I was chatting with a fellow producer the other day who, like me, has been excited and inspired by the creative possibilities AI brings to music. He had recently generated rapped AI Vocals, and they fit the track beautifully. The only issue? He couldn’t quite decide how he felt about releasing a song where the vocals weren’t performed by a human.

Following our conversation, I decided to take a closer look at the moral dilemmas and practical considerations involved in using AI vocals in a commercial music release.

AI Vocals v Musical Elements

When breaking down a song, it’s easy to separate it into two main components: the vocal and the musical accompaniment. While AI can now replicate nearly every element of a track, does the use of AI in some parts raise deeper creative or ethical questions than others? Are certain aspects of music creation inherently more “human” and therefore more problematic when it comes to generating AI derivatives?

Take, for example, a synth arpeggio compared to a saxophone solo. Although both may be played or programmed by a human, the sax solo tends to inherit a more organic, expressive quality. And when it comes to human expression, few things rival that of a sung or rapped vocal. With that in mind, let’s use vocals and lyrics as the focal point to explore the broader implications of involving AI in the music-making process.

A Matter of Quality

Before we delve too deeply into the ethical considerations it’s worth considering the more logistical issues. There are various aspects that may have a bearing on whether an AI vocal would even be a viable option. Let’s explore some of these.

Lyrics

First things first: all songs need lyrics, unless you’re going for a bit of jazz scat. Even before AI could generate realistic vocal recordings, it was already being used to write or assist in writing song lyrics. Tools like Botnik and BoredHumans Lyrics Generator would employ large language models and neural networks to create lyrical content. The technology has come a long way, but for an experienced or analytical ear, it’s still often possible to detect when lyrics have been generated artificially.

When it comes to AI-generated vocals, there are various scenarios to consider, each with its own set of questions.

• Is it acceptable to use AI to write or refine lyrics and then have a real vocalist record them?
• What if you write the lyrics yourself but use AI to perform them?
• Or, as was the case with my friend, what if AI handles everything—from writing to performance?

At their core, lyrics are an expression of human emotion and lived experience, so the idea of a computer generating them can feel somewhat hollow or disingenuous. But on the other hand, artists for years have been using songwriters to write their songs. For example, people don’t criticise Elton John for having Bernie Taupin write his lyrics. The case of lyrical content, like most of the areas we’ll explore, is something each artist must reconcile for themselves.

Creating your AI Vocals

There are a number of ways to create vocals using AI platforms such as Udio or Suno. Typically, you’ll provide a backing track (unless the AI is generating that too) along with the lyrics. You can choose to generate the entire vocal in one go or break it into sections.

Whichever method you choose, one important thing to keep in mind is that current AI technology can be difficult to direct with precision. It’s great at generating creative ideas and inspiration, but if you have a very specific sound or style in mind, AI rarely nails it on the first try. Thoughtful prompting and fine-tuning of filters and controls can help. And when you get something that is close but not quite right there are tools such as infill and remix that can help you to get closer to your creative vision. Despite all of this, compared to working with a session vocalist, your influence is far more limited, unless you’re using a dedicated vocal replacement tool (more on that shortly).

Acapella issues

One of the more frustrating challenges is that AI tools typically don’t like generating acapella vocals. This is particularly problematic when you need the vocal to be in the same key as your backing track. As a result, you’re often left with no choice but to use stem separation to isolate the vocal track. While many AI platforms offer this feature (usually as a paid add-on) you may get better results with third-party tools like Ultimate Vocal Remover.

That said, even the best separation tools can introduce artefacts that affect the overall sound quality. And that leads us neatly to the next point…

Audio Quality

This is arguably one of the biggest factors in determining whether an AI vocal is usable in a final track. While sound quality is steadily improving, it’s still not quite on par with a professionally recorded vocal, in terms of both Sonic clarity and emotional delivery. Many trained ears can spot an AI-generated vocal for these very reasons.

