Customer service
AI for email triage and routing
Define a short list of categories and urgency levels from your real inbox, such as delivery delay, damaged goods, new order or invoice question. Add an AI step to your email or help-desk tool that labels each incoming email, pulls out the order or tracking number and routes it to the right person. Keep a human check on urgent and uncertain cases.
Effort:
Medium
Time saved:
Roughly 30–60 minutes a day less sorting; verify in a pilot
The problem today
A shared inbox such as info@ or orders@ fills up with mixed requests. Someone starts every day reading and forwarding, and urgent issues like a missed delivery wait behind newsletters and supplier spam.
How it works, in plain words
It is like an office assistant who sorts the shared inbox into the right trays each morning, urgent ones on top.
What goes in: incoming emails to a shared address, plus your list of 6 to 10 categories, urgency rules and who owns each category.
What the AI does: it reads each email, picks a category and an urgency level, pulls out details such as the order or tracking number, and says how sure it is.
What a person checks: a person confirms the labels during the first weeks, and later reviews only urgent, uncertain or complaint emails.
What comes out: labelled emails routed to the right person or help-desk queue, with key details ready, so urgent issues are seen first.
It does not answer customers or solve problems. Unusual emails can be mislabelled, so automatic routing stays limited to categories that test reliably.
How it could work for businesses like yours
Illustrative examples, not client case studies.
A 9-person pet supplies e-shop in Kavala
One person spends the first hour of each day forwarding emails about late parcels, wrong items and supplier offers. The shop would sort 200 past emails by hand into eight categories and run AI labelling in suggest-only mode for a month. They would measure how often the label is right per category before allowing any automatic routing.
A 7-person performance marketing agency in Glyfada
Client requests for new ads, budget changes and reports all land in one hello@ address. The agency would tag each email by client and request type and send it to the right account owner's queue. A realistic first target could be every budget-change request reaching its owner within the hour.
A 30-person regional transport company in Alexandroupoli
Customers email about pickups, missed deliveries and proof of delivery in Greek, English and Bulgarian. The company would add an AI step that labels urgency and extracts the consignment number, with missed deliveries always marked urgent and checked by a person. They would track how long a missed-delivery email waits before someone acts.
How to do it, step by step
Export a sample of 200–300 recent emails and sort them by hand into 6–10 categories. This becomes your category list and your test set.
Write clear urgency rules, for example "goods arrived damaged" or "today's delivery missed". Decide who owns each category.
Set up AI classification in your help desk or with an automation tool. Ask it to return a category, an urgency level, the order or tracking number and how confident it is.
Run it in suggest-only mode for 2–4 weeks: the AI labels, a person confirms. Measure how often the label is right for each category.
Switch on automatic routing only for categories that are consistently right. Keep uncertain emails and complaints in a human review queue.
Review mislabelled emails monthly and adjust the categories as your business changes.
Tools to consider
Microsoft Power Automate with AI Builder: classifies Outlook emails, extracts data and routes them within Microsoft 365. Caveat: it needs some setup skill and the right licences.
Zapier or Make with an AI step: connects Gmail or Outlook to ChatGPT or Claude and on to your help desk or sheet. Caveat: each email passes through several services, so check where the data goes and how many runs you use.
Zendesk or Freshdesk: help desks with built-in AI that tags intent, language and sentiment. Caveat: most useful if your team already works in a help desk rather than a plain inbox.
Gmail or Outlook rules: simple filters for predictable cases such as supplier invoices or notifications. Caveat: they are not AI and break on unusual wording, but they often handle the easy emails for free.
Data protection and GDPR
Incoming emails contain names, addresses, phone numbers and sometimes complaints with sensitive details. Use tools with a data processing agreement and, ideally, storage in the EU. Send the classifier only the text it needs, not attachments, and avoid keeping copies in extra services. With Zapier or Make, each connected service is another processor to list in your records. Sorting emails is low risk. Using the same data to rate your own staff by response speed is a different purpose, so check it with your DPO or legal advisor first. Keep logs short-lived.
Mistakes to avoid
Starting with 30 categories instead of the 6–10 that cover most emails.
Switching on fully automatic routing before measuring accuracy per category.
Sending complaints an automatic reply that makes it obvious nobody read them.