What Are AI Music Generators (and How Do They Work)?
AI music generators are software tools that use artificial intelligence to create music based on user inputs or preset parameters. In simple terms, an AI music generator "listens" to patterns in a large collection of existing music and learns to create new compositions from those patterns.
The AI doesn't copy entire songs; instead, it studies characteristics like melodies, rhythms, chord progressions, and instrumentation across many genres. When you give the AI a prompt – say "a relaxing acoustic guitar tune" – it uses what it learned to compose a fresh piece of music that matches that description.
Think of it as a musical co-pilot: you provide a bit of direction, and the AI comes up with a draft melody, harmony, and beat. Behind the scenes, different platforms use different techniques. Some use deep learning models (like neural networks) that have been trained on audio waveforms or MIDI files of countless songs. These models might output a raw audio track or a musical score.
Others use algorithmic recombination – for example, Mubert combines short musical samples from a library to generate endless streams of music. But regardless of approach, the goal is the same: generate original music in a chosen style without human composers playing each note.
Importantly, the AI can also handle arrangements and instrumentation. It might decide the song structure (intro, verse, chorus), pick which instruments play when, and even synthesize the sound of those instruments. Some advanced systems can generate lyrics and vocals as well – more on that shortly when we discuss Suno and others.
In layman's terms, using an AI music generator is a bit like telling a very smart robot band what kind of song you want. You give it some guidance (a mood, a genre, maybe a reference track or a simple melody), and it jams something out for you. The results can range from simple background beats to surprisingly rich and professional-sounding songs. And because it's AI, it can do this in seconds or minutes, much faster than a human might compose a piece from scratch.
How Do You Use Online AI Music Platforms?
One great thing about today's AI music tools is that they're designed for ease of use. You don't need to know music theory or have production skills to get started. Most platforms have a user-friendly interface that guides you through the creation process.
Selecting a Style or Mood
Many AI music generators let you choose a genre (e.g. hip-hop, EDM, classical) or a mood (e.g. upbeat, melancholic, suspenseful). For instance, on Soundraw you can pick from a list of moods or themes, and the AI will instantly generate a set of tracks to match. You might specify "energetic, happy pop" and get a dozen song previews tailored to that vibe.
Entering Text Prompts
Newer tools use text-based prompts (similar to how you'd talk to ChatGPT). You describe the music you want in natural language. For example, Suno allows you to input a brief description or even custom lyrics – "an 80s-style synthwave track about the night sky" – and it will produce a song with that feel (even including AI-sung vocals if requested). This is incredibly intuitive: you tell the AI what to "hear" in your head, and it does its best to make it real.
Choosing Instruments/Settings
Some platforms provide knobs and sliders to fine-tune the result. You might adjust the tempo (speed), the key (musical scale), or instrumentation. AIVA, for example, lets users pick a preset style (from over 250 available) and adjust things like the composition length, key signature, and even edit the notes after generation.
In Soundraw's editor, you can specify the length of the song and which instruments or sections to include, then tweak the generated music by regenerating certain parts or changing chords. This level of control means the user isn't stuck with whatever the AI gives on the first try – you can iterate and refine.
Uploading References or Humming
A few tools allow more creative inputs. Some (like Mubert Studio) let human musicians upload samples that the AI will remix. Others allow you to hum a tune or sing a rough melody, which the AI can then build an accompaniment around. For instance, Suno has demonstrated a feature where you hum a tune and it transforms it into a full song (turning your hummed melody into different instruments and adding harmony).
Real-Time Generation and Playlists
Platforms like Mubert offer continuous music generation. Instead of making one fixed track, you can have an endless stream or adaptive soundtrack. You might choose a mood station (say, "Lo-fi Chill"), and the AI will improvise an infinite background music stream that evolves but stays within that vibe. Users can often skip or like tracks to influence the stream.
Downloading and Integrating
Once a piece is generated and you're happy with it, you can usually download it in common audio formats (MP3, WAV). Many tools also let you download stems or MIDI files – stems are the individual instrument tracks (drums, bass, vocals separated), which is great if you want to mix the music further in your own editing software.
Overall, using these platforms feels a bit like using a stock music library combined with a virtual composer at your command. The interface is often visual and simple – big "Generate" buttons, dropdowns for genres, and play/pause controls to preview the music.
