Recently, AI has infiltrated every corner of software delivery. It is writing code, tuning tests, fixing bugs, correlating logs and - most provocatively - making decisions inside CI/CD pipelines that used to be purely human territory. This isn't marketing hype - it is the inevitable result of handing models not just data, but influence. Influence without accountability is the sort of blind spot that turns innovation into chaos.
While consulting for a national DIY automotive store chain, we discovered a common pattern. Auto enthusiasts (gearheads) who could evaluate spare part technologies and verify quality on their own did not care which store they patronized, as long as the products they needed were always available. On the other hand, relative amateurs and novices who lacked sufficient technical knowledge developed loyalty to retail stores where they felt they received trustworthy guidance to help select the right products for their needs.
As the CEO and cofounder of an AI-native skills company, I've spent the last decade working with talent leaders to build better and fairer hiring processes. And, here's the uncomfortable truth: The biggest source of hiring bias isn't AI-it's us. While high-profile lawsuits like Mobley gets all the headlines, over 99.9% of employment discrimination claims in the previous five years don't center on AI bias, but on human bias.
Artificial intelligence is evolving rapidly, influencing multiple sectors not just by increasing productivity but also by making decisions on behalf of humans, such as screening job candidates and aiding in diagnostics.