Building Simple AI Workflows

So far, you've learned to use AI for individual tasks. Now it's time to connect these tasks into automated workflows that run with minimal intervention. This lesson introduces workflow automation tools and shows you how to build AI-powered automations using platforms like Zapier and Make.

What Is an AI Workflow?

An AI workflow connects multiple steps that trigger automatically:

Trigger → AI Processing → Action → (Optional: More Steps)

For example:

• Trigger: New email arrives
• AI Processing: Categorize and extract key information
• Action: Create task in project management tool

Popular Workflow Automation Platforms

Platform	Best For	AI Integration
Zapier	Beginners, wide app support	Built-in AI, ChatGPT integration
Make (formerly Integromat)	Complex logic, visual workflows	OpenAI module, Claude integration
n8n	Self-hosting, developers	Multiple AI nodes
Microsoft Power Automate	Microsoft 365 users	Azure AI, Copilot integration

Workflow Building Blocks

Triggers (What Starts the Workflow)

• New email received
• Form submission
• New file in folder
• Scheduled time
• New row in spreadsheet
• Webhook from another app

AI Processing Steps

• Summarize content
• Extract data
• Categorize/classify
• Generate response
• Translate
• Analyze sentiment

Actions (What Happens Next)

• Send email
• Create task/ticket
• Update spreadsheet
• Post to Slack/Teams
• Create document
• Update CRM

Example Workflows

Workflow 1: Email to Task Automation

Goal: Automatically create project tasks from client emails

Trigger: New email with label "Client Request"
    ↓
AI Step: Extract task details
    - Project name
    - Task description
    - Priority (based on language urgency)
    - Deadline (if mentioned)
    ↓
Action: Create task in Asana/Trello
    ↓
Action: Send confirmation reply to client

Workflow 2: Content Repurposing

Goal: Turn blog posts into social media content

Trigger: New post published (WordPress webhook)
    ↓
AI Step: Generate social versions
    - LinkedIn post (professional tone)
    - Twitter thread (casual, engaging)
    - Instagram caption (with emoji suggestions)
    ↓
Action: Save to spreadsheet for review
    ↓
Action: Notify marketing team in Slack

Workflow 3: Support Ticket Triage

Goal: Automatically categorize and route support tickets

Trigger: New support ticket submitted
    ↓
AI Step: Analyze ticket
    - Category (billing, technical, account, other)
    - Sentiment (frustrated, neutral, positive)
    - Urgency (high, medium, low)
    ↓
Branch: Route based on category
    - Technical → Development queue
    - Billing → Finance queue
    - High urgency → Alert on-call team
    ↓
AI Step: Generate suggested response
    ↓
Action: Add response as internal note

Building Your First Workflow (Zapier Example)

Step 1: Define the Goal

Step 2: Map Out the Steps

Before building, sketch your workflow:

1. TRIGGER: [What starts it]
   App: [Gmail/Outlook/etc.]

2. AI STEP: [What processing is needed]
   Prompt: [Your AI instruction]

3. ACTION: [What happens next]
   App: [Destination app]
   Data mapping: [What goes where]

Step 3: Write Your AI Prompt

The prompt is the most important part. Make it specific:

Expected JSON output format:

{
  "intent": "",
  "product": "",
  "urgency": "",
  "summary": "",
  "response_category": ""
}

Step 4: Test Thoroughly

Before going live:

• Test with real examples
• Check edge cases
• Verify data flows correctly
• Confirm AI output is consistent

Common Workflow Patterns

The Summarize & Route Pattern

Input → AI Summarizes → Route to right person/place

The Extract & Create Pattern

Input → AI Extracts data → Create new record

The Analyze & Alert Pattern

Input → AI Analyzes → Alert if conditions met

The Transform & Distribute Pattern

Input → AI Transforms format → Send to multiple destinations

Workflow Design Best Practices

DO:

• Start simple, add complexity gradually
• Include error handling (what if AI step fails?)
• Log workflow runs for debugging
• Build in human checkpoints for important decisions
• Test with realistic data before going live

DON'T:

• Automate high-stakes decisions without review
• Build complex workflows before mastering basics
• Forget about rate limits (too many requests too fast)
• Skip testing edge cases
• Ignore failed runs - investigate and fix

Planning Your Workflow

Use this template to plan before building:

Getting Started Recommendations

Week 1: Learn Your Platform

• Sign up for Zapier or Make (free tiers available)
• Build 2-3 simple automations without AI
• Understand triggers, actions, and data mapping

Week 2: Add AI Steps

• Add one AI step to existing automation
• Practice writing effective prompts
• Test with various inputs

Week 3: Build Complete AI Workflows

• Combine multiple AI steps
• Add branching logic
• Implement error handling

Key Takeaways

• AI workflows connect triggers, AI processing, and automated actions
• Start with simple workflows before building complex ones
• The AI prompt is the most critical step - make it specific and testable
• Always include error handling and human checkpoints for important decisions
• Popular platforms (Zapier, Make) offer free tiers to get started
• Test thoroughly before deploying workflows that affect real work