Real Use Cases for AI-Generated Music
Who is actually using AI-generated music, and for what? It turns out, AI music generators have a wide range of practical applications across different fields:
Content Creation (YouTube, Podcasts, Social Media)
This is one of the biggest use cases. Content creators often need background music – for intros, outros, or to set the mood in videos. Instead of scouring royalty-free libraries (or risking copyright issues by using commercial songs), creators can generate a custom track that fits perfectly.
For example, a YouTuber making a travel vlog to tropical beaches could ask an AI for a "chill upbeat tropical house track" as background music. Within minutes, they'll have a unique soundtrack with the exact length needed for their video. Podcasters use AI music for theme songs or transition stingers. Because the music is AI-generated and often royalty-free, they avoid licensing fees.
Game Development
Indie game developers, in particular, love AI music tools. Games often require loopable background tracks and multiple themes (battle music, calm village music, etc.). A tool like AIVA or Soundful can generate orchestral scores or 8-bit retro tunes on demand. Developers can iterate to get the right feel – for instance, making a dungeon theme more "dark and atmospheric" or a victory theme more triumphant.
Some AI music services (like Mubert and others) even offer APIs for games to generate music on the fly. Imagine a game that changes its music based on the player's situation using AI – intense music for boss fights, serene music for exploration – all generated in real time to avoid repetition.
Live Streaming and Virtual Events
Streamers on platforms like Twitch often run into the issue of music copyright. AI music generators allow them to create endless stream-safe background music. For example, a streamer can have a continuous lo-fi hip-hop beat playing that adapts to the mood of their stream. If they switch to a high-energy segment, they could seamlessly generate an uptempo track.
Film and Video Production
Beyond YouTube, even independent filmmakers are tapping AI for scoring. Need an emotional piano piece for a short film's climax? Or some tension-building underscore for a thriller scene? AI generators like AIVA have cinematic presets (modern thriller, romantic, etc.) that can produce these in a pinch.
While big studios still hire human composers, small studios or hobbyist filmmakers benefit from AI as a temp score or even the final music if it's good enough. It drastically cuts down cost and time, as multiple drafts can be generated and tested against the picture in hours, not weeks.
Music Prototyping and Inspiration
Interestingly, even musicians themselves use AI as a creative assistant. An artist might generate a melody or chord progression to overcome writer's block. AI can suggest novel combinations of styles – e.g. "try mixing jazz and EDM elements" – and produce a sample, which the human musician can then build upon.
Think of it as brainstorming with an AI collaborator. Some platforms allow uploading a draft melody and letting the AI continue it or harmonize it (Suno's song extension feature does this, analyzing and continuing an existing track in the same style). This is great for producers looking to experiment with variations on their musical ideas.
Ambient Music and Wellness
AI music generators are used for creating meditation music, relaxation soundscapes, or workout playlists tailored to certain tempos. Apps can generate personalized soundtracks – for example, an AI might compose calming music that syncs with your breathing for meditation, or high-BPM tracks that match your running pace on a treadmill.
Education and Experimentation
Educators have started to use AI music tools to teach concepts of music composition. Students who don't play instruments can still experiment with composing by instructing the AI and then analyzing the result. It's a fun way to learn about structure and genre – "What happens if I ask for the same melody in a jazz style vs a classical style?" – the AI can demonstrate instantly.
Comparing the Top AI Music Generator Tools
Let's take a closer look at some leading AI music generator platforms in 2025 and see how they stack up. We'll focus on four popular services – Suno, Mubert, AIVA, and Soundraw – each of which takes a slightly different approach to AI music.
Suno 🎵 (Text-to-Music with Vocals)
Suno is a newcomer that has quickly made waves. It's an AI music generator capable of creating full songs with vocals. In fact, Suno can generate lyrics and sing them using AI voices, alongside instrumental accompaniment. This sets it apart from many others that focus only on instrumental music.
Features: Suno's latest model (as of 2025) is quite advanced. It offers multi-language vocals, supporting singing in languages like English, French, Spanish, Chinese, and more. It also introduced a "Personas" feature – essentially profiles that learn your preferred style, so the AI can maintain consistency across different songs you make.
Strengths: Suno is great for creators who want a full song, vocals included, quickly. It's like having a virtual singer-songwriter on call. The audio quality is high and fairly "radio-ready" in terms of mixing and mastering polish. Suno's versatility with genres and its fast generation (often under 30 seconds for a song) make it a powerful tool for song prototyping.
