How to Tell If a Song Is AI: Four Checks That Still Work in 2026

A few years ago, working out how to tell if a song is AI was mostly a listening exercise. In 2026 it is a research exercise. Deezer says 75,000 AI-generated songs reach it every day, 44% of all uploads, and it says 97% of people cannot tell AI music from human-made music. When SubmitHub scanned more than a million releases in July 2026, it found AI audio in 38.5% of them.

So the useful question is not "does this sound AI?" but "what can I check?". Here are four checks, in the order worth running them, with what each one can and cannot tell you.

The short version: four checks, in order

Treat the four as evidence that adds up, not as tests that settle anything alone. A song with no AI label, a high checker score, no artist history and a chorus that forgets its own words is very probably AI. A song that trips only one check is probably just a song.

1. Check the platform's own AI label

The cheapest check is to look for a label, because some platforms now tell you. Coverage is uneven:

Deezer is the only one doing the work itself. It says it detected and tagged 13.4 million AI-generated songs in 2025. Spotify is explicit about the limits of its own label. When it launched AI credits, it said that "AI credits show how AI contributed to the song, not that the entire track is AI-generated", and that "the absence of a credit doesn't mean AI wasn't used." Our guides to Apple Music's Transparency Tags and YouTube Music's AI labels cover what those two platforms ask for.

A label is good evidence when it is there. Its absence tells you very little, because SubmitHub's July 2026 scan found that 31% of artists whose tracks flagged positive for AI said they had used no AI at all.

2. Run the song through an AI song checker

If there is no label, an AI song checker is the next step. These tools listen for statistical patterns that generators leave in audio and return a probability. Here are the free ones people use most, from each vendor's own page on 29 October 2026:

Every accuracy figure in that table is the vendor's own. We have not seen any of them independently tested on a shared set of songs, and a "99%" measured on a vendor's own test set says little about the song in front of you.

How SubmitHub's checker decides

SubmitHub's checker was built for playlist curators, so it is worth knowing how it decides. Its version 3 write-up describes two models. A spectral model turns the audio into a spectrogram, a picture of its frequencies over time, and uses image recognition to spot textures typical of AI generation. A temporal model looks at how melody, harmony and rhythm connect from moment to moment. The two are combined into a verdict that separates pure AI from human audio and from AI audio a human has edited.

That middle category matters. SubmitHub's July 2026 scan found 15.3% of releases were hybrids, AI audio later edited or processed by people. Spotify's credits make the same distinction for a reason: "AI" is often one element of a track, not the whole of it.

Why a checker can call a human song AI

The weak point of every checker is the file you give it. On SubmitHub's own announcement, users reported human songs, including decades-old recordings, flagged as likely AI when checked from YouTube or Spotify, while the same songs checked from a lossless download came back human. SubmitHub replied on the same thread that raw AI tracks "share a lot of similarity to processed YouTube tracks" and that "using raw audio tends to get the best results."

You can see why in a spectrogram. The one below is from an AI-generated song, Paper Moons, one of the WaveQuake examples we measured for our Suno alternatives ranking, taken from its public 176 kbps MP3.

The hard ceiling near 16 kHz looks like a fingerprint, and it is one, but of the MP3 encoder rather than the generator. A human song streamed or uploaded at a similar bitrate shows the same shelf. A model that reads spectrogram textures has to separate "compressed" from "generated", and compression is where it is most likely to slip. So check the best-quality file you can get. And never accuse a named artist publicly on one checker score.

3. Look at the artist, not just the audio

A song does not exist on its own. When the audio check is inconclusive, the context usually is not. None of these signals proves anything alone, but they add up:

• A famous voice somewhere it should not be. Lifehacker's guide makes the simplest point well: if a major artist really released a cover, it would be news and on the streaming services, not only in a short video.
• No footprint outside the upload. No live dates, no interviews, no photos taken by anyone else, no other credited musicians or producers.
• Volume and sameness. A catalogue that appeared all at once, with similar artwork and track lengths, released faster than a person could write and record.
• A watermark you can check. Some generators mark their output. Music Business Worldwide reported that everything made in Flow Music, the tool Riffusion became, carries Google's SynthID watermark.

Context also matters for the money. Deezer says up to 85% of streams on AI-generated tracks are fraudulent, which is why fake-artist catalogues and AI music overlap so often. Our explainer on AI music streaming fraud covers how those schemes work. And if your own song has been re-uploaded under someone else's name, our guide to what to do when someone re-uploads your track walks through the takedown steps.

4. Listen for the tells, knowing they are fading

Listening is still worth doing, but expect less from it than older guides promise. Lifehacker's 2024 guide listed the classic tells, and we checked two of them against eight current AI-generated songs we had already measured:

The two tells that still help are both about memory: a vocal that cannot hold a consistent character, and a song that cannot remember its own chorus. Listen to the whole track, then compare the first and last chorus line by line. The tells that are fading are about sound quality, because current generators produce mixes at ordinary commercial loudness. Our eight-song measurements are in the Suno alternatives ranking.

If you make AI music: disclose it

Everything above works better when artists disclose, and the platforms are moving that way. Spotify's credits and Apple Music's tags travel through your distributor, so tick the box when your distributor asks. Deezer will tag fully AI-generated tracks whether or not you do. Google's terms for its generative tools, including Flow Music, forbid "misleading others into thinking that generative AI content was created by a human."

Disclosure also protects you from the checkers. A disclosed hybrid track that a curator's checker flags is a non-event. An undisclosed one looks like the 31% who said they used no AI.

How we put this guide together

We read each platform's and tool's own pages on 29 October 2026, plus SubmitHub's version 3 announcement, Hypebot's report of SubmitHub's July 2026 scan, Music Business Worldwide's coverage of Spotify's AI credits, and Lifehacker's 2024 guide. The loudness, peak and lyric figures come from our own measurements of eight AI-generated songs from WaveQuake's public listening room, taken on 28 October 2026 with ffmpeg and Whisper large-v3-turbo. We did not run any checker against a test set, so we make no accuracy claim of our own for any tool listed here.