Can you reliably detect AI-generated content?

Partly. Text detectors and image- and video-forensics tools give useful signals, but none is perfect — all produce false positives and false negatives, and editing or paraphrasing reduces their accuracy. Treat detection as evidence to investigate, not as proof, especially when consequences are serious.

What is the best way to check if an image or video is a deepfake?

Combine tooling with manual checks: look for inconsistent lighting, hands, reflections and audio sync, reverse-image-search the source, and check provenance signals such as C2PA content credentials where present. For high-stakes cases, verify through a second channel rather than trusting any single detector.

Are free AI detectors good enough?

Free tools are fine for quick, low-stakes checks. For anything consequential — academic integrity, hiring, publishing, fraud prevention — use a reputable paid detector, confirm with a second tool, and keep a human in the loop.

How to detect AI text, images and deepfakes: a practical toolkit

“Was this written, drawn or filmed by a machine?” is now a routine question — for editors, teachers, recruiters, fraud teams and anyone who reads the internet. There’s no single button that answers it, but there is a practical toolkit. This guide walks through detection across the four media types, what the tools genuinely do, and the manual checks that still matter.

We have affiliate partnerships with some tools mentioned (we may earn a commission, at no cost to you — see our disclosure).

First principle: detection is a signal, not a verdict

Every detector — for text, images or video — produces false positives and false negatives. Editing, paraphrasing and “humanizer” tools push the numbers further. So the right mental model is a smoke alarm: worth investigating, never a final ruling. For anything that affects someone’s grade, job or money, confirm through a second method and keep a human deciding.

Text

This is the most mature category. Detectors estimate the likelihood that text was machine-generated and, in the better tools, highlight which passages look AI.

For one-off checks, a free tool is fine.
For workflows — editors vetting freelancers, schools at scale — use a reputable paid detector and confirm disagreements with a second.

We compare the leading options in depth in the best AI detectors guide; strong picks include Originality.ai (content teams), Copyleaks (scale and languages) and GPTZero (explains its reasoning).

Images

AI images have improved fast, so rely on a combination of signals rather than one tool:

Forensic detectors estimate whether an image is AI-generated.
Manual tells still help: garbled text in the background, impossible hands or teeth, inconsistent lighting and reflections, melting jewellery or backgrounds.
Reverse image search to find the original or earlier versions.
Provenance — check for C2PA “content credentials,” metadata that some cameras and AI tools now attach to declare how an image was made.

Audio (voice cloning)

Cloned voices are the basis of fast-growing fraud (we cover the criminal side in deepfake fraud and voice cloning). Detection tools exist but lag the generators, so process beats tooling:

Treat unexpected voice requests — especially for money or credentials — as unverified by default.
Verify through a second channel: call back on a known number, use an agreed code word.
Listen for flat emotion, odd pacing and artefacts on consonants, but don’t rely on your ear alone.

Video (deepfakes)

The hardest and highest-stakes category. Combine:

Detection / forensics tools for manipulation analysis.
Manual checks: unnatural blinking, edges around the face and hair, lighting that doesn’t match the scene, lip-sync drift.
Provenance and context: where did it first appear, who published it, does any reputable source corroborate it?

For anything consequential — a “CEO” on a video call authorising a transfer — the only safe answer is out-of-band verification, not a detector score.

A simple workflow

Run a reputable detector for the medium.
Add manual checks appropriate to that medium.
Check provenance (source, reverse search, content credentials).
For high stakes, verify through a second channel and keep a human in charge.

No tool does this for you end-to-end. Together, these steps turn “it looks real” into something you’ve actually checked.

For the deeper defensive playbooks — especially on voice and video fraud — our sister project counterAI goes further.

Tools and techniques were current as of mid-2026 and evolve quickly; verify on the vendor’s site before relying on any single tool.

We report facts with sources and dates. We never label a named company as fraudulent or "AI-washing" as a statement of fact — we present verifiable data and the questions an investor should ask.