An automated YouTube content publishing pipeline built with n8n and OpenAI that takes videos from a Google Drive content library, generates SEO-optimized metadata, publishes them to YouTube, tracks publishing status, and reports completion automatically.

The workflow supports scheduled and batch publishing, reducing repetitive work for creators, agencies, and content teams.

Publishing videos manually requires more than uploading a file.

Each video needed:

A search-friendly title

Optimized description

Keywords and hashtags

YouTube discovery tags

Manual upload and configuration

Publishing status tracking

Team notification after completion

Repeating this process across multiple videos consumed significant time and created inconsistent SEO metadata.

I built an AI-powered n8n YouTube publishing automation that connects content tracking, cloud storage, AI metadata generation, YouTube publishing, and reporting.

Google Sheets identifies records marked Pending.

Google Drive retrieves the corresponding video file.

OpenAI generates SEO-focused YouTube metadata.

The YouTube API uploads the video with the generated metadata.

Google Sheets is updated with the publishing result.

Gmail sends a confirmation containing the published video URL.

For each video, the AI workflow can generate:

Multiple SEO title variations

Keyword-rich video description

Calls to action

Timestamps

Relevant hashtags

YouTube discovery tags

This creates a repeatable metadata-generation process instead of relying on manual optimization for every upload.

Each video moves through a controlled lifecycle:

The workflow records:

YouTube video ID

Upload status

Published URL

Timestamp

Processing errors when applicable

Failed uploads can retry up to three times before the error is recorded for review.

The system supports scheduled batch processing, allowing multiple pending videos to be processed during each execution.

This makes the workflow suitable for content libraries containing dozens or hundreds of videos without requiring the team to manually initiate every upload.

10+ hours/week saved on manual publishing tasks

Consistent AI-generated SEO metadata

Automated YouTube publishing and status tracking

Reduced manual configuration errors

Batch processing for multiple videos

Videos can move from scheduled content to published content within minutes

The demonstration workflow is designed to process approximately 5–20 videos per batch on a configurable schedule.

n8n — workflow orchestration

OpenAI — AI metadata generation

Google Drive — video storage

Google Sheets — publishing queue and status tracking

YouTube API — automated video publishing

Gmail — publishing notifications

JavaScript — data processing and workflow logic

Build Type: Self-initiated demonstration build Role: AI Workflow Automation Engineer Platform: n8n Industry: Content Creation / Video Marketing