Start with the work, not the tool
Most failed AI projects start with a product and go looking for a problem. We start the other way around. We sit down with the people who do the work, from the front desk to accounting to sales, and look for tasks that are repetitive, rule-based, and time-consuming. Answering the same customer questions. Keying invoices into accounting software. Chasing follow-ups. Building the same weekly report by hand.
Those are the places where AI and automation tend to pay off, because the work is well understood and the result is easy to check. We also look for places where AI is a poor fit, such as decisions that need judgment, situations with legal or safety consequences, or processes that are broken to begin with. Automating a bad process just produces bad results faster.