How to Tell if a Song Is AI-Generated

AI music generators like Suno and Udio have reached a point where their outputs can fool casual listeners. A catchy melody, realistic vocals, and polished production — all generated in seconds. But if you know what to listen for, there are telltale signs that separate AI-generated tracks from human-made music.

The Spectral Fingerprint

Every piece of audio has a "spectrogram" — a visual representation of its frequencies over time. Human performances create complex, irregular spectrograms because real musicians introduce subtle variations in timing, pitch, and dynamics. AI music, on the other hand, tends to produce unnaturally smooth spectrograms. The frequency transitions are too clean, too predictable. This is often the first thing forensic analysis tools like SUS IT look for.

Listen for the Loop

AI models are trained on patterns, and they tend to produce patterns. Pay attention to the micro-structure of a track. Does the hi-hat pattern repeat with machine-like precision? Do the chord voicings remain identical from verse to verse? Human musicians naturally drift — a snare hit lands slightly early, a vocal phrase breathes differently on the second take. AI tracks often lack these organic imperfections.

Vocal Tells

AI-generated vocals have improved dramatically, but they still struggle with certain elements. Listen for breath sounds between phrases — many AI generators either omit them entirely or place them at perfectly regular intervals. Real singers breathe irregularly based on the phrase length and emotional intensity. Also pay attention to consonant sounds like "s" and "t" — AI vocals sometimes produce slightly smeared or metallic sibilance.

The Arrangement Problem

One of the most reliable indicators is song arrangement. AI tracks tend to follow formulaic structures very literally — intro, verse, chorus, verse, chorus, bridge, chorus, outro. While many human songs follow this structure too, AI arrangements often feel mechanical in their transitions. The energy builds and drops at predictable intervals, and the transitions between sections can feel abrupt or lack the natural momentum a human producer would create.

Harmonic Clues

AI music generators sometimes produce harmonically "safe" compositions. They tend to stick to common chord progressions and avoid the kinds of surprising harmonic choices that make human music distinctive. If a track sounds pleasant but somehow unremarkable — like background music that never takes a risk — it may be worth investigating further.

When in Doubt, Analyze

Your ears can catch a lot, but forensic tools can catch what you can't. SUS IT performs spectral analysis on the raw audio data, examining frequency distribution, phase coherence, and temporal patterns at a level of detail that goes far beyond human perception. For the most accurate results, upload uncompressed audio files (WAV or FLAC) rather than MP3s, which introduce their own compression artifacts that can interfere with detection.

The Bottom Line

AI-generated music isn't inherently bad, but transparency matters. Whether you're a listener, a label A&R, or a fellow musician, understanding when AI is involved helps maintain trust in the creative ecosystem. As AI models improve, the signs become subtler — but forensic analysis keeps pace, using the mathematical fingerprints that generation models inevitably leave behind.