Thing 12

AI music generation

Last reviewed: March 2026 45–60 minutes

Of all the Things in this programme, this one might produce the biggest double-take. You type a short description (a genre, a mood, maybe some lyrics) and AI gives you back a complete song. Vocals, instruments, structure, the lot. Not a rough loop or a basic sketch. A finished-sounding track with verses, a chorus, and a bridge, performed by AI-generated singers who sound convincingly human.

If the image generators in Thing 9 surprised you, this is that experience but for your ears.

AI music generation has moved fast. Two years ago, the outputs were interesting curiosities, clearly synthetic and often incoherent, though occasionally entertaining. Today, the leading tools produce music that is, on a casual listen, hard to tell apart from human-made recordings. The melodies make sense. The lyrics (when AI-generated) mostly hold together. The production quality, the mixing and layering and the way instruments sit together, is often well beyond what you'd expect from typing a sentence into a text box.

This is exciting and unsettling in roughly equal measure, depending on who you ask. If you need background music for a presentation, a podcast intro, or a training video, these tools solve a real problem that used to involve either paying for stock music or learning to produce your own. For professional musicians and the wider music industry, the implications are more complicated, and the legal and ethical questions are still being worked out in real time.

This Thing gives you hands-on experience with the leading music generation tools. You'll create your own songs, try different styles, and form your own view on what this technology does well and where it falls short.


How AI music generation works

An abstract illustration representing AI music generation, with visual elements suggesting sound waves, musical notes, and digital creation
AI music generators can produce complete, polished-sounding tracks from a short text description, often in under two minutes.

The basic process is simple. You write a text prompt describing the kind of music you want (the genre, the mood, the tempo, perhaps a theme or some lyrics) and the AI generates a complete audio track. Generation typically takes between 30 seconds and a couple of minutes, and the result is a fully produced piece of music you can listen to, download, and share.

Under the surface, these tools use large neural networks trained on vast amounts of existing music. They've learned patterns: how a pop chorus tends to build, what chord progressions sound natural in jazz, how a drum pattern in reggae differs from electronic dance music, how vocal melodies relate to the underlying harmony. When you give the AI a prompt, it draws on all of those learned patterns to generate something new that fits your description.

This is worth pausing on, because it connects to a bigger question. These models were trained on existing human-made music, millions of songs. The legal and ethical status of that training process is actively contested, and we'll come back to it later in this Thing. For now, the important point is that AI music generation isn't pulling from a library of pre-made clips. It generates new audio from scratch, guided by patterns learned during training.


The current tool landscape

You've got several options for generating music with AI. Here's what's available and worth trying.


AI music generation is at the centre of a major copyright debate, and it would be wrong to explore these tools without addressing it.

The models behind Suno, Udio, and similar tools were trained on enormous quantities of existing music. The music industry's position, backed by major record labels and many artists, is that this training constituted copyright infringement on a massive scale. In 2024, major record labels filed lawsuits against both Suno and Udio, alleging wilful copyright infringement.

The legal picture has shifted since then. Warner Music Group settled its lawsuit with Suno in early 2026 and formed a partnership involving licensed models and structured download restrictions. Universal Music Group reached a similar arrangement with Udio. These settlements suggest the industry is moving towards a licensing model rather than outright opposition, a pattern we've seen before with technologies that initially disrupted established creative industries.

But the ethical questions aren't fully resolved by licensing deals between corporations. Many individual musicians and smaller artists feel that their work was used without consent to train systems that now compete with them. The debate about whether AI-generated music devalues human creativity is real and ongoing, and reasonable people disagree.

For your use during this activity, the practical situation is straightforward: songs generated on free tiers are for personal, non-commercial use. You can create them, listen to them, share them with friends, and submit them as evidence for your badge. You shouldn't use them in any commercial context; that requires a paid plan with appropriate licensing. And it's worth being transparent about AI generation if you share your creations publicly; passing off AI-generated music as your own human performance would be misleading regardless of the legal position.


Resources to explore

Suno

The most accessible AI music generator with the most generous free tier (50 credits per day, roughly 10 songs). Web-based, no download required. Best starting point for this activity.

Open tool
Udio

Higher-fidelity output with more control, but a more limited free tier (10 daily credits plus 100 monthly). Worth trying as a comparison if you have time.

