your AI Pilot Will Fail in Production

So for us, before we put the word trust on it, we need to understand the governance around the solution. So we have a very strong security team, like Michelle said, and we vet every AI system through hands-on testing, proof of concept exercises. We do prompt injection, bias testing, and guardrail testing. We put all that together, and from there, we want to understand how the system behaves when someone tries to manipulate it and push it outside of the intended scope to see how it performs. We want to stress test the solution to see if it meets our agreed-upon metrics. For example, with the chatbot, we were measuring answer accuracy, successful resolution, and how often there's a need for additional support after there's a chat interaction. And then we want to have a feedback loop that goes back to what Michelle said about communication with a partner to share what we're seeing from the technology standpoint, from the cybersecurity standpoint, from the governance standpoint, review the findings with the vendor, and then use that feedback to make improvements.