Some vocal styles fare better than others, and features like “infill” can help polish AI vocals to sound more natural. But if you have not managed to create a usable acapella and had to separate the vocal from a full mix, there will almost always be a dip in quality. If this is a deal breaker for you and you find yourself consistently hitting a wall in terms of sound or control, there’s another path worth exploring…

Hybrid AI solutions

Perhaps the best balance between control and quality comes from voice replacement tools like Audimee or VoiceSwap. These platforms let you record your own guide vocal, then swap your voice out for one from their catalog of available vocalists. This method offers more influence over phrasing and delivery, and arguably raises fewer ethical red flags since you’re still deeply involved in the creative process. In fact, I would argue that it’s not dissimilar to hiring a session singer for your track.

The only real limitation is that you’re restricted to the voices provided, although some platforms allow you to train the AI on a specific vocalist of your choosing. You just need to feed it 10-20 mins of dry vocal to train it on. I’d argue this approach represents the ideal combination of AI assistance and human artistry.

Check out the video below to see how this works using Audimee.

AI Guide Vocal

Finally, there’s the option of using AI vocals purely as a guide or source of inspiration—essentially treating AI as a co-writer. Once you’ve created a vocal that captures the mood or structure you want, you can hand it over to a real vocalist to bring it to life. If you don’t know any singers personally, there are plenty of online platforms like Fiverr, Airgigs, or SoundBetter, where you can find talented vocalists ready to collaborate for a fee.

This is an ideal solution for producers or songwriters who struggle with lyrics or melodies but feel uneasy about using AI as the final performer.

Is AI any different to Sampling?

When discussing the ethical implications of using AI vocals, it might be helpful to view the issue through the same lens as sampling. Sampling vocals has long been accepted as a creative and legitimate technique, especially in genres like EDM, where it’s become a core part of the production process. So, is there really a fundamental difference between an AI-generated vocal and a sampled one?

The most obvious distinction is that a sampled vocal was originally performed by a person. But from a creative standpoint, especially from the perspective of a producer crafting a track, the workflow for integrating a sample versus an AI-generated vocal feels remarkably similar. In fact, one could argue that using an AI vocal actually involves more creative input and control. You have to come up with a prompt, lyrics, perhaps provide a guide or reference, and often need to tweak and refine the vocal to suit your track. With a traditional sample, you’re confined to the limits of the original recording.

In many ways, AI vocals can be seen as an evolution of sampling. Both samples and AI vocals require you to make the vocal work in your production opposed to using a vocalist who’s job it would be to enhance your musical backing. AI simply offers an endless array of possibilities, vocal textures and styles to choose from and shape to your needs. You just need to accept that these have been generated using chips and code rather than lungs and a microphone.

In fact, if you take it a step further, you could argue that AI is simply the most advanced form of sampling ever created. At its core, AI models are trained on massive datasets pulled from across the internet*. The voices they generate aren’t synthesised from scratch but instead composites. Intricate blends of thousands of real vocal recordings.

This perspective blurs the line between what we typically consider a “sample” and what we now call an AI-generated vocal. When you look at the underlying mechanics, the gap between the two narrows considerably.

* Both Suno and Udio have explicitly admitted in their legal defenses that their AI models were trained on copyrighted music. Suno stated that its “training data includes essentially all music files of reasonable quality that are accessible on the open Internet,” while Udio admitted its AI “listened to and learned from a large collection of recorded music” from the internet.

Your Audience – Will they care?

Now we come to what, for many musicians, is the deciding factor: Will my listeners actually care if the vocals are AI-generated? In fact, will they even notice?

In most cases, the answer is probably not, especially if you’ve taken the time to craft a well-produced and convincing vocal. To the average listener, particularly those streaming music casually, the origin of the voice may not even cross their mind. If the vocal sounds good and fits the track, they’re likely to accept it without question.

The only potential complication arises during the marketing and promotional phase. Your audience might expect to see a featured vocalist credited, or a desire to connect with the artist behind the voice. In these cases, the absence of a named collaborator can raise questions. Nothing is stopping you from giving your AI vocalist an alias or persona, much like a featured artist. But ultimately, it comes down to your own level of comfort: Are you happy to be transparent about using AI, or would you prefer to let the music speak for itself and avoid drawing attention to it?

