You Paid a Freelancer for Original Copy. Here's How to Find Out If AI Wrote It.

Say you're a content manager at a growing B2B startup. You've been working with a freelance writer for three months — good turnaround, reasonable rates, polished drafts. Then a colleague runs one of the published blog posts through a detector on a whim. The result comes back flagged as likely AI-generated. Now you're staring at a backlog of thirty articles and wondering which ones are real.

This is the situation more content teams are walking into than you'd expect. And the first question is always the same: how do you actually check?

How to Check If Text Is Generated by AI

To check if text is generated by AI, run it through a dedicated AI detection tool — these analyze patterns like sentence uniformity, predictable transitions, and low-entropy word choices that large language models favor. No single tool is definitive, but running text through two or three gives you a clearer signal. Our free AI detector is a good starting point for quick checks on individual pieces.

The process matters as much as the tool. Here's what actually works in practice.

What AI Detectors Are Actually Looking For

AI detectors don't read meaning. They read statistical patterns. Understanding this changes how you interpret results.

When a language model generates text, it makes high-confidence word choices — the most probable next token given the context. This produces text that's readable and coherent but tends toward uniformity. Sentences cluster around similar lengths. Transitions like "it's worth noting" or "this is particularly important" appear at predictable intervals. Paragraph structures echo each other. For a deeper look at the mechanics, how AI detectors work breaks this down in full.

Human writing is messier. It has quirks. A journalist might write a three-word sentence followed by a sprawling, clause-heavy one that loops back on itself. An expert might use unusual phrasing because they're thinking in domain-specific terms, not because they're deliberately varying their rhythm. That randomness is hard to fake — and it's exactly what detectors measure.

A Practical Process for Checking Multiple Pieces

If you're the content manager in the scenario above — or the professor working through a stack of essays, or the editor reviewing a manuscript — here's a workable approach:

• Run each piece through at least two tools. Detectors disagree more often than their confidence scores suggest. A piece flagged by one and cleared by another warrants a manual read, not an automatic verdict.
• Check for structural uniformity. AI text often has a recognizable skeleton — intro paragraph, three supporting points, summary conclusion. That alone isn't proof, but it's a pattern worth flagging.
• Look at the transitions. Phrases like "in today's world," "it is important to consider," and "as we can see" are statistically overrepresented in AI output. Not impossible in human writing, but worth a second look.
• Ask for a draft history or research notes. A freelancer who wrote content from scratch should have some record of the thinking behind it — sources consulted, an early outline, something. AI-generated content tends to have no such trail.
• Compare against earlier work. If the style suddenly shifts — becomes smoother, more formulaic, loses the writer's characteristic habits — that change is worth asking about directly.

What to Do When You Find Something Flagged

A flag is not a verdict. Some human writing triggers detectors, especially if the writer works in a formal register, is a non-native English speaker, or simply happens to write with the kind of clean, precise prose that overlaps with AI patterns. AI detection false positives are more common than most people realize, and acting on one without investigation has real consequences — for a professional relationship, for morale, for fairness.

What a flag should trigger is a conversation, not an accusation. Give the writer a chance to explain their process. Ask for notes or sources. Request a fresh draft of one section written from scratch with an open brief. The response tells you more than the detector score.

If you're publishing that content publicly, there's also an SEO dimension. Google's guidance on AI content focuses on quality and value rather than origin, but text that reads as uniformly machine-generated can hurt engagement metrics and may eventually register in quality signals. Google and AI content SEO covers the current state of that question in detail.

When the AI Content Is Your Own

The scenario flips sometimes. Picture a postgraduate student three days from a submission deadline who used AI assistance on a first draft, then edited it heavily — but now wonders whether the committee will flag it anyway. Or a comms professional who used an AI tool for a rough pass, rewrote most of it, and isn't sure how much of the original fingerprint is still visible.

In that case, checking your own work before it goes anywhere is the smart move. Run it through a detector and see what comes back. If sections are flagged, that's where the rewriting effort should focus — specifically targeting sentence-length uniformity and predictable phrasing patterns that drove the detection.

WriteMask handles this by restructuring flagged text while preserving meaning, and achieves a 93% pass rate on major detection platforms. The goal isn't to game a detector — it's to produce text that reads like a human actually thought it through, because detectors and readers are both responding to the same underlying quality signal.

The Realistic Bottom Line

No tool tells you with certainty that a human wrote something. What detectors give you is signal — probabilistic, context-dependent, useful as one input among several. The content manager who discovered the problem in the scenario above needed to do three things: audit the existing backlog for patterns, have an honest conversation with the freelancer, and put a review step in place before future work goes live.

The checking process is less about finding proof and more about raising questions worth answering. Start with the free AI detector, read the results critically, and treat flags as the beginning of an inquiry rather than the end of one.