A hands-on tutorial for building AI-powered automations with n8n. No coding required. Real examples you can implement today.
Building Your First AI Automation: A Beginner's Guide to n8n + AI
AI is powerful. Automation is powerful. Together, they're transformative.
n8n is a free, open-source automation tool that connects to AI models. You can build AI-powered workflows without writing code.
This tutorial walks you through building real AI automations from scratch.
What is n8n?
n8n (pronounced "n-eight-n") is a workflow automation tool:
- Connects apps and services
- Triggers actions based on events
- No coding required (but supports code if needed)
- Self-hosted or cloud
Think Zapier, but open-source, more flexible, and with better AI integration. For a detailed comparison, see our Zapier vs Make guide.
Getting Started
Option 1: n8n Cloud (Easiest)
- Go to cloud.n8n.io
- Create free account
- Start building
Free tier includes 2,500 executions/month.
Option 2: Self-Hosted (Free)
# Using Docker
docker run -it --rm \
--name n8n \
-p 5678:5678 \
-v n8n_data:/home/node/.n8n \
n8nio/n8n
Access at localhost:5678
Option 3: Desktop App
Download from n8n.io for Mac/Windows/Linux.
Your First AI Workflow
Let's build something real: An email summarizer that sends you daily digests.
Workflow Overview
- Trigger: Schedule (every morning)
- Fetch: Get unread emails
- AI: Summarize each email
- Send: Email yourself the digest
Step-by-Step
Step 1: Create New Workflow
Click "New Workflow" in n8n. You'll see a blank canvas.
Step 2: Add Schedule Trigger
- Click "+" to add node
- Search for "Schedule Trigger"
- Configure: Every day at 8:00 AM
Step 3: Add Email Fetch
- Add "Gmail" node (or your email provider)
- Connect your account
- Operation: "Get Many"
- Filters: Unread = true, Since = last 24 hours
Step 4: Add AI Summarization
- Add "OpenAI" node
- Enter your API key
- Operation: "Chat"
- Model: GPT-4o-mini (cost-effective)
- Messages:
- System: "You are an email summarizer. Provide a 2-sentence summary of each email."
- User:
{{ $json.body }}
Step 5: Aggregate Results
- Add "Aggregate" node
- Combine all summaries into one message
Step 6: Send Digest
- Add "Send Email" node
- To: Your email
- Subject: "Daily Email Digest"
- Body: The aggregated summaries
Step 7: Test and Activate
- Click "Execute Workflow" to test
- Fix any issues
- Toggle "Active" to enable
Practical AI Automations
Automation 1: Lead Qualifier
Trigger: New form submission (Typeform, Google Forms)
Process:
- AI analyzes submission for lead quality
- Scores lead (1-10)
- High scores → Notify sales immediately
- Low scores → Add to nurture campaign
n8n Flow:
Typeform → OpenAI (qualify) → IF (score > 7) → Slack + CRM
→ IF (score ≤ 7) → Email campaign
AI Prompt:
Analyze this lead form submission and score from 1-10:
- 9-10: Enterprise buyer, urgent need
- 7-8: Good fit, active interest
- 5-6: Potential fit, early stage
- 1-4: Poor fit or spam
Submission: {{ $json.answers }}
Respond with JSON: {"score": X, "reason": "..."}
Automation 2: Content Repurposer
Trigger: New blog post published (WordPress, Ghost)
Process:
- Fetch blog content
- AI creates social posts
- Schedule to multiple platforms
n8n Flow:
RSS Feed → OpenAI (create posts) → Twitter + LinkedIn + Buffer
AI Prompt:
Create social media posts from this blog article:
Title: {{ $json.title }}
Content: {{ $json.content }}
Generate:
1. One tweet (280 chars max)
2. One LinkedIn post (2-3 paragraphs)
3. Three hashtag suggestions
Format as JSON.
Automation 3: Support Ticket Router
For more enterprise workflow automation patterns, see our workflow automation guide.
Trigger: New support ticket (Zendesk, Freshdesk)
Process:
- AI analyzes ticket content
- Categorizes issue type
- Assigns priority
- Routes to appropriate team
n8n Flow:
Zendesk Trigger → OpenAI (analyze) → Update Ticket → Slack (if urgent)
AI Prompt:
Analyze this support ticket:
Subject: {{ $json.subject }}
Body: {{ $json.body }}
Determine:
- Category: [billing, technical, feature_request, bug, other]
- Priority: [low, medium, high, urgent]
- Suggested team: [billing, engineering, product, general]
- Sentiment: [positive, neutral, negative, angry]
Respond as JSON.
Automation 4: Meeting Notes Processor
Trigger: New recording in Zoom/Google Meet
Process:
- Transcribe recording
- AI extracts action items
- Creates tasks in project management tool
- Sends summary to attendees
n8n Flow:
Zoom → Whisper (transcribe) → OpenAI (extract) → Notion + Slack
AI Prompt:
Analyze this meeting transcript and extract:
1. Summary (3-5 bullet points)
2. Action items (who, what, deadline if mentioned)
3. Key decisions made
4. Open questions
Transcript: {{ $json.transcript }}
Format as structured JSON.
