Tech News : Spotify Introduces Real-Time Listening Activity And Jam Requests

Spotify has introduced two new Messages features that let users see what friends are listening to in real time and invite them into shared listening sessions, signalling a deeper shift towards in-app social interaction.

Wider Rollout By Early February

The update, confirmed by Spotify on 7 January, adds Listening Activity and Request to Jam to markets where Messages is already available, with wider rollout expected by early February.

Why Spotify Is Doubling Down On Social Features

For much of its history, Spotify has been a largely solitary experience. For example, while playlists, links, and Wrapped summaries encouraged sharing, that sharing typically happened elsewhere, via WhatsApp, Instagram, or other messaging platforms.

However, the introduction of Messages in August 2025 marked a change in direction. Spotify began experimenting with keeping conversations inside its own ecosystem, rather than acting purely as a content source for other apps.

According to Spotify’s Newsroom, that shift has already shown measurable engagement. The company says that “almost 40 million users have sent nearly 340 million messages” since Messages launched, indicating sustained use rather than novelty adoption.

Listening Activity and Request to Jam build directly on that behaviour, turning private listening into a visible signal and reducing friction between discovery, conversation, and shared playback.

Listening Activity

Listening Activity is an opt-in feature that displays what a user is currently listening to within the Messages interface. If the user is not actively playing audio, their most recently played track is shown instead.

Once enabled (via the Privacy and social settings), activity appears at the top of Messages chats and in the chat row of the side drawer. It is only visible to contacts a user has already messaged on Spotify.

Spotify has been keen to highlight the controllability of Activity sharing, pointing out that it can be turned off at any time, and users can still see other people’s listening activity even if they have not enabled their own, provided the other person has opted in.

Tapping on a friend’s listening activity opens a set of quick actions, including starting playback, saving the track, opening the context menu, or reacting with one of six emojis. The design focuses on immediacy rather than commentary, encouraging lightweight engagement rather than long conversations.

Spotify describes the feature as giving users “a real-time look at what music your friends and family are listening to”, positioning it as a social awareness rather than a performance feature.

Request To Jam And The Growth Of Shared Listening

Alongside visibility, Spotify is also making it easier to act on that awareness through Request to Jam. This is Spotify’s real-time collaborative listening feature, which allows users to share a queue of tracks and listen synchronously from different locations. Spotify says Jam usage has been accelerating, noting that daily active users have “more than doubled year over year”.

Why?

Request to Jam actually addresses one of the main barriers to remote shared listening, i.e., timing. For example, previously, users needed to coordinate externally or guess when friends were available. With Listening Activity, availability becomes visible, and Request to Jam provides a one-tap invitation.

Premium users can send a Jam request directly from a Messages chat. The recipient can accept or decline. If accepted, the recipient becomes the host, and both participants can add tracks to a shared queue.

Suggested Tracks

During a Jam, participants see each other’s display names and receive suggested tracks based on their combined listening profiles. Invitations expire if not accepted, and users can leave sessions at any time.

Spotify frames this as a way to “quickly turn those moments into shared listening sessions”, blending discovery with participation.

Subscription, Age, And Messaging Limits

Spotify says access to the new features is shaped by existing platform constraints. Listening Activity is available to all users with access to Messages, regardless of subscription tier. Request to Jam, however, can only be initiated by Premium users, though Free users can join when invited.

Both features are limited to users aged 16 and over, reflecting Messages’ existing age restriction. Messages themselves remain one-to-one only, and users can only message people they have previously shared content with, such as playlist collaborators or Jam participants.

Messages are encrypted at rest and in transit, though Spotify has confirmed they are not end-to-end encrypted, a point that may matter to privacy-conscious users.

For Spotify

From a commercial perspective, these features support several of Spotify’s core objectives. For example, keeping discovery, conversation, and shared listening inside the app increases time spent on the platform, strengthens habit formation, and reduces reliance on external social networks. Each of those factors contributes to retention, which remains critical in a highly competitive streaming market.

Also, Request to Jam essentially reinforces the value gap between Free and Premium tiers. While Free users can participate, only Premium subscribers can initiate sessions, subtly encouraging upgrades without aggressive prompts.

There is also a data dimension to all this. For example, social listening creates more context around discovery, which may improve recommendation quality over time, especially when combined listening preferences are involved.

Competitive Pressure On Other Streaming Platforms

Spotify’s move further differentiates it from rivals that focus primarily on catalogue and audio quality rather than social interaction.

Apple Music, Amazon Music, and YouTube Music all offer sharing and collaborative playlists, but none have integrated real-time listening visibility and messaging in the same way. Spotify’s approach positions social engagement as a product feature rather than a marketing add-on.

If Listening Activity and Jam continue to grow, competitors may face some pressure to respond, particularly if users begin to associate Spotify with shared experiences rather than individual consumption.

Users And Business

For everyday users, the changes lower the barrier to discovery and shared listening, particularly for people who already use Spotify socially with friends or family.

For businesses, creators, and brands, the implications are more indirect but still relevant. For example, music-led environments such as gyms, retail spaces, cafés, and studios increasingly use Spotify as part of their brand experience. Greater social visibility may influence how playlists spread organically between users.

Artists and podcasters may also benefit if listening activity encourages faster, peer-driven discovery, though Spotify has not yet provided data on how activity visibility affects streaming behaviour at scale.

Criticisms and Challenges

Despite the careful framing, the update is not without potential drawbacks. For example, some users may be uncomfortable with even limited visibility into their listening habits, particularly when content is personal or sensitive. Although Listening Activity is opt-in, social pressure can still influence participation once features become widespread.

There are also privacy questions around how listening data is surfaced, even among known contacts. While Spotify has avoided public feeds, the boundary between awareness and exposure remains subjective.

From a product perspective, Messages is still a relatively constrained system. The lack of group chats and broader discovery limits how far social interaction can scale, and some users may continue to prefer external messaging apps regardless of new features.

It remains unclear at this point how Listening Activity will affect listening behaviour itself. Although visibility can encourage sharing, it can also lead to self-censorship, where users avoid certain content because they know it may be seen.

That said, Spotify’s rollout seems to suggest a confidence that the benefits will outweigh those risks, but real-world adoption will determine whether social listening becomes a core part of the platform or remains a feature used by a smaller subset of engaged users.

What Does This Mean For Your Business?

Spotify’s decision to surface listening behaviour and make shared sessions easier reflects a broader recalibration of what a streaming platform is expected to do. For example, this is no longer just about access to a catalogue or algorithmic recommendations, but about creating moments of interaction that keep users present, engaged, and less likely to drift elsewhere. Listening Activity and Request to Jam both essentially prioritise immediacy, reducing the steps between discovery, response, and participation.

For Spotify, retention matters as much as growth, and social features that sit naturally inside everyday listening habits offer a way to deepen engagement without radically changing how the app works. The measured design choices, opt-in visibility, one-to-one messaging, and Premium-led initiation suggest an attempt to balance expansion with control rather than chasing scale at all costs.

For competitors, this could raise the bar around what shared listening looks like in practice. Collaborative playlists alone may start to feel static if real-time awareness and interaction become more normalised. Whether rivals respond with similar features or take a different approach will shape how social music streaming evolves over the next few years.

UK businesses and organisations that already rely on Spotify as part of their customer or workplace experience may also feel indirect effects. For example, shared listening habits can influence how playlists circulate organically, how music-led environments shape brand perception, and how quickly new content gains traction through peer visibility. For creators, venues, retailers, and service-led spaces, the line between listening and recommendation is becoming shorter and more socially driven.

At the same time, adoption is not guaranteed. Privacy comfort levels, differing attitudes to visibility, and the continued pull of external messaging platforms will all influence how widely these features are used. Spotify’s challenge now is less about launching new tools and more about ensuring they become part of everyday behaviour without creating friction or fatigue.

How users respond over the coming months will determine whether social listening becomes a defining layer of Spotify’s identity or remains a useful but optional enhancement for a more engaged subset of its audience.

Tech Insight : Spotify AI ‘Band’ Sparks Labelling Debate

In this Tech Insight, we look at how the sudden rise of a (possibly AI-generated) band on Spotify has reignited the debate over whether music streaming platforms should clearly label artificially created songs.

An Indie Rock Hit, But Who Made It?

The Velvet Sundown appeared suddenly in June 2025 and has since attracted more than 850,000 monthly listeners on Spotify. To give some idea of their popularity, their most streamed track, Dust on the Wind, has been played over 380,000 times, with many listeners noting similarities to the 1977 Kansas ballad Dust in the Wind. However, it seems that no one knows for sure who the band actually is, or whether its members even exist.

Four Names and Not Much Else

The band’s Spotify profile lists the four names of band members as Gabe Farrow, Lennie West, Milo Rains, and Orion “Rio” Del Mar. However, it’s been reported that none of these individuals has any online presence outside the band, i.e., no interviews, no live shows, no solo projects. In fact, their Instagram feed is populated with images that appear to be AI-generated, showing oddly rendered “band members” in stylised poses. Also, a supposed quote from Billboard magazine in their bio (“the memory of something you never lived, and somehow makes it feel real”) has no known source.

Speculation

It seems that the ambiguity has fuelled speculation across Reddit, X, and YouTube, with some users pointing out audio “artefacts” in the recordings (small glitches or distortions often associated with synthetic audio generation tools). Music producer and YouTuber Rick Beato has been reported as describing the band’s output as having the hallmarks of AI composition, especially after running one of the songs through a digital splitter in Logic Pro.

Suno, Deezer and the “AI Slop” Flood

Although The Velvet Sundown has not confirmed the use of AI tools, the music streaming service Deezer has flagged all of the band’s tracks as “100 per cent AI-generated” using its new detection algorithm. Deezer is currently the only major platform openly tagging AI music content. Its system identifies audio created with generative tools like Suno and Udio, which can compose full songs from basic text prompts.

In April 2025, Deezer reported that 18 per cent of all content uploaded to the platform was AI-generated, a sharp rise from just 10 per cent in January. That translates to more than 180,000 bot-made tracks per week! Deezer CEO Alexis Lanternier has said that the goal is not to ban AI music, but to ensure transparency and protect the interests of human artists.

“AI is not inherently good or bad,” he said. “But we believe a responsible and transparent approach is key to building trust with our users and the music industry.”

Spotify, Apple and Amazon Stay Quiet

In contrast, it seems that streaming platform Spotify has no current system in place to flag AI-generated content and has made no official comment on The Velvet Sundown. CEO Daniel Ek has previously been reported as saying that Spotify would not ban AI-made tracks, but stated he was opposed to using the technology to impersonate real artists. Despite that, Spotify’s algorithm has promoted The Velvet Sundown on its personalised “Discover Weekly” playlists, pushing the track to millions of users without any disclosure of its potential origin.

Apple Music and Amazon Music also host The Velvet Sundown’s music but have remained silent on whether they intend to introduce any kind of AI labelling or detection system.

A Lack of Labelling Sparks Concern

It seems that this lack of labelling has sparked concern from artists, producers and industry groups. For example, Ed Newton-Rex, founder of the advocacy group Fairly Trained, described the situation as “theft dressed up as competition.” He argued that AI firms are profiting from training data scraped from real musicians’ work, often without consent or compensation.

Identity Confusion and Media Hoaxes

Adding to the confusion, Rolling Stone US initially reported that a spokesperson for the band had confirmed the music was generated using Suno. That spokesperson later turned out to be fake, part of an elaborate “art hoax” designed to deceive journalists. The individual, known as Andrew Frelon, later admitted in a Substack post that he was unaffiliated with the band and fabricated the story.

In response, The Velvet Sundown issued a statement on its Spotify page denying any link to Frelon, describing his claims as “unauthorised.” The band has continued to post cryptic messages via its social media channels. One X post read: “They said we’re not real. Maybe you aren’t either.”

It seems that this ambiguity is part of the brand’s strategy. Their upcoming album, Paper Sun Rebellion, is being promoted with AI-style visuals and poetic descriptions that blur the line between artificial and authentic. Whether this is genuine artistic expression or a marketing gimmick has become a key question for commentators.

A Threat to Emerging Artists?

For real-world musicians, the rise of AI-generated bands actually poses a serious challenge. Kristian Heironimus, of the indie group Velvet Meadow, was recently quoted in NBC News as saying that watching an alleged AI act soar to 500,000 listeners in just two weeks was “disheartening.” He highlighted the difficulty of competing with endless, instantly produced AI content that can mimic any genre and flood discovery algorithms.

Many in the industry appear to share his concern. For example, last year, hundreds of artists, including Sir Elton John and Dua Lipa, signed an open letter demanding legal protections against the unauthorised use of their work in training AI models. While the UK government declined to introduce new legislation at the time, it is currently holding a separate consultation on AI and copyright.

Meanwhile, a coalition of major US record labels (Universal Music Group, Sony Music and Warner Music) has filed lawsuits against AI music developers Suno and Udio, alleging large-scale copyright infringement. Both companies argue that using publicly available music to train models constitutes “fair use,” a defence commonly deployed by AI developers.

Who Decides What’s Real?

The lack of consensus on what constitutes “AI-generated” music adds further complexity. Some artists use AI tools like Suno or Udio to create backing tracks or generate lyrics, while others use them to compose full songs. Platforms like Spotify typically don’t require artists to disclose how their music was made. Nor do they differentiate between artists who use AI as a tool and those who rely on it entirely.

Most Platforms Treat AI Songs Like Human Ones (For Now)

Deezer’s approach is based on identifying audio characteristics and metadata patterns typical of AI tools. However, even that has limits, particularly as generative music becomes more sophisticated. For now, most streaming platforms continue to treat AI songs the same as human-made ones for purposes of recommendation, royalties, and categorisation.

People Are Interested In More Than Just The Sound of an Artist

Industry voices like Lanternier warn that this is unsustainable. “People are not only interested in the sound,” he said. “They are interested in the whole story of an artist… We believe it’s right to support the real artist, so that they continue to create music that people love.”

Listeners Left in the Dark

From a user perspective, it seems it’s increasingly difficult to tell what’s human and what’s machine-made. For example, generative AI can now mimic voices, create convincing instrumentals, and even generate promotional images, all with minimal input. This means that listeners may not even realise they’re streaming AI-made content unless a platform flags it.

This has broader implications for trust. For example, as Professor Gina Neff from the University of Cambridge noted in relation to this subject, “Our collective grip on reality seems shaky. The Velvet Sundown story plays into the fears we have of losing control of AI and shows how important protecting online information is.”

“AI Slop” Drowning Out Real Voices?

It also seems that some fear that AI-generated content (sometimes referred to as “AI slop”) will drown out real voices, especially in genres like indie rock or ambient electronica where lyrical ambiguity and minimalistic production make AI mimicry easier to hide.

However, others, like Suno CEO Mikey Shulman, believe the conversation is overblown. “I think people are forgetting the important question, which is: how did it make you feel?” he said. “There are Grammy winners who use Suno in their production every day.”

That said, the debate continues to sharpen and, with AI tools getting more advanced and streaming platforms dragging their feet on labelling, the question of who (or what) we’re actually listening to may only get more complicated.

What Does This Mean For Your Business?

Whether The Velvet Sundown is a genuine artistic experiment or a high-concept AI stunt, its rapid rise appears to have thrown the spotlight on the growing presence of synthetic music in mainstream discovery channels. The core issue is not simply the existence of AI-generated tracks, but the complete absence of transparency around them. For example, if listeners can’t tell whether a song is human-made or artificially composed, the entire trust framework underpinning streaming services begins to erode.

This matters not just for artists and platforms, but for a much wider set of stakeholders. For independent musicians and producers, there’s a real risk that generative AI will continue to crowd their work out of key algorithms and recommendation feeds. For record labels and rights holders, the legal and licensing landscape remains unclear, especially while AI companies assert fair use in the training of their models. Also, for UK businesses in the creative, tech, marketing or media sectors, the commercial implications are equally serious. For example, AI-generated content could be misused in ad campaigns, misrepresent music licensing in branded environments, or create reputational risks for companies trying to align with genuine cultural voices.

It’s also becoming harder for consumers and businesses to trust the authenticity of what they’re engaging with. When a band can be created, promoted and streamed globally without anyone knowing if it even exists, it raises questions about how influence, monetisation, and even identity are being managed online. For a platform like Spotify to push AI-generated tracks without disclosure, while human creators struggle to break through, could create long-term imbalances in both visibility and revenue distribution.

What’s clear is that this isn’t just a creative debate but is also a technological, ethical and commercial one. Without industry-wide standards or regulatory clarity, streaming platforms may soon find themselves forced to choose between innovation and integrity. Whether through clear labelling, artist verification, or changes to royalty structures, the choices made now will shape the relationship between AI and music for years to come.