Weaknesses: Despite its impressive vocal generation, Suno (like any AI) can sometimes produce generic or emotionally flat lyrics – they might rhyme and make sense, but may lack the poetic depth a human songwriter would craft. The vocals, while realistic, can occasionally sound a bit synthetic or overly autotuned in parts.
Mubert 🎶 (Generative Music via Samples and API)
Mubert takes a different approach. Rather than composing music note-by-note from scratch, Mubert generates music by intelligently stitching together snippets of sound from a huge database of human-made samples. It uses algorithms and AI to ensure these samples flow together musically.
Features: Mubert is known for offering various products: Mubert Render (a simple web interface where you can generate a track by choosing descriptors), Mubert Studio (which allows musicians to upload their samples and earn when those are used), and a robust Mubert API. Real-time generation is a selling point: Mubert can output an endless stream without repeating by continually mixing and transitioning between loops.
Strengths: Mubert's music tends to be excellent for background and utility purposes. Because it's based on real samples from musicians, the sound is high-quality and often more organically human. It shines in genres like electronic, ambient, lo-fi, and modern styles where loop-based construction is common.
Weaknesses: The flip side of Mubert's approach is limited melodic control. You can't ask Mubert to produce a specific melody or follow a storyline in lyrics – it doesn't do vocals or lyric generation. If you need a hummable tune or a dramatic composition with a clear beginning and end, Mubert might feel lacking.
AIVA 🎼 (AI Composition Assistant with Orchestral Flair)
AIVA (Artificial Intelligence Virtual Artist) is one of the veteran platforms in AI music. It's been around since mid-2010s and even made headlines for being the first AI to be recognized as a composer by a music rights society. AIVA specializes in composition – particularly in classical, cinematic, and symphonic music, though it can do modern genres too.
Features: AIVA comes with an extensive library of preset styles – over 250 styles as of 2025. These range from "Modern Cinematic" to "Jazz Ballad" to "Baroque" or "Pop Rock". Users can input a few parameters (desired length, tempo, mood) and then hit compose. Where AIVA shines is allowing user input to guide the composition: you can upload a reference audio or melody (MIDI file) to influence its style.
Strengths: AIVA's strength is quality and control. The compositions it generates, especially in classical or film score style, are often impressively coherent – complete with appropriate chord progressions, development, and endings. It's been used to create soundtracks for games and commercials that sound like a human composer wrote them in a traditional style.
Weaknesses: AIVA primarily creates instrumental music. There are no vocals or lyric generation. If you need a pop song with a catchy sung chorus, AIVA alone can't do that. Also, AIVA's interface and workflow are a bit more complex than, say, Soundraw or Boomy.
Soundraw 🎹 (Customizable Royalty-Free Music for Creators)
Soundraw is an AI music generator tailored for content creators who want quick, customizable tracks with no copyright hassles. It's often praised for its easy workflow and the ability to tweak the music to fit your project.
Features: Using Soundraw feels like a mix of automation and manual control. You start by selecting a general mood/genre (Soundraw has many, like "Happy EDM," "Cinematic Suspense," "Corporate Motivational," etc.). The AI then generates about 15 track options on the spot for you to preview. Each track comes with a structure – e.g., intro, verse, chorus, etc., which you can see in the interface.
Strengths: For YouTubers, video editors, and designers, Soundraw is a godsend for quickly generating soundtrack music. It requires zero musical skill – just choose and tweak. The fact that it gives multiple options fast is great; you're not stuck waiting for one result at a time.
Weaknesses: Soundraw's main limitation is that it's focused on instrumental music (like many others, no vocals/lyrics in outputs). The music it generates, while good for backgrounds, might not have the memorable melody or complexity that a dedicated composer might create for a stand-alone song.
Comparison Summary
- Suno: Best for complete songs with vocals
- Mubert: Best for continuous background music
- AIVA: Best for orchestral and cinematic compositions
- Soundraw: Best for customizable content creator music
Legal and Copyright Considerations of AI-Generated Music
One big question that arises with AI-generated music is: who owns the music, and is it legal to use it freely? This area is evolving quickly, and as of 2025 there are some key points to understand to stay on the safe side.
