With generative AI now capable of producing virtually any style of music, many singers and rappers are beginning to ask: Can I use AI to generate backing tracks? And while this is certainly possible, before you start prompting platforms like Udio or Suno, it’s important to carefully consider the pros and cons.

In this post, we consider the potential issues associated with using generative AI beats in your releases compared to the established lease beat option.

Professional Production Quality

One of the most significant drawbacks of AI-generated beats lies in their overall sound quality. While they may sound acceptable to the untrained ear, when compared to a professionally produced beat, they often fall short, particularly in areas such as the punchiness of the drum transients, which are critical in most modern genres. They also have a slightly flamy sound to them, giving them a low-resolution MP3 quality.

Further compounding this quality issue is AI’s tendency to struggle with maintaining a consistent tempo. Though platforms like Udio and Suno typically stay within a general BPM, the timing often isn’t tight enough to align perfectly with a DAW grid. This is especially the case with longer compositions. This forces you to use time-stretching or warping techniques to correct the audio. Not only is this process tedious, but it can also introduce unwanted sonic artefacts, which is hardly ideal if your goal is to create a polished, studio-quality, radio-ready track.

When you purchase a beat from a skilled and experienced beatmaker, it’s already been mixed and structured with vocals in mind. The timing is spot on, and the arrangement is crafted to complement a vocalist’s performance. You’re often drawn to a specific producer’s work precisely because of the refined audio quality and stylistic cohesion. Using subpar beats can negatively reflect on your artistry and influence how your music is perceived by listeners.

Audience Perception

One increasingly apparent challenge is the growing public discomfort with the rise of generative AI in music. This was made even clearer after producer Timbaland publicly praised AI-generated vocals, which triggered a wave of backlash. A quick scroll through the comment sections reveals a strong resistance among music fans toward AI-produced content. For more on the whole Timbabland controversy, check out this post.

People generally view music as a deeply human form of emotional and creative expression. The idea that a machine can replicate that essence through a few well-crafted prompts doesn’t sit well with many.

And although it might be tempting to obscure the source of your backing track, transparency is a valuable currency as an artist. Sharing where your beat came from and highlighting the beatmaker can help build your personal brand and create promotional opportunities. It is also something that record labels value and are used to handling.

Legal Clarity & Usage Rights

This is where things get a little technical. You’ll need to carefully review the terms and conditions of your chosen music AI platform. While you may be able to generate a beat, that doesn’t necessarily mean you’re free to use it commercially as a backing track. Let’s break down the current legal landscape for the two most popular AI music platforms: Suno and Udio.

Suno

Paid (Pro/Premier) users:

• You own full rights to any music created while subscribed and can release tracks on platforms like Spotify, Apple Music, YouTube, and even for sync licensing.
• Attribution to Suno isn’t required, though it’s appreciated.
• Your commercial rights remain valid even after you cancel your subscription, but only for the music made during your paid period.
• However, Suno doesn’t guarantee copyright safety. Because outputs aren’t guaranteed to be unique, you are responsible for any copyright disputes.

Free (Basic) users:

• You do not own the tracks, and usage is restricted to non-commercial purposes such as personal listening or sharing. Attribution to Suno is required.

Udio

Any paying user:

• Udio claims no ownership over your creations. You retain all rights.
• You’re allowed to use, edit, and distribute your music commercially, as long as it doesn’t include any copyrighted content you don’t own.
• Commercial use does require crediting Udio in your metadata, description, or credits.

Free-tier outputs:

• Free users must also credit Udio. Commercial rights are somewhat similar to those granted to paid users, though full usage typically requires a subscription.

As you can see, both platforms include restrictions, especially on the free tiers. It’s also worth noting that you cannot distribute AI-generated music to platforms with Content ID systems (like YouTube). However, this same rule applies to leased beats unless you have purchased exclusive rights and the leased beat contains no samples.