Open tool
AIVA

Specialises in orchestral and cinematic instrumental music. Free tier available. Good for film scores and classical-style compositions.

Open tool
Beatoven.ai

Background music for video and podcasts. Fairly Trained certified (models trained on licensed music). Free tier available.

Open tool
AI music generator comparison (Superprompt)

A regularly updated comparison of the major AI music generators, useful for understanding the current state of the field.

Read article

Activity: create your own AI-generated music

45–60 minutes A free Suno account (+ optionally Udio)

You're going to create two songs using AI music generation: one where the AI handles everything, and one where you write the lyrics yourself. The comparison between the two will tell you a lot about how these tools work and where human input makes a difference.

  1. Create your first song (AI-generated lyrics). Go to suno.com, create a free account, and use the Create feature. Enter a style description without providing your own lyrics. Be specific about the genre and mood; the more detail you give, the more interesting the results tend to be. Suno will generate two versions. Listen to both, paying attention not just to the music but to the lyrics. Save or download whichever version you prefer, and note down your exact prompt.
  2. Write your own lyrics and create a second song. Switch to custom mode. Write a short set of lyrics (a verse and a chorus is plenty) about something personal to you: a place you love, a hobby, a memory, a pet, a favourite season. Use tags like [Verse], [Chorus], [Bridge], and [Outro] to help the AI understand your song structure. In the style description, try something different from your first song. Generate, listen, and save your preferred version.
  3. Compare across tools (optional but recommended). Take the lyrics you wrote in step 2 and enter them into Udio with a similar style description. This gives you a direct comparison of how two different AI tools interpret the same words and brief. The differences can be revealing, not just in sound quality, but in the musical choices each tool makes about melody, tempo, and arrangement.
  4. Write a short reflection. In 250 to 350 words, cover what surprised you, how the AI-written lyrics compared to your own, what the tools did well and where they fell short, practical uses you can imagine, and your thoughts on the copyright questions.
Privacy reminder: use personal examples, hobbies, or fictional scenarios for your lyrics. Never use actual work materials, confidential content, or anything that could identify your employer. When you upload text to Suno or Udio, it's processed on their servers.

Your output

A document or blog post containing:

  • Both audio files (or links to them on Suno/Udio)
  • The prompts and lyrics you used for each song
  • Your written reflection (250 to 350 words)

Why this matters

AI music generation is one of those capabilities that makes the breadth of current AI feel real in a way that text generation sometimes doesn't. When you type words and get back a song, complete with a human-sounding voice singing over professionally arranged instruments, it shows something about what neural networks can learn that's hard to appreciate in the abstract.

But beyond the wow factor, there are practical applications. Background music for presentations, podcasts, and video content has traditionally been either expensive (commissioning original music or licensing premium stock tracks) or generic (using free stock music that everyone recognises). AI music generation offers a middle path: custom music, tailored to your specific needs, at zero cost on the free tier.

There's also something in the creative experience itself. Even if you've never considered yourself musical, the process of describing a song (thinking about genre, mood, tempo, and what you want the lyrics to say) is a form of creative direction. You're making aesthetic choices, evaluating results, and iterating towards something that satisfies you. The AI handles the technical execution, but the creative vision is yours.

That said, the technology raises questions that don't have easy answers. What happens to human musicians when anyone can generate a passable song in 30 seconds? How do we value musical skill and artistry in a world where the sound of professional music can be produced without any of the underlying craft? These aren't hypothetical concerns. They're active debates in the music industry right now, and forming your own informed view is part of being AI literate.


Claim your Open Badge

Submit both audio files (or links to them), the prompts and lyrics you used, and your written reflection as evidence for your Thing 12 badge via cred.scot.

Thing 12: AI music generation open badge
Thing 12: AI music generation

Submit your audio files or links, prompts, lyrics, and reflection as evidence to claim this badge via cred.scot.

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What's next

You've now worked with AI across text, images, speech, audio editing, and music. That's a pretty comprehensive tour of what AI can create. In Thing 13, we turn to the last major creative format: video. AI video generation is the newest of these capabilities, and it's the one where the gap between what's impressive and what's actually useful is most interesting to explore. You'll generate your own short video clips and see both how far the technology has come and where the limitations are still very visible.