To make AI music, you pick a generator like Suno or Udio, describe the song you want in a text prompt, generate a track, then refine the prompt and edit the result until it works. The whole process can take minutes, but the difference between a throwaway clip and something usable comes down to how you prompt and how you finish the track. Here’s the full workflow.
Step 1: Choose your tool
Your choice depends on what you’re after. For full songs with vocals from a text prompt, Suno and Udio are the go-to options. For instrumental background music, Soundraw or Mubert. For editable composition, AIVA. For a free starting point inside a DAW, BandLab SongStarter. If you’re not sure, our roundup of the best AI music generators compares them by job.
Step 2: Write a clear prompt
The prompt is where most of the quality comes from. Describe genre, mood, tempo feel, instruments and vocal style. “Slow soulful R&B, female vocal, warm electric piano, late-night feel” gives the model far more to work with than “make a good song.” You can usually add your own lyrics too. For full song tools, learning how to make AI songs from text and how to write better Suno prompts will sharpen this step quickly.
Step 3: Generate and compare
Generate a track — most tools give you two versions per prompt. Listen to both. Don’t expect the first result to be perfect; treat each generation as a draft. If something is close but not right, note what you’d change before you tweak the prompt.
Step 4: Refine and iterate
Adjust one thing at a time. If the energy is wrong, change the mood words. If the vocal sits oddly, describe the vocal style differently. Many tools let you extend a section, regenerate part of a song, or keep a section you like and rebuild the rest. Iteration is the real skill in AI music — the people who get great results just generate more and prompt more precisely.
Step 5: Edit and finish like a real track
AI output is raw material. To make it feel like yours, bring it into a DAW and treat it properly:
- Trim and arrange — cut weak sections, tidy the intro and outro.
- Separate stems if you can — tools like Moises or Lalal.ai split a track into vocals and instruments so you can rebalance or replace parts. See the best AI stem separation tools.
- Mix and master — even a quick pass helps. Our beginner’s guide to mixing your first song covers the essentials, and an AI mastering tool like LANDR or eMastered can polish the final bounce.
Step 6: Check what you’re allowed to do with it
Before you publish, confirm what the tool’s licence and your plan permit — commercial use, monetisation and ownership terms vary by tool and are an evolving legal area. If you intend to release or sell the track, read can you sell AI music first. This is general guidance, not legal advice.
How to write a prompt that actually works
Most disappointing results come from a prompt that’s too thin, not from the tool being weak. A useful prompt answers four questions for the model: what style is this, how should it feel, what’s playing, and who’s singing. Think of it as a brief you’d hand a session musician rather than a wish. The more concrete you are, the less the model has to guess — and guessing is where generic, samey output comes from.
A few habits make a measurable difference:
- Lead with genre and sub-genre. “Indie folk” lands somewhere different from “lo-fi bedroom indie folk.” The narrower tag pulls the model toward a clearer reference point.
- Describe the feel in plain words. Mood terms like “wistful,” “driving,” “sparse” or “triumphant” steer the arrangement more than tempo numbers alone.
- Name a couple of instruments, not ten. Listing every instrument you can think of muddies the result. Two or three signature sounds give the model a backbone to build on.
- Be specific about the vocal. Range, gender, tone and delivery (“breathy,” “raspy,” “spoken-word”) shape the whole track, because the vocal usually sits front and centre.
- Use era and feel instead of artist names. Many tools filter out artist references, and even when they don’t, “early-2000s garage rock energy” is more reliable than naming a band.
Common mistakes to avoid
Once you’ve made a few tracks you start to notice the same traps. Knowing them up front saves a lot of wasted generations.
- Treating the first generation as final. The first draft is a starting point. The strongest results almost always come from several passes, not one lucky prompt.
- Changing everything at once. If you rewrite the whole prompt between generations, you can’t tell what helped. Move one variable at a time so you learn what each word does.
- Skipping the DAW. Publishing the raw export is the quickest way to sound “AI-made.” A trim, a level balance and a light master separate a usable track from an obvious clip.
- Ignoring loudness and dynamics. AI bounces are often inconsistent in level. A quick mastering pass fixes volume jumps and stops the track feeling flat next to professionally released music.
- Assuming you own it outright. Licence terms differ by tool and plan, especially for commercial use. Check before you build a release around a track.
Tips for better AI music
- Be specific about instruments and mood; vague prompts give vague results.
- Generate several versions and cherry-pick the best sections.
- Use reference language — naming an era or feel often helps more than naming an artist.
- Always finish in a DAW if you want it to sound intentional.
Frequently asked questions
Do I need music skills to make AI music?
No. The generation itself needs no musical training — you describe what you want. Basic production knowledge helps you edit and finish the track, but you can start with zero experience.
How long does it take to make an AI song?
Generating a draft takes a minute or two. Getting something you’re happy to release — with iteration, editing and a mix — can take anywhere from half an hour to an afternoon, depending on how polished you want it.
What’s the best free way to make AI music?
Several tools have free tiers. BandLab SongStarter is free and DAW-based, and most text-to-song tools offer limited free generations. See the best free AI music generators for the current options.
Why do my AI tracks all sound the same?
Usually it’s the prompt. Short, generic prompts push the model toward its most average output, so everything ends up sounding alike. Tighten the genre, name a distinctive vocal and instrument, describe a specific mood, and finish each track differently in your DAW. Small changes in the brief lead to noticeably more varied results.
