3 playlists you can manually curate with AI today

When you use AI to automate tagging, it’s like having a music expert listen to (and categorise) your tracks. You get accurate track data that adheres to a cohesive and defined taxonomy. 

Sure, AI tagging saves you time, but it’s also the foundation for loads of creative solutions to real business problems. One of those is automating playlist curation.

On the Musiio blog, we recently looked at an easy, time-saving way to use this AI-generated tag data to help create playlists. We specifically say “help” because we firmly believe that AI is best applied as an assistive tool. It automates the tasks you don’t want to do, so you can leverage your musical intuition. 

In the first instance, this process can save you time listening to inappropriate tracks, but the level of catalogue segmentation that’s possible may surprise you. And it’s especially powerful when filtering down massive catalogues.

Here are some concrete examples of playlists you can quickly curate with automation made possible by AI tagging.

1. Pump

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A reliable workout playlist can be tricky to curate. There are many different genres you could highlight, and each will find its own audience. But thinning down your catalogue to only show you appropriate tracks is remarkably quick with AI tags. 

Here, we’re aiming for a high-energy, motivational electronic sound to keep the endorphins pumping.

You can build this workout playlist by including tracks with the following attributes:

• Genre: Electronic
• Mood: Energetic
• BPM: 120-135

If your longlist still has too many dark-sounding or unusual tracks, you can be just as prescriptive by excluding tags. For example, try excluding the following:

• Energy: Very Low, Low, Medium
• Mood Valence: Negative
• Mood: Dark
• BPM Variance: Large

2. Focus

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Once your listener has left the gym, it’s time to create a suitable focus playlist. If you stay within the world of electronic music, it’s pretty trivial to generate another longlist of tracks using AI-generated tags.

This time, the objective is to create a downtempo, relaxing playlist that still has repetitive, hypnotic elements to promote a focused state. And above all, it can’t have any distracting vocals.

You can make that longlist using the following tags:

• Genre: Electronic
• Energy: Medium and Low
• Mood: Relaxed
• BPM: 70-90
• Instrumental, with Percussion elements

Depending on your catalogue, this tag mix should leave you with some interesting options. And if you’re finding that you need to narrow things down again, try excluding:

• Mood: Romantic 

3. Recentre 

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Finally, after a hard day tapping away in the content mill, your listener needs soundscapes to underscore some gentle stretches and escape thoughts of mindless toil. 

The aim is to create a sense of restorative calm with an electronic sound palette.

You can try to build your list of candidate tracks with these tags:

• Genre: Electronic and Ambient
• Mood: Neutral
• Instrumental

You may find at this point a decent few tracks still aren’t passed the vibe check. To zero in on that soporific, meditative sound, you’d do well to exclude these:

• Mood: Dark, Sad, Scary
• Energy: Medium, High, Very High
• Percussion elements

These are just three examples of the sorts of activity-based playlists you can easily make with the assistance of AI tagging. To learn more about how one of our amazing clients has integrated AI into their curation process, read the BeatMix case study.

Next time, we’ll look at ways of using Musiio tech to audition alternative tracks for sync.

To learn more about how AI tagging can help you scale playlisting, drop us a message via our contact form, on Twitter, LinkedIn or email sales@musiio.com.