Moving from AI PoCs to Deployment: Lessons from AI Breakfast

Many AI initiatives stall because teams treat LLMs as a “magic box” and accumulate PoCs that never reach production. This post describes S-PRO’s small-format “AI Breakfast” roundtables and the practical decision tools discussed: start with non-sensitive data, prioritize use cases via an impact–effort matrix, and use an AI maturity model to plan what productionization really needs (data pipelines, security guardrails, user adoption). It also surfaces executive concerns—data leakage, accountability when systems fail, and auditability in regulated domains. Tech leaders get a repeatable way to move from experimentation to governed, operational AI.