If you work in video, you know that using a ‘cool song’ is only a part of the creative process. You need music that supports pacing, fits dialogue, can be edited, and won’t cause licensing problems later.
When it comes to AI music generators, not all are created equal. Some may seem like they create solid music, but you might find it hard to edit or use dialogue with it.
This guide explains how AI music generators work and what to look for when choosing one to fit your creative needs.
What an AI music generator actually is
AI music generators are machine learning models trained on big datasets of recorded music. During training, the model analyzes the music’s patterns, like rhythm, harmony, instrumentation, genre features, and song structure.
These generators don’t understand music the way a composer does, instead, they learn statistical patterns. For example, if you write a prompt like “cinematic orchestral build with emotional piano,” the model predicts what would usually come next in that type of music based on its training, then generates your audio based on statistical probability.
That can create music that sounds good. But, generating sound isn’t the same as creating music you can build a video around.
Some models are good at producing texture, vibe, or a loop, but not all AI music generator models can produce a full musical structure, including intros, builds, drops, bridges, and solid endings.
This really shows up when it comes to using AI music generators for instrumental music and vocal music. While some models can generate full songs with lyrics, verses, choruses, and even genre-specific phrasing, others only generate instrumental tracks. Things become even trickier when you need to generate human-like lyrics in different languages, with structured intros and endings.
The main types of AI music generation models
Not all AI music generation models work in the same way. Most fall into three general categories:
Prompt-based generation
This is the most common type of AI music generator. You write a prompt, and the model generates a full track. This is also called text to music AI generation.
Prompt-based models are quick and easy, and are great for exploring ideas, but what you gain in ease, you lose in control. Once the track is generated, you might find you have less control over the arrangement or timing.
Style-conditioned generation
Prompt, with styles included in bold: “YouTube intro music, 120 BPM, electronic drums, bright synth lead, 15 seconds, clear ending high hat.”
As well as using a prompt, these models use style cues, letting you choose genre, tempo, mood, or instrumentation for more control.
This usually leads to more controlled results, which is great if you need music that fits a specific format, such as YouTube intro music or short ad spots. However, this can also lead to very predictable, familiar-sounding music.
Reference-driven generation
Prompt: “Use the reference track, make the bridge longer and remove the second chorus. Instead, add an instrumental section that builds tension before the final chorus. Add lyrics about taking the dog for a walk in the rain.”
Reference track:
Updated track:
Some AI music generators allow you to generate using reference tracks or specifics like tempo, structure, or mood intensity.
This gives you more control over your end result, but it still depends on how well the model behind the generator understands music as a whole, such as how a song is constructed.
Overall, the differences between generators are less about features and more about how well the model understands musical structure.
How some AI music models generate
Different models have different focuses, and that changes how useful the music is once you need to work with and edit it.
Lyria
Lyria focuses on musical progression, with tracks usually moving clearly from intro to build to ending. It isn’t an editing tool, though, so if you need more control over sections, you’ll still need to use other tools as well.
Suno
Suno AI focuses on fast, full songs, often with vocals and lyrics. You enter a prompt and get a finished track in seconds. The songs often sound complete on their own, though editing options can be more limited once you start reshaping them.
Klay
Klay focuses on fast results and style matching. It works well for drafts, but if you need detailed pacing or flexible sections, it might not be the best option.
Things to consider with AI music models
Prompt: “Create a 30-second inspirational pop song with female vocals. Start immediately with full instrumental and vocals at maximum energy. No intro. No instrumental breaks. Add layered backing vocals. Let the final vocal line trail off naturally.”
Editing is usually where AI tracks can become trickier (but not impossible) to work with. For example, looping can expose timing problems, a build may peak too early, or an ending may feel a bit sudden.
Tool flexibility means you might not be able to shorten or extend a section easily. This forces creators to adjust the music to your edit.
Music that sounds good by itself can suddenly sound awkward once you add dialogue or sound effects. Once you lower it under voiceover, it can overpower the voice. The way to get around this is to choose music that’s easily editable. AI music with clear sections, builds, and endings gives you the room needed to cut, loop, and shape around your dialogue without breaking the flow.
Licensing: why this now matters more than ever
Licensing isn’t just a legal detail, especially when it comes to regulation around AI copyright and licensing.
Music licensing affects where and how you can publish your work, and more so with AI. Before you use AI-generated music, you need to know if the tool’s license covers you for monetization, reuse in other projects, and handing it over to clients.
Some AI tools have solid commercial rights that cover you for all of the above, but others limit use or change terms as the tool evolves. As a creator, you’ll need to check the tool’s licensing terms and make sure that you comply.
Before you publish: a quick AI music checklist
Before starting to create AI-generated music for video, it’s a good idea to make sure the tool you’re working with creates music that will be easy to edit later. Here’s a checklist to help you choose your music generator:
- Does it have a clear intro, build, and ending, especially one that works with your edit’s pace?
- Do sections cut and loop smoothly, with no noticeable jumps?
- Does the music work well and sound good under any dialogue?
- Can you adjust the length or structure of your track if you change the timeline?
- Does the tool’s licensing cover you properly for monetized and/or client work?
- Does the energy stay consistent from start to finish?
How to use AI music going forward
AI music works best when it fits both your project, work process, and licensing needs.
With Artlist’s AI music generator, you can create a track quickly, test it, and finish your project using licensed music, sound effects, and other assets in the same place.
AI music is moving fast. From being fun to experiment with to something that’s professionally workable, generators are quickly improving. AI music that cuts and edits easily can change your entire workflow.
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