How to succeed with AI? Combining Kafka and AI Guardrails
AI is changing many things about our efficiency and how we operate: sublime translations, customer interactions, code builder, driving our cars etc. Even if we love cutting-edge things, we’re all having a hard time keeping up with it.
There is a massive problem we tend to forget: AI can easily go off the rails without the right guardrails. And when it does, it’s not just a technical glitch, it can lead to disastrous consequences for the business.
From my own experience as a CTO, I’ve seen firsthand that real AI success doesn’t come from speed alone. It comes from control — control over the data your AI consumes, how it operates, and ensuring it doesn’t deliver the wrong outputs (more on this below).
The other part of the success is about maximizing the potential and impact of AI. That’s where Kafka and data streaming enter the game
One of the biggest risks when dealing with AI is the absence of built-in governance. When you rely on AI/LLMs to automate processes, talk to customers, handle sensitive data, or make decisions, you’re opening the door to a range of risks:
