How Artificial Intelligence Has Changed the Music Streaming Industry

Music has always been about creative expression and about sharing a message or feeling. While that still holds true today, the music industry has changed in many ways since people first started buying vinyl records decades ago. Namely in the way that music is shared and distributed but also in the way music is viewed – at least by record labels. Now big data drives their decision-making processes to reach as big of an audience as possible.

Machine learning, fueled by a massive internal, user, and external data sets, have redirected the way people create and consume music forever. The streaming industry has only blossomed in the last decade – the blink of an eye in music terms – and AI runs it.

Dancing to the Tune of Artificial Intelligence

Streaming platforms like Spotify, Joox, and QQ Music apply AI and machine learning liberally to increase personalization. In fact, providing personalized experiences lies at the heart of the massive success that streaming companies like Spotify have enjoyed so far.

This is because music is a deeply personal experience, and people differ in their tastes, even within the same genre. Then there’s also the fact that a person’s mood can influence the music they decide to listen to.

Companies know that, which is why they’re using machine learning to transform the way they deliver music. The current AI application has already made great strides in search optimization and recommendation engines by analyzing listener habits, the media, and audio.

How Machine Learning Improves The User Experience

The term artificial intelligence can be confusing as it has several different applications. In terms of the music industry, this translates to algorithms used to detect patterns and make decisions based on them. Those patterns are supplied by two major sources:

User Data

Streaming platforms look at users’ behavioral trends to guide their algorithms. This includes how often they listened to a song, which genres they listen to most, and which songs they add to playlists. Each platform’s algorithms surely include many more behavioral markers than those listed here, but the public isn’t necessarily privy to them.


What is evident, however, is that these companies also gather other sets of personal data to link to their users for deeper insights. The type of data they gather likely varies, but it does include things like people’s location, age, keyword preferences, and the devices people use.

Audio Analysis

One of the most intensive applications of AI in music streaming is in audio analysis – also called audio models. The big streaming platforms, like Spotify and Apple Music, add thousands of new songs to their libraries every day. Every song is analyzed and tagged according to different vectors.

Some companies utilize advanced technology, like convolutional neural networks – the same tech used in facial recognition. This helps streaming services go beyond normal genre tags to analyze a song’s pitch, melody, vocal styles, lyrics, and more. With that, they can combine user preferences to recommend songs that those users will presumably want to listen to.

Security Flaws Inherent in Today’s Data Gathering Model

The prospect of personalization is promising – who doesn’t want new playlists tailored to their tastes and moods? But it comes at a cost because AI isn’t just used to provide a better user experience. Streaming services are also using machine learning for advertising purposes.

While that’s already frustratingly invasive to a degree, the bigger problem is that user data can be exposed during cybersecurity attacks. Data breaches are among the most common security threats in the world right now, and they expose a lot of sensitive personal information. This threat isn’t just limited to the streaming platforms people use either but includes the advertisers they share information with.

So what can users do? The first step is to be informed on how much of their data is being collected. The next is to use additional privacy tools like VPNs to avoid the risk of cyber threats.

A virtual private network encrypts users’ online traffic, and hides their location, preventing third parties (like advertisers) and hackers from getting their information. Don’t opt for the free services, though, as they’re usually slow and may gather data for advertisers too, defeating the purpose.

Paid VPN services offer protection from more than just data-gathering streaming platforms and provide a few other benefits too. For instance, they give users access to geo-restricted streaming content and can even help save a few dollars off of online shopping or travel expenses.

The Future of Personalized Music Streaming

Artificial intelligence has and continues to transform the music industry in incredible ways, however, this needs to be tempered with caution. Right now, AI is used to gather incredible amounts of data, which could fall into the wrong hands.

This threat may become even greater in the near future as people start moving towards wearable technology. Imagine a sensor or implant that monitors their moods and can adapt the music they’re listening to accordingly in real-time. It may not be a reality now – but neither was music streaming tw