daveac

I'm a mid/senior developer at a small-to-medium sized business and spend a fair bit of my free time experimenting with AI training and models. Lately, I've been pondering how heavily companies—especially in smaller organizations—are leaning on AI-generated predictions for decision-making.

My concern is that overreliance on these models might create feedback loops that reinforce inherent biases in the training data. This could lead to a narrowing of options where decisions become self-confirming, ultimately limiting strategic flexibility and innovation.

Have you seen evidence of this happening in practice? How can SMEs strike a balance between leveraging AI insights and maintaining a broad, unbiased perspective in their decision-making?

Are there any practical safeguards or frameworks that you’ve implemented or come across to prevent strategic lock-in?