AI for Email Outreach

1. 1

   Drafting from a brief

   Producing first-touch messages against a template and a value proposition you define.

2. 2

   Personalisation at scale

   Adapting each message using what is known about the recipient — role, company, recent news, how they found you.

3. 3

   Sequencing

   The follow-ups after the first message, on a schedule, stopping the moment someone replies.

4. 4

   Send-time and volume control

   Spreading sending to mimic normal behaviour rather than dispatching a thousand messages at once.

5. 5

   Reply classification

   Sorting responses into interested, not now, and stop contacting me — and acting on the last one properly.

6. 6

   Testing variants

   Running alternative subject lines and openings and reporting what performs, rather than guessing.

None of the above matters if your messages land in spam. Volume from a domain with no sending history, poorly matched lists that generate complaints, and mailbox providers that have grown considerably better at spotting bulk sending all push in the same direction.

Damage here is slow to appear and slow to undo. By the time open rates fall, the reputation problem is already established, and it affects your ordinary business email too — invoices, replies to customers, everything from that domain. This is the main argument for sending less to better-matched people.

Practical protections: warm up new domains gradually, keep volumes moderate, authenticate properly with SPF, DKIM and DMARC, remove bounces and complaints immediately, and watch reply rate as the health metric rather than send count.

Commercial email is regulated, and the rules apply the same whether a person or a tool composed the message. Depending on where you and the recipient are, that can mean a lawful basis for contact, accurate sender identification, a working opt-out honoured promptly, and a physical address in the message.

GDPR, CAN-SPAM, CASL and their equivalents differ in what they require, and consent rules for business contacts vary by country. Take your own legal advice for the markets you send into — this is general information, not legal advice.

• Get authentication right first — SPF, DKIM and DMARC — before increasing any volume.
• Send from a subdomain rather than your primary domain, so a reputation problem does not reach your ordinary mail.
• Start small and grow gradually. A new domain sending heavily is the fastest route to a spam folder.
• Narrow the list until you could justify every name on it to the person receiving it.
• Confirm opt-outs are honoured automatically and immediately, and test it.
• Track reply rate rather than open rate — opens have become unreliable, and replies are the point anyway.

Will AI-written outreach land in spam?

Filters respond to sending patterns, list quality, authentication and recipient complaints far more than to who composed the text. Where AI causes problems is indirectly, by making high volume easy. Sending less to better-matched recipients, from a properly authenticated domain warmed up gradually, matters much more than the wording.

Is AI-personalised cold email legal?

Cold email is lawful in many jurisdictions subject to conditions — lawful basis or consent depending on location, honest sender identification, a working opt-out, and often a physical address. Requirements differ significantly between GDPR, CAN-SPAM and CASL regimes. Take your own legal advice for the markets you send into.