Ownership and Copyright
Traditionally, music is automatically copyrighted to its human composer. But what if an AI composes the music? In the United States (and many other jurisdictions), the law is leaning towards "no human authorship, no copyright." A landmark ruling in March 2025 by the U.S. Court of Appeals stated that works created entirely by AI with no human input cannot be copyrighted.
In other words, if an AI generates a song start to finish and you did nothing creative besides pressing a button, that output by itself isn't protected by traditional copyright – it would effectively be public domain, meaning anyone else could also use it freely. The rationale is that copyright is meant to protect human creativity, and if a piece has no human creator, there's no author to own it.
Licensing from Platforms
To avoid uncertainties, most AI music platforms address usage rights in their terms of service. Essentially, when you create a track using their AI, they grant you a license to use that track. For example, Soundraw and Soundful outright say all music you generate is yours to use royalty-free in perpetuity.
AIVA, as we saw, even grants you copyright ownership at the higher tier – meaning AIVA won't claim authorship, and you can register the work as yours. These licenses are crucial: they are the company's way of saying "we won't sue you or ask for royalties for using the music our AI generated, and we ensure the music isn't copied from someone else's protected material."
ElevenLabs & Licensed AI Music
A cutting-edge development in 2025 is companies like ElevenLabs entering AI music with a licensing-first approach. ElevenLabs, known for voice AI, launched an AI music generator called "Eleven Music" and made headlines by striking deals with music rights holders (like Merlin and Kobalt, which represent many popular artists).
This means they trained their AI on music with permission, and artists opted in (with revenue sharing). As a result, they can guarantee that the generated music is cleared for commercial use in a way competitors could not. ElevenLabs claims users can create a song with their AI and use it in film, TV, games, ads – worry-free – because they've addressed the copyright on the dataset side.
Bottom Line for Users
When using an AI music generator, always check the usage terms. In most cases, as long as you follow their guidelines, you can use the music in your projects without paying royalties or fearing takedowns. Many tools encourage attribution, which is a nice gesture even if not required.
New Trends in AI Music in 2025 (Integrating Voice and Beyond)
The year 2025 has brought some exciting new trends in the AI music generator space, pushing the boundaries of what these tools can do and how we use them.
AI Music Meets AI Voice (Singing and Narration)
Perhaps the biggest trend is the fusion of music generation with voice generation. Earlier AI music tools mostly stuck to instruments, but now we're seeing platforms that can also produce vocal tracks – and not just generic "oohs and ahhs," but full lyrics and singing. This technology connects closely with AI voice text-to-speech advancements that are revolutionizing audio content creation.
What's happening now is specialized voice AI companies like ElevenLabs entering the music arena and bringing their expertise in realistic voice synthesis. ElevenLabs' new Eleven Music tool not only generates the instrumental track from a text prompt, it can also generate vocals in multiple languages and styles to go with it.
This is a game-changer: imagine typing "Generate a punk rock song with male vocals, in Japanese." The AI can actually output a cranked-up punk instrumental and a voice shouting lyrics in Japanese, on beat. This was science fiction not long ago!
Licensed Datasets and Industry Collaboration
AI music generators in 2025 are moving towards legit licensed training data. Early AI models often used whatever music they could to learn from (which raised copyright questions). Now, companies realize for their tools to be used commercially by customers, they need to assure everyone that the AI isn't regurgitating someone's protected song.
The approach pioneered by ElevenLabs' Eleven Music – making deals with music rights organizations to access a catalog for training, and setting up opt-in and revenue share with artists – is likely to be followed by others. This trend means you might soon see AI music tools proudly stating things like "Trained on 10,000 hours of properly licensed music, including contributions from working musicians."
Personalized and Adaptive Music
Another trend is making AI music more personalized. This can mean two things. One, personalized to the user: training on your own music to make new tracks in your style. Two, personalized to the audience or context: AI music that adapts to you in real time.
By 2025, AI music could integrate with smart devices – e.g., a smartwatch detects you're running and triggers the AI to amp up the tempo and intensity of your playlist. For content creators, personalization might mean each viewer could theoretically get a slightly different soundtrack suited to their preferences.
Quality Jumps and Hybrid Creativity
The overall quality of AI-generated music keeps improving. Larger models, better training techniques, and more computing power mean more realistic instrument sounds and more coherent compositions. We're seeing AI handle complex genres better – jazz improvisation, progressive rock with changing time signatures, etc.
