AI-Generated Music: 13 AI Music Generators to Try

To speed up and simplify music production, many artists now employ artificial intelligence to create AI-generated music. In the past few years, AI has matured as a compositional tool, allowing musicians to discover new sounds derived from AI algorithms and software. As a result, AI-generated music has become mainstream and is adding another dimension to the music industry.  

What is AI-Generated Music

AI-generated music refers to music that is solely created or aided by artificial intelligence. To generate new music, these tools use machine learning algorithms trained on extensive datasets that analyze musical elements such as lyrics, chords, harmony and rhythm. Some AI music generators specialize in certain aspects of the musical process, like lyric writing or editing, but others can automate the entire process. 

How Does AI-Generated Music Work? 

AI-generated music works by training AI algorithms on large quantities of music data (MIDI files, audio recordings, sheet music etc.) to learn patterns in melody, rhythm, harmony and style. Once trained, these algorithms can be used to generate new music by predicting the next logical sequence of notes, chords or even lyrics based on prompts asking for specific genres, themes and instrumentation.   

Some of the most advanced AI music generators can create entire, multi-instrument compositions that sound stylistically coherent. The output can then be refined by users to more closely fit what they want. Artists have started to embrace this technology and its capabilities, leading to an increasing demand for AI music generators.

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13 AI Music Generators and Tools 

While advanced, AI-composed music captures much of the attention these days, AI has been quietly reshaping the music industry for years. It’s now regularly used to create ambient music for relaxation and royalty-free tracks for content creators, as well as to automate the mixing and mastering process.

Here’s a closer look at some notable players.

Soundraw

Soundraw is a royalty-free music platform that uses AI to tailor songs to the needs of creators. Selecting and molding factors like mood, genre, song length and chorus positioning, creatives can develop personalized musical tracks that align with video sequences. Soundraw users also avoid some of the copyright issues that arise on other platforms, making it even easier to create and distribute music.

• Notable features: Royalty-free music, options for customizing songs to fit video sequences
• Cost: Plans start at $11.04 per month

Aiva Technologies

Aiva Technologies is the creator of a soundtrack-producing artificial intelligence music engine. The platform enables composers and creators to make originals, or upload their work to create new variations. Depending on the plan chosen, creators can also forgo the worry of licensing because the platform offers full usage rights. Rather than replacing musicians, Aiva wants to enhance the collaboration between artificial and organic creativity.

• Notable features: Ability to quickly produce variations of a musical work, full usage rights
• Cost: Free plan with additional plan options

Beatoven.ai

Beatoven.ai allows creatives to develop customized background music using text prompts. Users can fine-tune prompts to edit the genre, instrumentals and emotional elements of a track. When users download tracks, they also receive licenses via email to maintain full ownership over their content. Beatoven.ai claims to be a “fairly trained certified AI provider” and compensates musicians who let the company use their music to train its AI models.

• Notable features: Prompt editing for personalized music, licenses emailed after each download
• Cost: Free plan with additional tiers for increased usage

Soundful

Soundful is an AI music generator that produces background music for social media, video games, digital ads and other formats. Users choose from a broad range of music templates and moods, adapting tracks to their specific needs. Larger organizations can select Soundful’s enterprise plan to establish licensing terms and ways for monetizing templates, ensuring their creative endeavors remain profitable.

• Notable features: Royalty-free music, broad selection of moods and templates, licensing and monetization plans available
• Cost: Free plan, with option to upgrade to premium, pro or a business tier plan

Suno

Suno was made by a team of musicians and AI experts who hail from companies like Meta and TikTok. The tool has made a habit out of generating songs that have gone viral, thanks to its ability to produce instrumentals, vocals and lyrics from a single text prompt. Users can play around with prompts to craft a song about a particular topic and in a specific genre.

• Notable features: Instrumentals and vocals generated, ability to edit genre and topic 
• Cost: Free plan with additional plan options

Udio

Developed by former Google Deepmind researchers, Udio is an AI music generator that lets users create unique tracks with prompts and tags. After writing a prompt, a user can make further tweaks by adding tags that alter elements like the genre and emotional tone of the song. For each submission, Udio produces two versions and features a prompt box that doesn’t reset, so users can continue to adjust and build on previous prompts.

• Notable features: Tags to edit specific song elements, a prompt box that doesn’t reset 
• Cost: Free plan with additional plan options

Meta’s AudioCraft

With the release of its text-to-audio tool AudioCraft, Meta is taking generative AI in music to another level. AudioCraft is trained on licensed music and public sound effects, so users can quickly add tunes or sounds to a video with text prompts. Leveraging a neural network model called EnCodec, AudioCraft delivers high-quality sounds on a consistent basis and compresses files for faster sharing.

• Notable features: Trained on licensed music and public sound effects, text-to-audio abilities
• Cost: Free and open source.

iZotope’s AI Assistants 

iZotope emerged as a pioneer in AI-assisted music production back in 2016, with the release of Track Assistant. The mixing feature uses AI to generate custom effects settings based on the sonic palette of a given track. Today, it hosts a full suite of assistants that tailor starting-point suggestions for vocal mixes, reverb application and mastering. 

• Notable features: Collection of AI music assistants 
• Cost: Products range from $29 to $2,499

Brain.fm

Brain.fm is a web and mobile application that provides atmospheric music to encourage rest, relaxation and focus. Created by a team of engineers, entrepreneurs, musicians and scientists, the company’s music engine uses AI to arrange musical compositions and add acoustic features that enable listeners to enter certain mental states. In a pilot study led by a Brain.fm academic collaborator, the application showed higher rates of sustained attention and less mind-wandering, which led to a boost in productivity.

