How to automate lead generation with AI: Build a lead-enrichment pipeline that writes your icebreaker

How do you automate lead generation with AI? You set up a workflow that scrapes prospect URLs, enriches each record with firmographic data, scores the lead, and finally asks an LLM to write a personalized opening line. The result is a ready-to-export CSV (or direct CRM push) that you can use for outbound outreach without manual research.

What is AI lead generation? AI lead generation is the process of using artificial intelligence to discover, enrich, and qualify prospects automatically.

What you need

\*Pricing is current as of August 2026; check each provider's pricing page for the latest details.

Estimated build time: 6-8 hours for a developer comfortable with n8n and basic API usage.

Step-by-step build

1. Provision the n8n instance - Pull the Docker image: docker run -d --restart unless-stopped -p 5678:5678 n8nio/n8n - Open http://localhost:5678 and create a new workflow called Lead Enrichment + Icebreaker.

2. Add a "HTTP Request" node to fetch a prospect list - Set Method to GET. - URL: https://api.example.com/prospects?status=active (replace with your source). - Enable Pagination if the API returns paged results.

3. Split the list into individual items - Add a "SplitInBatches" node, batch size 1. This feeds each prospect into the downstream nodes one-by-one.

4. Scrape the company website for extra data - Insert a "Browserless" node (provided by the Browserless.io integration). - Endpoint: https://chrome.browserless.io/scrape - Payload (JSON):

 {
 "url": "{{$json[\"website\"]}}",
 "actions": [
 {
 "type": "click",
 "selector": "a[data-contact]"
 },
 {
 "type": "waitForSelector",
 "selector": ".company-info"
 },
 {
 "type": "extract",
 "selector": ".company-info",
 "property": "innerText",
 "as": "companyInfo"
 }
 ]
 }
 

What this does: Visits the prospect's website, clicks the contact link, waits for the company info block, and returns the raw text as companyInfo.

5. Enrich with third-party data (e.g., Clearbit) - Add another "HTTP Request" node. - Method: GET - URL: https://person.clearbit.com/v2/people/find?email={{$json["email"]}} - Authentication: API Key header Authorization: Bearer YOUR_CLEARBIT_KEY.

6. Score the lead - Insert a "Set" node called Score. - Add a field score with the expression:

 {{
 ($json["companyInfo"]?.includes("Fortune") ? 30 : 0) +
 ($json["clearbit"]["employment"]["title"]?.includes("CTO") ? 20 : 0) +
 ($json["openAiSentiment"]?.positive ? 10 : 0)
 }}
 

This simple rule adds points for Fortune-500 mentions, a C-level title, and a positive sentiment from the icebreaker draft (computed later).

7. Generate a personalized icebreaker - Add an "OpenAI" node (built-in in n8n). - Model: gpt-4 - Prompt (copy-paste exact):

 You are a sales writer. Write a one-sentence icebreaker for a cold email to {{ $json["firstName"] }} {{ $json["lastName"] }} at {{ $json["company"] }}. Use the following context: {{ $json["companyInfo"] }}. Keep it under 20 words and include a reference to a recent news item or product launch if possible.
 

What this does: Sends the prospect's enriched data to GPT-4, which returns a concise, context-aware opening line.

8. Store results in Google Sheets (optional for review) - Add a "Google Sheets" node, connect to a sheet named Leads. - Map columns: First Name, Last Name, Email, Company, Score, Icebreaker.

9. Push qualified leads to HubSpot - Insert a "HubSpot" node, set Operation to Create/Update Contact. - Map the same fields plus a custom property lead_score. - Enable a filter: only contacts with score >= 50 are sent.

10. Activate the workflow - Set a cron trigger to run daily at 02:00 UTC. - Turn the workflow Active.

Your pipeline now automates lead generation with AI, delivering enriched, scored contacts and a ready-to-send icebreaker without any manual copy-pasting.

Where this breaks

For a deeper technical reference, see n8n's documentation.