There's also a trend of hybrid usage: human artists incorporating AI in professional music production. For instance, a producer might generate a few AI ideas for a melody, pick one they like, modify it, and then record it with a real instrument. This mirrors what happened with AI image generation in design – it became another tool in the toolkit.
Integrations with Platforms and Workflows
AI music generators are increasingly integrating with existing software and platforms. For example, some offer plugins for Adobe Premiere or After Effects, so video editors can generate a soundtrack without leaving their editing software. Others might integrate with game engines like Unity/Unreal for dynamic game scoring.
API integrations are a huge trend – as we covered with Mubert and also ElevenLabs announcing API access for Eleven Music. This allows developers to bake AI music capabilities directly into creative apps. We're also seeing AI music in voice assistants and smart speakers.
Limitations and Challenges of AI-Generated Music
It's not all sunshine and catchy tunes in the world of AI music. Current AI music generators, for all their marvels, do come with limitations and challenges. Anyone diving in should have realistic expectations and be prepared to work around these issues:
Lack of Human "Soul" and Emotional Depth
As much as AI has learned to imitate musical styles, many listeners and creators feel there's an ineffable quality missing – the emotional expressiveness that comes from a human performer or composer pouring their life experience into a piece. AI-generated music can sometimes sound mechanical or emotionally shallow.
It might hit the right notes and harmony, but perhaps doesn't evoke goosebumps the way a heartfelt human performance might. AI compositions may "lack the emotional nuances and unique touch that human musicians bring", and might require a human to "breathe life" into them post-generation.
Generality and Originality Concerns
Many AI tools have a tendency to play it safe. They're trained on tons of existing music, so they often gravitate toward the mean of that data – producing music that is pleasant but sometimes generic. If everyone uses the same AI presets, there's a risk that many tracks end up sounding quite similar, leading to homogenization.
Already, you can often guess when a track comes from certain AI generators because they have a signature sound or progressions they favor. This challenge means creators should not rely on one tool for everything. One tip is to "try combining outputs from different AI systems, or layering unusual instrumentation or effects" to give the music a unique twist beyond the algorithm's default.
Technical Limitations
Depending on the platform, you might face limits on how long a piece the AI can generate in one go. Some systems cap at a few minutes and then you'd have to stitch pieces. Audio quality can also vary – a few generators might output at lower bitrates or sample rates on free tiers (sounding a bit muddy or compressed).
In AI vocals, you sometimes hear artifacts – strange pronunciations, warbling, or the voice lacking smooth transitions. These technical quirks are being ironed out with each model update, but they still pop up.
Learning Curve and Workflow Adjustments
While basic usage is easy, integrating AI tools into a professional workflow might require adaptation. For example, getting a perfect loop might involve trial and error with the AI outputs. Composers used to writing music note-by-note might struggle with the "randomness" of AI and lack of direct control.
On the flip side, non-musicians might sometimes find the range of choices (all the moods, settings) overwhelming – like having too many flavors at an ice cream shop. Some time is needed to learn how to phrase prompts effectively or how to tweak settings to get desired results.
Challenges with Lyrics and Vocals
AI lyrics, while grammatically okay, often lack depth, metaphor, or true storytelling. They might come off as cliché or nonspecific ("Tonight we fly in the sky, you and I" – that sort of generic pop lyric). So if you want meaningful words, you'll likely need to pen them yourself or heavily edit the AI's suggestion.
AI vocals, as mentioned, are impressive but can be hit or miss. They sometimes mispronounce unusual names or get the timing slightly off. And they can't really improvise or add human-like ad-libs unless explicitly generated.
Working with Limitations
Think of an AI composer like an apprentice: it can come up with drafts and play around, but a master's touch may be needed to refine those drafts into something truly special. Many pros treat AI output as a "first draft" – a starting point to then edit or produce further.
The Future of AI's Role in Music Creation
Looking ahead, the future of AI in music is poised to be incredibly dynamic. Here's a forward-looking take on where things are heading and what that means for musicians, creators, and listeners:
AI as a Ubiquitous Creative Partner
Just as synthesizers and computers became standard tools in studios, AI will likely be a normal part of music creation. The stigma (if any remains) around using AI will diminish. Future musicians might routinely start a composition by consulting their AI assistant for ideas – "Hey AI, give me four cool chord progressions in D minor" – and then build a song from there.
