I Needed Background Music – Here’s Which AI Tool Worked Best for Each

So the thing that actually pushed me into trying AI music generators was not curiosity or some desire to test new technology. It was a copyright claim on my video. I

had grabbed a track from one of those “royalty-free music for creators” playlists — the ones YouTube itself recommends in the audio library — used it under a product review, video was doing fine for maybe two weeks, and then the claim showed up. Revenue gone. Not a strike technically, just the monetization icon going yellow, but that is real money disappearing from a video that was actually getting views.

Tried disputing it, got nowhere, moved on. But I was not about to keep guessing which “free” tracks are actually free and which ones have some publisher lurking in the background waiting to claim. That whole system is broken and if you have been on YouTube for any amount of time you probably already know that.

Anyway that is how I ended up testing AI music tools. Not all of them, but the main ones people talk about — ToMusic AI, Suno, Udio, Soundraw, Mubert, Beatoven, and AIVA. I am not a musician by any stretch, I just needed background audio that would not get me claimed and that did not sound like someone recorded it inside a tin can.

What I Actually Needed the Music For

Look, I am going to be upfront here because most of these comparison articles pretend the person tested every possible use case like they are running a recording studio. I was not doing that. I needed two things:

• First thing — a short background track that sits under voiceover. This is the bread and butter for anyone making product reviews, tutorials, how-to content, anything where you are talking and you just need something underneath that makes the video feel less empty. The track should be forgettable in a good way. The moment your viewer starts paying attention to the music instead of what you are saying, that track has failed.
• Second thing — a slightly more energetic piece for b-roll sections. You know when you cut away from talking and show the product up close or show some process happening? That section needs a bit more energy, something that picks up the pace for twenty or thirty seconds and then you are back to talking. Not a song. Not something with vocals or a big drop. Just a subtle shift in energy that makes the edit feel intentional.

That is it. Those are my two use cases. I did not need cinematic scores or lyric-based songs or ambient soundscapes for meditation videos. If you need those things this will still be somewhat useful because you will see how the tools behave generally, but my testing was focused on what I described above.

Which Tools Handled the Background Track Job

ToMusic ended up being the one I use most often for this and the reason is kind of boring honestly. It is not because the output blew my mind on first listen. Suno actually sounds better if you compare raw audio quality side by side, pretty much everyone agrees on that. The reason I kept coming back to ToMusic AI is that the whole process of getting a usable track took less effort and less time than the alternatives.

You type something like “calm lo-fi, no vocals, steady, low energy, suitable for voiceover” and you get back something that works. Not amazing. Works. And then you save it in the library and next week when you need a similar vibe for another video you can find it again without scrolling through a feed of random stuff. That part — finding your old generations, comparing them, downloading the right one — sounds like a small thing until you have been using a tool for a month and you have thirty or forty tracks scattered across sessions with no way to search through them. Suno’s interface is kind of a mess for this. Great output, disorganized workspace.

Soundraw did well here too, especially the timeline feature where you can adjust energy levels across different sections of the track. If you want the music to dip during your talking parts and come up during b-roll, Soundraw lets you do that visually which is actually pretty smart. Mubert was fast — like almost instant — but the results sounded generic in a way that was hard to ignore, kind of like hold music that got a slight upgrade.

Beatoven was fine but the interface took longer to figure out than the actual music generation. AIVA felt like it was built for someone who thinks about music in terms of movements and arrangements, which is not me at all.

The B-Roll Energy Bump Was Harder Than Expected

This is where things got more interesting because a “slightly more energetic version of the same mood” turns out to be a weirdly difficult prompt for AI tools. Most of them interpreted “more energy” as “completely different genre” which is not what you want when the track needs to feel like it belongs in the same video as the calmer version.

Suno kept giving me something that sounded like a proper song with structure and build-ups. Impressive, definitely, but way too much for twenty seconds of product close-ups. Udio did something similar — it wants to create music, like actual music with artistic intent, and asking it to make a slightly peppier version of background audio kind of offends its creative sensibilities or whatever is happening inside that model.

ToMusic AI handled this better because the prompt system lets you stay specific without the tool trying to overinterpret what you want. “Upbeat lo-fi, light percussion, no vocals, moderate energy, short format” gave me something that matched the calmer track well enough that the transition in the video edit felt natural. Not perfect. Sometimes it took three or four generations before one landed right. But the process of generating and comparing multiple attempts was not painful, which matters when you are doing this on a Tuesday night and you just want to finish editing.

Soundraw’s timeline approach was useful here too. Instead of generating a separate track entirely you could take the same base composition and drag the energy slider up for the section that plays during b-roll. Same mood, different intensity. Actually clever.

How They All Scored When I Compared Everything

After going through both use cases on each platform multiple times — and I do mean multiple because the first generation is almost never the one you end up using — here is where things settled:

ToMusic AI Music Generator scored highest overall because it was the least annoying to use repeatedly. That sounds like faint praise and maybe it is, but “least annoying to use repeatedly” is actually the highest compliment you can give a tool that you need to open twice a week for the foreseeable future. Suno is more impressive. ToMusic AI is more practical. Depends on what you are actually doing.

Suno wins sound quality, not even a debate. If you are making music where the audio itself is the product — like actual songs — Suno is the tool. But for what I need, sound quality is one column out of six. Ad distraction matters because some of these platforms shove upgrade prompts in your face every third click. Interface cleanliness matters because if the workspace is confusing you spend more time navigating menus than actually listening to outputs. Loading speed matters because generating four variations and comparing them should not take your entire evening.

If you are in the same situation — making content, need music, tired of copyright roulette — just pick one and start generating. You will figure out within three or four sessions whether the tool fits how you work or whether it fights you. The table above might save you some of that trial time but honestly the only way to know is to sit down and make something with it. The copyright claim that started all of this cost me more in lost revenue than any of these subscriptions cost for a full year, so at minimum the math works out.