What is an AI Editor?

An AI editor is a person who reviews, improves, and finalizes AI-generated content before publication. Unlike traditional editors who work with human writers, AI editors specifically work with AI first drafts, focusing on issues common to AI output.

This role combines traditional editing skills with understanding of AI limitations, hallucinations, and typical patterns that need fixing.

What AI editors do

Fact-check relentlessly - verify every factual claim because hallucinations are common. Add specificity by replacing generic AI statements with concrete examples and real numbers. Remove AI patterns like "delve into" and "leverage." Inject expertise through unique perspectives and real-world examples. Optimize for readers by ensuring content actually helps the audience.

AI editors add substance that wasn't in the draft. Traditional editors polish existing depth; AI editors must CREATE depth through addition of specifics, examples, and expertise. It's closer to co-writing than pure editing.

Skills for AI editing

You need subject expertise to spot errors and add valuable insights. Pattern recognition helps you quickly identify common AI issues across multiple pieces. Strategic thinking ensures content serves business goals and targets keywords effectively. Efficiency is essential - edit quickly enough that AI first drafts actually save time compared to writing from scratch.

Common pitfalls include over-trusting AI (always verify claims), under-editing (publishing "pretty good" instead of helpful), and fighting bad drafts instead of rewriting them.

How to edit AI content efficiently

Develop a consistent checklist: verify claims, add specifics, remove AI patterns, inject expertise, check keyword placement, add internal links. Create templates for common improvements.

Batch similar work - edit multiple similar pieces in sequence to build momentum. The goal isn't making AI content "pass" as human writing. It's making content genuinely helpful to readers by combining AI efficiency with human expertise. Readers shouldn't care how it was created; they should just find it useful.