AI could even become part of music education: students might practice by having AI jam with them, or use AI to hear how a theory concept sounds in practice. Essentially, AI will be the ever-present "second pair of ears" in the room for composers and producers.
Completely New Genres and Forms
With AI's ability to blend styles and even invent sounds, we could see new genres of music emerging that are in part AI-crafted. For example, AI might mix throat singing with techno in a way humans haven't tried, birthing a fresh sound. Or generative music that evolves endlessly, giving rise to "living albums" that change each time you listen.
People might release interactive music experiences – not just a fixed recording, but an AI-driven app that produces a unique rendition of an album for each listener. This concept of "dynamic music releases" could be an artistic frontier.
Personal Soundtracks and AI DJs
Imagine a world where every person has an AI DJ that knows their taste and context. Your morning could start with an AI-curated song that it composed for you – maybe to gently energize you based on your sleep quality and schedule for the day. When you exercise, your AI generates the perfect workout mix in real-time, hitting those beats just when you need motivation.
This personal soundtrack idea extends to experiences: theme parks might have AI music that reacts to the crowd's mood; video games will certainly have more adaptive scores that respond to player actions via AI composition.
Collaboration Between Artists and AI
We'll likely see famous artists openly co-creating with AI. For instance, a pop producer might generate 100 variations of a hook with AI and pick the catchiest to be the cornerstone of a new hit. Or an artist might "license" their own style to an AI – e.g., a singer could allow an AI to use their vocal style, then fans or other musicians could generate new songs featuring that voice (with the artist's oversight and profit-sharing).
Quality and Realism Hitting New Highs
In the future, it may become genuinely difficult to distinguish AI music from human-made music – not just in sound quality but in emotional effect. With better modeling of expression and perhaps even AI being trained on performance nuances, we might get AI performances that convey sadness, joy, aggression, etc. convincingly.
AI might even analyze the emotional content of lyrics or the creator's stated intent and adjust the musical expression to match (playing a passage more "wistfully" for example, like a session musician would). In the ideal scenario, AI could amplify human emotional storytelling rather than mute it.
Conclusion: Embrace the New Era of Music Creation
The landscape of music creation in 2025 is one where AI-powered tools are playing a starring role. We've seen how accessible and versatile AI music generators like Suno, Mubert, AIVA, and Soundraw have become – empowering everyone from hobbyist content creators to professional composers to experiment with sounds and compositions that might have been out of reach otherwise.
These tools can drastically cut down production time, reduce costs, and even inspire entirely new creative directions. At the same time, we've acknowledged the limitations and learned the importance of adding that human touch to truly make a track shine.
The exciting part is you don't have to take our word for it – you can try it yourself. The best way to understand the power and potential of AI music generators is to experiment hands-on. Many of the platforms we discussed have free trials or free tiers, so you can get a feel for making music with AI in just minutes.
Have a YouTube video that needs background music? Go generate a few tracks and see which one elevates your content. Have a poem or lyrics you wrote years ago? Plug them into a tool like Suno or ElevenLabs' music generator and listen as it blossoms into a full song. Not a musician? All the more reason – you'll be amazed at how you can compose something listenable without any formal training.
We also encourage you to explore ElevenLabs' suite of AI tools as part of your creative journey. ElevenLabs has been a leader in realistic AI voice generation – think of the possibilities when you combine that with AI voice text-to-speech technology. You could create a narration for your video with a lifelike AI voice and generate the background score all within the same ecosystem.
With the new Eleven Music tool, you can dive into generating custom music that's cleared for commercial use, and even add vocals or voiceovers effortlessly. In this rapidly evolving field, ElevenLabs is pushing the envelope, and their tools are user-friendly for newcomers and powerful for seasoned creators alike.
Now is the time to get playful with AI in your own projects. Whether you're a content creator looking to spice up your media, a game developer seeking dynamic audio, or an artist wanting to break through writer's block – give these AI music generators a spin. The barrier to entry has never been lower, and the creative rewards can be astonishing.
You might discover a spark of inspiration from an AI-generated melody, or find that perfect soundtrack you've been searching for, or simply have a lot of fun in the process. Your next soundtrack or hit song might just be a few clicks away.
So go ahead – embrace this new era of music creation. Fire up an AI music generator, try out ElevenLabs' voice and music tools, and let your imagination run wild. In the symphony of human and artificial creativity, you are the conductor – and the world is eager to hear what you'll create. Happy composing!