• Notable features: Music that caters to certain mental states, product backed by neuroscience and psychology research
• Cost: $9.99 per month or $69.99 per year

LANDR

LANDR is a creative platform that enables musicians to create, master and sell their music. The company’s mastering software uses AI and machine learning to analyze track styles and enhance parameters based on its reference library of genres and styles. Beyond AI-enhanced mastering, LANDR enables musicians to create quality music and distribute it on major streaming platforms while avoiding the costs associated with a professional studio.

• Notable features: Library of music samples, independent music distribution
• Cost: All-in-one subscription for $8.25 per month, with additional plan options

Output’s Arcade Software and Kit Generator 

Output’s signature software Arcade lets users build and manipulate loops into full-length tracks. Users can access audio-preset plug-ins, then adjust sonic details like delay, chorus, echo and fidelity before minting a track. The software also features an AI-powered tool called Kit Generator, which lets users generate a full kit, or collection of sounds, from discrete audio samples. Output’s technology has supported music by artists like Drake and Rihanna and the scores of Black Panther and Game of Thrones.

• Notable features: Track-building software, AI tool for creating collections of sounds
• Cost: Free trial available for a limited time, prices may change

OpenAI’s Jukebox

Jukebox is OpenAI’s music generation platform. Trained on more than one million songs, the tool can generate harmonies and vocals directly in raw audio across different genres and styles. Despite providing free access to the source, using Jukebox requires some technical know-how. Users can clone a Jukebox repository on GitHub or other version control platforms or create a dedicated computational environment to run the system. 

• Notable features: Instrumental and vocal generation, but requires some development knowledge to use. 
• Pricing: Free and open-source if used for noncommercial purposes.  

Google’s Magenta

Magenta is a Google open source project that explores new ways to use AI in the creative fields. One of its main features is generating music with AI. Available as a plug-in to Ableton Live, it is a staple program in the music industry. Magenta Studio can assist with remixes and extend instrumental tracks. Additionally, it can generate melodies and drum patterns based on specific input parameters, like style and tempo. 

• Notable features: Google-made plug-in for generating entire songs and instrumental snippets.
• Pricing: Free plug-in for Ableton Live.

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Impact of AI on Music

Much remains to be seen about how musicians and companies respond to the spread of AI. But one thing all parties can agree on is that AI-generated music has forever changed the industry — in both promising and problematic ways.   

Leads to New and Different Forms

The rise of AI-generated music has led to companies and individuals offering unique takes on renowned songs and artists. 

For example, the piece “Drowned in the Sun” is the product of Google’s Magenta and a neural network inputting data from dozens of original Nirvana recordings and crafting lyrics for the singer of a Nirvana tribute band to perform. Although the audio is a bit muddy, AI has impressed even those in academia with its abilities. 

“It’s able to coherently generate a multi-instrumental piece of music with metrical structure, musical phrases, progressions that make sense, all while doing it at a granular audio rate,” said Oliver Bown, author of Beyond the Creative Species. 

Offers Artists More Creative Options

Writer Robin Sloan and musician Jesse Solomon Clark created an album using OpenAI’s Jukebox, which, like Magenta, can predictively continue a musical snippet. Holly Herndon’s 2019 album, Proto, described by Vulture as the “world’s first mainstream album made with AI,” incorporated a neural network that generated audio variations based on hours of vocal samples. 

“[Herndon is] working with AI as this sort of extended choir,” Bown said.

Inspired by these applications, artists and technologists hope for an even greater step forward. One possibility for AI in music could be models that respond to artists in real-time performances. Rather than edit down the interesting bits offered by a model, humans could bounce off musical ideas with AI, just like a bass player and drummer in a rhythm section.

“It’s a long shot, but it could have a huge impact,” said Roger Dannenberg, a professor of computer science, art and music at Carnegie Mellon University.  

Hinders Originality 

AI has been able to replicate the sonic qualities of artists, but the innovation that defined famous musicians has remained elusive. The effect of AI producing songs that sound similar to previous works is a lack of variety and quality in AI-generated music pieces.  

“Nirvana was famous for doing things in a different way than had come before,” said Jason Palamara, assistant professor of music and arts technology at Indiana University-Purdue University Indianapolis. “But machine learning is really good at doing things the way that humans have already done them before.”

Hope persists for a not-too-distant future where AI moves beyond mimicry and riffs with human musicians, but rudimentary versions of this technology are flawed by a lack of sophisticated real-time musical interfaces. This means simple details for humans (like synchronizing and beat tracking) are a major challenge for models, Dannenberg said. 

The data limitations are pronounced, too. The “Drowned in the Sun” Nirvana track stems from hours of rich MIDI data, but a live performance generates scant audio in comparison. So, for live-music generation, “you have to kind of dumb it down,” Palamara said. 

Sparks Copyright Conflicts 

Similar to the arenas of AI writing and AI-generated art, the legal framework for AI in music remains murky. Those who produce AI-generated music may not be able to copyright their music while musicians whose songs were analyzed may not know when it’s appropriate to sue someone for copying their lyrics or any other musical elements too closely. 

Debates around the authenticity and accuracy of AI music and who owns what have culminated in a legal battle. A group of record labels has sued companies on the grounds of copyright infringement, putting the future of the entire AI industry in limbo for the time being.

Raises Concerns Over Job Losses

Job losses due to automation are a major worry when it comes to AI, and music is no exception to this trend. AI that produces beats, rhythms and melodies may take over the roles of drummers, bassists and other musicians. 

Of course, the ultimate goal is to have artificial intelligence supplement musicians, serving as collaborators for adding fresh sounds and techniques to the creative process. However, AI causing job losses in the music industry is a very real possibility that artists, technologists and other parties need to weigh when relying on AI music generators.

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