Possibly the biggest unknown in using AI tools comes from the legal uncertainty surrounding their future. With lawsuits still pending against both Udio and Suno, the landscape could change rapidly depending on the outcomes. Currently, the legality of AI-generated music sits in a grey area, since both platforms have acknowledged training their models on copyrighted material. In response, streaming platforms like Deezer have already introduced AI-detection tools that de-prioritise such content.

So for now, leasing a beat remains a more straightforward and established option, particularly if you’re thinking long term.

Genre Authenticity & Style

One of the most common critiques of AI-generated music is its tendency to sound generic or emotionally detached. This is especially prevalent when attempting to replicate niche genres or cultural nuances. While AI can quickly generate a beat that mimics the surface-level traits of a style, it often misses the subtleties that define genre-specific production.

In contrast, producers who create beats for commercial use are often deeply committed to the scenes they create beats for. Whether that’s trap, boom bap, Afrobeats, Garage or melodic pop, these beatmakers typically spend years mastering their craft and understanding of these styles. They will have a deep appreciation of the technical aspects of production as well as the cultural cues, emotional tones, and evolving trends of their chosen genres.

A top flight beatmaker will know what swing a boom bap snare needs, how to layer melancholy pads in an emo trap track, or where to leave space in a commercial pop beat for a singer to soar. This level of musical intuition is difficult for AI models to replicate, especially when it comes to genre fusion, underground styles, or emerging sounds that aren’t well-represented in AI training data.

Song Selection and Structure

Finally, let’s look at the practical process of finding and adapting a beat for use as a backing track. Chances are, you will have an idea of the kind of beat and mood that you’re after. You might even have a specific key or tempo in mind. More often, you are looking for a beat in the style of a certain artist, a ‘type beat’ as they are commonly referred to.

Most reputable beat-selling platforms offer powerful filters that let you search by mood, tempo, genre, or even the type of artist you’re inspired by. You can also sort by price, making it easier to stick to a budget. Having these search tools available allows you to quickly browse and audition beats with a single click. You can even favourite beats and beatmakers that connect with you, creating useful shortlists.

Generative AI tools, by contrast, are far more unpredictable. You’ll likely need to generate several iterations before finding something that resonates. While platforms like Suno and Udio are relatively fast (producing results in 15–30 seconds), the time still adds up, especially considering you will probably have to generate multiple results. In that same period, you could have previewed dozens of high-quality lease beats.

Additionally, you’ll need to spend time crafting effective prompts, which can be frustrating as they don’t always give you what you ask for. AI platforms don’t allow the use of artists’ or producers’ names in prompts, making it even harder to direct the output toward a specific sound or feel.

Even when you do generate something promising, structuring it into a usable backing track is often challenging. AI tools may introduce too much variation, and organising sections like verses, hooks, and bridges into a cohesive format can require significant editing in a DAW. As mentioned earlier, inconsistent tempo makes this even more difficult.

In contrast, beatmakers often build their tracks using familiar song structures, which simplifies the process. The arrangement is usually polished and intuitive, giving you immediate inspiration for how your vocals might sit on the track. And if you need to make edits, it’s generally much easier.

Summary

While it is tempting to experiment with AI to generate beats for you it’s important that you consider all of the points we have covered in this post. The world of AI music is still evolving rapidly. Whether or not it becomes accepted by mainstream listeners, labels, and streaming platforms remains to be seen.

Depending on your musical goals and values, AI may offer intriguing possibilities. Or you might find the idea of your music containing a fundamentally non-human element unsettling. You may also take issue with the copyright concerns and the ethics of training AI on unlicensed music created by others. This certainly seems to be an issue for many people in the comments sections of AI-related posts.

In the end, the choice is yours. As of now, there’s no law preventing you from using AI-generated beats in your songs. If you’re comfortable with that direction, feel free to explore it, but make sure to do so with your eyes open.

And if you are looking for Beats or Samples for your next project then RouteNote Create has you covered. sign-up now and take your music to the next level (without the use of AI)