Automation 5: Competitive Monitor
Trigger: Schedule (weekly)
Process:
- Fetch competitor content (RSS, Google Alerts)
- AI analyzes for notable changes
- Compiles report
- Emails to team
n8n Flow:
Schedule → RSS (competitor A) + RSS (competitor B) → OpenAI → Email
AI Prompt:
Analyze these competitor updates from the past week:
{{ $json.items }}
Identify:
1. New product features announced
2. Pricing changes
3. Marketing campaign themes
4. Notable blog/content topics
5. Anything our team should know
Provide a concise brief for the product team.
Working with AI Nodes
OpenAI Node
Most common choice. Supports GPT-4, GPT-4o-mini.
Key settings:
- Model: Choose based on task complexity
- Temperature: 0 for consistent output, 0.7 for creative
- Max tokens: Limit output length
Anthropic (Claude) Node
Available in n8n. Same setup pattern as OpenAI.
AI Agent Node
For complex, multi-step AI reasoning:
- Gives AI access to tools
- Can make decisions about next steps
- More powerful, more complex
Custom HTTP Request
Connect to any AI API:
- Add HTTP Request node
- Configure authentication
- Build request body
- Parse response
Best Practices
Error Handling
Add error handling to every AI workflow:
- Error Trigger: Catches failures
- Retry Logic: Try again on transient errors
- Fallback: Human notification if AI fails
Rate Limiting
AI APIs have limits. Manage with:
- Wait nodes: Add delays between calls
- Batching: Process items in groups
- Caching: Store results to avoid repeat calls
Cost Control
AI calls cost money. For detailed optimization strategies, see our AI cost guide.
Control with:
- Cheaper models for simple tasks (GPT-4o-mini vs GPT-4)
- Shorter prompts (fewer tokens)
- Limit output length (max_tokens)
- Cache repeated queries
Testing
Before activating:
- Test with sample data
- Verify AI output quality
- Check error handling
- Monitor first few runs
Common Pitfalls
AI Output Parsing
AI returns text. If you need structured data:
Problem: AI returns unparsable response.
Solution:
- Explicitly request JSON in prompt
- Use JSON mode (OpenAI)
- Add fallback parsing logic
Long Content
AI has context limits.
Problem: Content exceeds model context window.
Solution:
- Summarize first, then process
- Split into chunks
- Use model with larger context
Inconsistent Responses
AI output varies.
Problem: Same input, different output format.
Solution:
- Lower temperature (0-0.3)
- Provide examples in prompt
- Use structured output mode
Resources
n8n Resources
- Documentation: docs.n8n.io
- Templates: n8n.io/workflows
- Community: community.n8n.io
AI API Documentation
- OpenAI: platform.openai.com/docs
- Anthropic: docs.anthropic.com
- Google AI: ai.google.dev
Frequently Asked Questions
What is n8n and do I need coding skills to use it?
n8n is a free, open-source workflow automation tool that connects apps and AI models through a visual interface. You don't need coding skills for basic automations - it works with drag-and-drop nodes. However, it supports code for advanced use cases if you want more control.
How is n8n different from Zapier or Make?
n8n is open-source and can be self-hosted (completely free), while Zapier and Make are cloud-only with usage limits. n8n offers better AI integration, more flexibility for complex workflows, and unlimited executions when self-hosted. The tradeoff is slightly more technical setup.
How much does it cost to run AI automations with n8n?
n8n itself is free (self-hosted) or $20-50/month (cloud tier). The main cost is AI API usage - using GPT-4o-mini for automations typically costs $5-50/month depending on volume. A basic email summarizer processing 30 emails daily costs roughly $0.50-1/month in AI API fees.
What's the best first AI automation to build with n8n?
Start with an email summarizer that runs daily: schedule a trigger to fetch unread emails, use OpenAI to summarize each one, and email yourself a digest. This teaches core n8n concepts, uses AI meaningfully, and provides immediate value. It takes about 30 minutes to build.
Can I use Claude or other AI models instead of OpenAI?
Yes, n8n supports multiple AI providers including OpenAI, Anthropic (Claude), Google AI, and others. You can add any AI API using the HTTP Request node with custom configuration. Different models work better for different tasks - Claude excels at analysis while GPT-4o-mini is more cost-effective.
How do I prevent my AI automations from costing too much?
Control costs by using cheaper models for simple tasks (GPT-4o-mini vs GPT-4), adding delays between API calls to avoid rate limits, caching repeated queries, limiting output length with max_tokens, and monitoring usage in the early days. Most basic automations cost under $10/month with proper model selection.
Get Started Today
- Sign up for n8n (cloud or self-hosted)
- Get an OpenAI API key
- Build the email summarizer above
- Expand from there
AI automation isn't just for engineers. With n8n, anyone can build powerful AI workflows.
Start simple. Learn by doing. Automate one process at a time.
Your first automation is 30 minutes away.
Need help building AI automation for your business? Cedar Operations designs custom automation solutions. Let's discuss your needs →
Related reading:
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