How to Make a Song With AI

Step 1: Choose Your AI Music Platform

Your platform choice determines what kind of output you can create and how you interact with the tool. For your first AI song, Suno is the recommended starting point because it handles the entire process, from prompt to finished song with vocals, in a single step. You do not need to understand music theory, own a DAW, or have any prior production experience.

If you specifically want instrumental-only output, SOUNDRAW and Beatoven.ai offer more control over background music styles through parameter menus rather than free-form prompts. If you want to run generation locally without an account or subscription, MusicGen is the best open-source option, though it requires GPU hardware and technical setup. Our best AI music generators guide covers each platform's strengths in detail.

Create an account on your chosen platform. Most offer free tiers that let you generate a limited number of tracks per day, which is enough to learn the workflow before committing to a paid plan.

Step 2: Write Your Music Prompt

The prompt is the most important input in the entire process. A well-written prompt produces dramatically better output than a vague one. Think of it as giving a session musician a creative brief rather than just saying "play something nice."

Include these elements in your prompt:

Genre: Be specific. "Indie folk" is better than "folk." "90s boom-bap hip-hop" is better than "rap." Combining genres works well: "acoustic folk-pop with soft electronic production."

Mood: Emotional descriptors guide the harmonic and rhythmic choices. "Wistful and nostalgic" produces different music than "energetic and triumphant." Use two or three mood words to be clear.

Instrumentation: Name the instruments you want to hear. "Acoustic guitar, upright bass, gentle brushed drums, and warm piano" gives the model specific targets. Without instrument guidance, the model chooses a default palette that may not match your vision.

Tempo: Describe the speed as "slow," "mid-tempo," or "fast," or provide a specific BPM value if you have one in mind. This prevents the model from generating an energetic dance track when you wanted a slow ballad.

Production style: Describe the recording aesthetic. "Lo-fi with warm analog character" produces a different texture than "crisp modern studio production." This influences reverb, compression, and overall polish.

A complete example prompt: "Slow tempo indie folk ballad with male vocals, acoustic guitar fingerpicking, soft cello, and gentle brushed drums. Wistful and nostalgic mood, like driving through the countryside at sunset. Warm lo-fi production with a little room reverb."

Step 3: Add Custom Lyrics

Most platforms let you either provide your own lyrics or have the AI generate them. Auto-generated lyrics are convenient but often generic, relying on common rhyme patterns and predictable imagery. Writing your own lyrics gives you control over what the song actually says and produces a more personal, intentional result.

When writing lyrics for AI generation, keep a few things in mind. Shorter lines tend to be set to music more successfully than long, prose-like sentences. Clear syllable counts help the model maintain rhythmic consistency. Standard song structures (verse, chorus, verse, chorus, bridge, chorus) are well-understood by trained models and produce the most coherent output. You can indicate structure using tags that the platform recognizes, such as [Verse], [Chorus], and [Bridge].

If you are not a natural lyricist, a middle-ground approach is to write the key lines and themes yourself, let the AI fill in supporting lines, and then edit the result. This preserves your creative intent while taking advantage of the model's ability to maintain rhyme schemes and syllable patterns.

Step 4: Select a Vocal Style

If your platform supports vocal generation (Suno, ElevenLabs), you can influence how the singing voice sounds. On Suno, the Voices feature lets you select from voice profiles or upload a short reference clip to guide the vocal character. You cannot clone a specific person's voice, but you can steer the output toward a general vocal quality: breathy, powerful, raspy, smooth, high-pitched, low-pitched.

Match the vocal style to your genre. A powerful, belting vocal suits an arena-rock anthem. A soft, intimate vocal fits a bedroom-pop track. A rhythmic, percussive delivery works for hip-hop. When in doubt, let the platform choose a default voice and then adjust in subsequent iterations based on what you hear.

For instrumental-only tracks, skip this step. For more detail on vocal options across platforms, see our guide to AI music generators with vocals.

Step 5: Generate and Review

Submit your prompt and listen to the complete output. Suno typically produces two variations from each prompt, giving you immediate options to compare. Other platforms may produce a single output per generation.

On your first listen, pay attention to several things. Does the genre match what you requested? Is the tempo appropriate? Do the instruments you specified actually appear in the output? If you provided lyrics, are they sung correctly with natural phrasing? Is the overall mood right?

Do not expect perfection from the first generation. AI music generation involves randomness, and even the best prompts produce variable results. The goal of the first generation is to see how well the model understood your intent, not to get a finished product. Generate three to five variations from the same prompt before making judgments about the prompt's effectiveness.

Step 6: Refine and Iterate

Based on your first results, adjust the prompt to fix what did not work. If the tempo was too fast, add "slow" or a specific BPM. If the wrong instruments appeared, name them more explicitly. If the mood was too aggressive, add calming descriptors. If the vocals did not match your vision, adjust the voice selection or add vocal style guidance to the prompt.

Iteration is where the real quality improvement happens. Most users who are disappointed with AI music generation have only tried one or two prompts. Experienced users iterate through five to fifteen variations, refining the prompt each time, before arriving at a track they are genuinely satisfied with. Each generation teaches you something about how the model interprets language, and that knowledge makes your future prompts more effective.

Some platforms offer additional refinement tools. Suno lets you extend or regenerate specific sections of a track. SOUNDRAW lets you adjust the energy curve and rearrange sections after generation. These post-generation editing capabilities reduce the need for full re-generations and let you fine-tune specific parts of an otherwise good track.

Step 7: Export and Use Your Song

Once you have a track you are happy with, download it in your preferred format. Most platforms offer MP3 and WAV export, with WAV providing higher quality for professional use. Some platforms like SOUNDRAW also offer stem export, giving you separate files for each instrument group that you can mix independently in a DAW.

Before publishing or distributing your track, verify your licensing rights. On Suno's free tier, output is restricted to non-commercial use. On paid plans, you own the track and can distribute it commercially. Each platform has different terms, so check the specific license associated with your plan before uploading to streaming services, using in monetized content, or selling to clients. For a complete overview of ownership rules, see who owns AI-generated music.