Post by Fulcrum Digital Inc

"What happens when it doesn't work?"    That is the question a CIO asked us during a conversation about deploying AI across his organization.    In production, AI isn’t judged only by its best responses, but also by what happens when confidence drops, an exception appears, or a business-critical process stops working.     Can the system learn from it? When should people step in? How do you monitor it?  More than focusing only on model accuracy, having governance, traceability, permission architecture and clear escalation paths is key to ensure an AI system works after deployment.  That's why, when we built FD Ryze, we didn't focus only on helping enterprises find answers faster. We focused on making those answers traceable, governed, and grounded in the organization's own data.    If you're thinking about moving AI from pilot to production, we've explored this challenge in more detail in one of our latest blogs. Read it here: https://lnkd.in/dxyRwY25