Email overload is one of the defining productivity problems of knowledge work. AI can help with several specific aspects — here is what actually works versus what sounds good in a demo.
AI Email Drafting
Claude, GPT-4o, and Gemini all draft professional emails well when given context. The workflow that works: keep a prompt template. “Draft a professional German email declining a meeting invitation. Context: [paste the invitation]. My reason: schedule conflict next week. Tone: polite but direct.” Maintain a small library of templates for your most common email types — responses to recruiters, meeting requests, complaints, and status updates. The drafting takes 30 seconds; editing to your voice takes 1 minute.
Email Summarisation
Long email threads (particularly in German) can be pasted into Claude or ChatGPT and summarised: “Summarise this email thread. What are the key decisions, action items, and unresolved questions?” This works well for returning to a thread after time away or for understanding a thread you’ve been CC’d into. For German-language threads, AI summarisation removes the cognitive load of parsing complex German business correspondence.
n8n Email Automation
For recurring email tasks, n8n (self-hosted free tier) connects to Gmail or Outlook via IMAP/SMTP and can automate: filter newsletters and send daily digest, trigger webhooks on specific sender patterns, or auto-reply with acknowledgement messages. The setup requires technical investment (1–3 hours) but runs indefinitely without maintenance.
What Doesn’t Work Well
Fully automated AI email responses (without human review) for anything important — AI misreads tone, misses context, or generates factually incorrect details. Inbox zero promises — AI makes processing faster but doesn’t change the volume. Priority ranking by AI — the AI doesn’t know what matters to you as well as you do. Use AI for drafting and summarising; keep humans in the loop for sending.