That said, audience perception can be a double-edged sword. While many listeners may not care, or may even be intrigued by the use of AI, others could feel differently, particularly those who place a high value on authenticity and human expression in music.

There is a growing cultural awareness around AI content, and in some circles, a degree of scepticism or backlash. Some fans may feel deceived if they discover that a powerful or emotive vocal performance wasn’t delivered by a real person, especially if that fact wasn’t disclosed up front. And the last thing most music makers want are negative comments or upset fans, especially if you have spent years building a fan base.

In short, while AI vocals might not be a big deal for most casual listeners, there is a vocal minority that could take issue with the use of AI vocals, particularly if it’s perceived as disingenuous or lacking transparency. As with so much in this space, it’s all about context, communication, and the kind of relationship you want to build with your audience.

Distributing Your AI Work

So, after much thought and experimentation, you’ve decided to release your AI-vocalled track into the world. But what, if any, are the implications of distributing music created, at least in part, by artificial intelligence?

At present, most major digital distributors, including us here at RouteNote, are fully open to distributing AI-generated music to platforms like Spotify, Apple Music, and others. The main limitation lies in sending content to stores that rely on Content ID systems, such as YouTube and TikTok. These platforms have tighter restrictions in place to prevent copyright confusion or misuse. That said, you’re entirely free to assign your AI vocalist a name and even create a visual identity for them, should you wish to market them as a featured artist.

However, a word of caution: this is a rapidly evolving space. As of now, both Udio and Suno, two of the biggest players in AI music generation, are facing lawsuits from a coalition of music industry giants. Depending on how this test case unfolds, we may see significant changes in the legal and distribution landscape.

And in other developments, streaming service Deezer has already developed technology designed to identify and de-prioritise AI-generated content in search results. And there’s growing speculation that AI music may eventually require digital watermarking, so it can be easily identified by listeners and platforms alike.

In that sense, we might currently be living in a kind of “golden era” for AI music distribution, where the tools are advanced, the regulations are relatively relaxed, and the opportunities are wide open. If you’re thinking of experimenting, now may be the time to take advantage of that freedom.

Of course, beyond the artistic or legal considerations, there’s also a very real financial incentive. Hiring session vocalists, renting studio time, and negotiating publishing and royalty splits can be costly and time-consuming. With an AI singer or rapper, those expenses and complications largely disappear. You retain full ownership of your track, meaning you can work faster and more independently. For artists seeking to build a prolific catalogue, AI offers an undeniably efficient route.

Conclusion

In this piece I’ve discussed many aspects of using AI vocals within a composition, yet I’ve likely only scratched the surface. From the technical and practical, to the creative and ethical, this is major shift in the way music is created and viewed. While the pros and cons are numerous and often nuanced, the ultimate decision to embrace AI in your music is deeply personal. You can weigh up the arguments, analyse the implications, and consider your audience’s expectations, but in the end, it comes down to how you feel about it. At its heart, your music should always reflect you.

You are clearly doing nothing wrong by harnessing the powers of AI to assist you with your vocal parts. On the contrary, when approached thoughtfully, it can greatly elevate your work. AI opens doors that were once locked for independent creators, offering capabilities that were previously reserved for those with substantial budgets or industry connections. A great example is using tools like Audimee to transform your vocal demo recording into something that sounds fully professional.

As well as the artistic and philosophical questions, there are practical realities to consider. Hiring musicians is expensive. Dealing with splits, contracts, and schedules can slow down your momentum. AI removes many of these obstacles, allowing for greater output and creative freedom. For many artists, that’s a game-changer.

If I were to summarise, there’s a compelling case for using AI vocals if your goal is to maximise short-term productivity, reduce costs, and get music out to listeners quickly. It’s a fast, efficient way to create without the traditional barriers.

But if your artistic vision is deeply rooted in traditional creative processes and the authenticity of human performance, then AI may feel like a compromise too far for both you and your audience.

Either way, this is a conversation that’s only just beginning and it will be extremely interesting to see how things develop.

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