How to use AI to triage your inbox and draft replies
You triage an inbox with AI by giving it your own sorting rules, letting it group each morning's mail into a few named buckets, and letting it draft replies for the routine bucket only. Everything else it hands you untouched. You keep the send button. Set up this way, you open your mail to a short list of things that genuinely need you plus a stack of drafts to approve, rather than a hundred unread lines you have to read through before you know which ones matter.
This works because most inboxes are really two inboxes stacked on top of each other. A small share of the mail needs a decision only you can make. A much larger share follows a pattern you have answered many times before. Telling those two apart is mechanical work, and mechanical work is exactly what a tool should be doing.
Start with the tool you already have
You do not need to build anything on day one. The tool class here is a general assistant that can read text you give it, and there are three usual routes: the AI features already sitting inside your mail client, a chat assistant you paste into by hand, or a small automation that pipes new mail to a model and puts drafts back in your folder. The third one is the eventual destination. The second one is where you should start.
For the first week, paste in a morning's senders and subject lines and ask for the sort. Read what comes back. When the sort is wrong, and it will be at first, fix the rules rather than the tool. Doing it in that order means you are not building plumbing around instructions that do not yet work, which is the most common way this project stalls.
Write the buckets down first
The rules are the real work here, and they are yours, not the tool's. Four buckets are usually plenty: mail that needs you, mail with a routine reply, mail that is information only, and mail that needs nothing at all. Name them in whatever words you actually use. Then write one plain sentence per bucket describing what belongs in it, with an example or two.
Add one tie-break rule: when the tool is unsure, it goes in the bucket that needs you. An item wrongly sent to your pile costs you a few seconds. An item wrongly treated as routine can cost you a customer. The rule is not symmetrical, so do not let the sorting be either.
Exhibit 1
Your rules do the sorting, and only one bucket gets a drafted reply.
What to feed it
Four things, and they fit on a page or two. The bucket rules you just wrote. A short glossary of names: your clients, your staff, your suppliers, your products, spelled the way you spell them, so nothing comes back mangled. Between ten and twenty real past replies covering the situations that repeat, which teach your voice far better than any instruction to sound friendly and professional. And an escalation list of senders and topics that are never drafted automatically, whatever the tool thinks: complaints, anything legal, anything about money owed, anything from your accountant.
Keep the whole thing small. A tight page that you have actually read beats a folder of documents nobody has looked at since it was assembled, and a short rule set is one you will keep up to date.
The prompt approach
Give the model the role, the buckets with their definitions, the tie-break rule, and a fixed output format. One line per message works well: sender, subject, bucket, and a short reason. Asking for the reason costs you nothing and makes rule problems visible immediately, because you can see whether it misread the mail or simply followed a rule you wrote badly.
For the drafts, add a second instruction covering the routine bucket alone. Write in my voice, matching the examples. Do not state a fact that is not in the thread or the notes. Where a specific detail is needed and missing, leave a marked blank such as [CONFIRM DATE] rather than filling it in. That last line matters more than any other. It is the difference between a draft you skim and approve, and a draft you have to fact-check sentence by sentence, which is slower than writing it yourself.
Check before anything goes out
Approving a draft is a real step, not a formality, and it goes quickly once you know what you are looking for. Names and spellings. Numbers, dates, prices. Any promise the draft makes on your behalf. And anything stated as fact that you cannot trace back to the thread. Tone comes last, and it is usually fine if your examples were good ones.
Exhibit 2
Nothing leaves the drafts folder without passing your check first.
Keep a rough sense of how often you rewrite a draft rather than tweak it. When that keeps happening for one kind of mail, the rules need a change or that type belongs in the bucket that needs you. The same discipline shows up in every routine you hand over, which is why the wider list of tasks AI can take on comes with the same approval step attached to each one.
What to keep out of it
Before you connect anything to a live mailbox, agree in writing what the tool may see and where that information is allowed to go. The simplest version is a list of folders, labels, or senders it never touches: personal mail, anything about staff, anything covered by a confidentiality agreement. Settle this while the setup is still a chat window you paste into, because the answers are much harder to unwind once a system is running on its own. That is the plain, unglamorous half of AI enablement, and it is what makes the rest safe to use.
What this looks like after a few weeks
Not an empty inbox. A shorter one, and a morning that starts with a decision instead of a search. The tool sorts and drafts, you read and send, and the rules get a little sharper each time something lands in the wrong pile. Once that rhythm holds, the same pattern extends easily to the next repetitive job, whether that is drafting a quote from your past ones or turning meeting notes into actions. The judgment stays with you throughout. Only the typing moves.