“Google will bring you back a hundred thousand answers. A librarian will bring you back the right one.”
— Neil Gaiman

In a world flooded with information, that distinction matters.

Systems don’t usually fail because information is missing. They fail because the right information is hard to find, hard to understand, or hard to use.

A librarian is trained to notice that.

With a Master of Science in Library and Information Science, I was trained to think deeply about how knowledge is structured, organized, retrieved, evaluated, and trusted. Not just what information says, but how people find it, make sense of it, and use it to make decisions.

That lens applies far beyond libraries.

Today’s organizations are built on information systems. Workflows, client experiences, internal processes, knowledge bases, and AI-supported tools all depend on people having access to clear, reliable, well-organized information.

When information is scattered, language is inconsistent, or processes aren’t intuitive, people hesitate. They make mistakes. They ask more questions. Work slows down. And adding new technology to an unclear system can create even more complexity.

That’s especially important with AI.

AI is only as useful as the information, workflows, and human decisions surrounding it. Before asking what AI can automate or improve, organizations need to understand how work gets done today, where information lives, where people get stuck, and which problems are actually worth solving.

My work brings together information science, knowledge management, user experience, content strategy, workflow analysis, and human-centered AI strategy to uncover those patterns and help organizations make clearer decisions about what to improve—and what to do next.

Because having more information isn’t the goal.

It has to make sense.