AI helps when it removes a specific, repetitive chunk of work. The useful cases I see most are drafting and triaging support replies, summarising or extracting data from documents, and speeding up internal tasks people do by hand. It’s a tool for a job, not magic — and if it won’t help your case, I’ll say so.

It can be, if it’s set up carefully. I’m deliberate about what data goes where, which parts stay on your own systems, and what a provider is allowed to keep. Keeping your data sane is part of the job, not an afterthought.

Not always. AI is worth adding when there’s a real, repetitive task it can take over. If your problem is better solved by a plain automation or a fix to your backend, that’s what I’ll recommend — I won’t sell you AI for the sake of it.

You don’t need to understand the technology; you need to name the task that eats time. From there the process is short: we look at how that task flows through your tools today, add the smallest AI step that removes the manual part, and test it against real examples from your business before it touches anything live. You keep a person in the loop wherever a wrong answer would matter. Most owners are surprised that the hard part isn’t the AI — it’s deciding which task is worth automating first.