TV is being YouTube-ified
You sit down to watch TV. But instead of flipping through cable channels, you pick up your remote and open YouTube. The home screen floods with a curated lineup: the latest Daily Show episode with Jon Stewart, a highlights reel with yesterday’s best NBA moments, and a quick summary of the stock market, brought to you by Bloomberg. You didn’t specifically ask for any of these videos, but somehow, they’re exactly what you like to see. So you lean back... and just enjoy the show.
This is the new primetime. Not dictated by a human or a TV network, but assembled by an algorithm that knows your tastes better than you do. What was once a platform for viral cat videos and amateur clips is now reshaping the very nature of television. And it’s not just YouTube. Traditional TV and streaming giants are racing to adapt.
It's an interesting convergence, actually. YouTube is becoming more like TV. TV is becoming more like YouTube. And somewhere in between, the future of how we watch is taking shape. Some time ago I wrote about a resurgence of old entertainment concepts and habits, including “linear TV”. But this is more than that. The question is no longer whether it will happen - it already is. The real question is: what comes next?
From Scheduled Viewing to Algorithmic Curation
Television was once defined by the clock. Prime time slots, appointment viewing, and watercooler moments the next day. Viewers tuned in not just to see their favorite shows but to align with a collective schedule. Then came streaming - Netflix, Hulu, Disney+ - giving viewers control over what to watch and when. Binge-watching replaced weekly rituals. Convenience became king.
But now, something new is emerging. YouTube, TikTok, and even Instagram Reels are rewriting the script. These platforms thrive on endless, personalized feeds. Content is surfaced not because of when it was made or aired, but because an algorithm calculated it is something you like. Passive consumption is making a comeback - but with precision targeting.
This shift is driven by data. Platforms analyze viewing history, watch duration, likes, and even pauses. Every scroll, skip, or rewatch refines the algorithm. The result is a hyper-personalized experience. Instead of choosing from a fixed menu, viewers are handed a buffet that constantly reshapes itself based on their tastes. This, by the way, is not that different from my absolute favorite Spotify feature – the Discover Weekly playlist.
The implications are quite interesting. Traditional TV networks crafted schedules based on broad audience preferences. Streaming platforms offered vast libraries but often left viewers overwhelmed by choice. Now, algorithms aim to solve this paradox - offering the ease of traditional TV with the personalization of streaming. It's not by accident that connected TVs are now the 'primary device' for watching YouTube in the US.
Why YouTube’s Model Works
At the heart of YouTube’s success is its ability to blend infinite content variety with algorithmic targeting. The platform thrives because it understands three key things: discovery, creators, and passive consumption.
Discovery is effortless. Viewers don’t need to search endlessly. The algorithm continuously surfaces content tailored to individual interests - sometimes before the viewer even knows they’re interested. This removes friction and fosters a near-endless viewing loop.
Creators fuel the ecosystem. Unlike traditional studios, YouTube hosts millions of independent creators producing niche content. Whether it’s a lesson to play bass like a monster (Joe Dart, this is for you) or theories about the weirdest Severance episode ever, there’s something for everyone. This almost infinite catalogue ensures that algorithms can always match content to specific tastes.
Passive consumption completes the cycle. YouTube’s autoplay feature mimics traditional TV’s lean-back experience. But instead of reruns or generic programming, it offers fresh, hyper-relevant videos. Viewers can engage actively or let the algorithm handle the programming.
This trio - discovery, creators, and passive consumption - forms a self-reinforcing loop. Algorithms surface content, creators respond to demand, and viewers stay engaged. The result? A platform that increasingly feels indeed like the future of television.
How “Traditional” Media Is Fighting Back
Other media companies have taken notice. The success of YouTube’s algorithm-driven model is reshaping the strategies of both TV networks and streaming platforms.
Streaming giants like Netflix, Disney+, and Amazon Prime Video are integrating more algorithmic recommendations into their interfaces. Netflix's “Play Something” feature is designed to reduce friction, improve discovery, and replicate the lean-back viewing experience YouTube has perfected. HBO Max and others now feature continuously updated carousels based on viewing patterns.
Netflix “Play Something” feature
Free ad-supported streaming television (FAST) platforms like Pluto TV (one of my long-time favorites), Tubi, and Roku Channel have successfully replicated the old-school linear TV experience, by distributing or creating their own FAST channels. These services offer scheduled channels that autoplay content, reducing decision fatigue while still leveraging data for curation. FAST platforms are rapidly growing, with global FAST revenues projected to reach $12 billion by 2027, up from $4 billion in 2022.
Pluto TV channel guide UI
Traditional broadcasters are experimenting with digital-first, short-form content to engage younger audiences - often distributed via YouTube or TikTok before hitting linear schedules.
But they face a fundamental challenge: their content is premium, costly, and finite—while YouTube’s creator-driven model scales infinitely.
The result is a hybrid future. Streaming services will increasingly resemble YouTube in their UX - offering both on-demand libraries and algorithmically generated “live” feeds. Traditional TV won’t disappear, but its role will shift - from the default viewing option to a curated, premium experience within a broader ecosystem dominated by data-driven platforms.
The Risks of the YouTube-ification of TV
While algorithm-driven content curation offers convenience and endless entertainment, it comes with trade-offs.
One concern is the narrowing of content diversity. Algorithms optimize for engagement, often favoring sensational, polarizing, or formulaic content. This can create (even more) filter bubbles, where viewers are fed more of what they already like, reducing exposure to diverse perspectives or unconventional programming. The serendipity of stumbling upon an unexpected documentary or a foreign drama on traditional TV risks being lost… but again, with video consumption moving online and to on-demand platforms, this is already happening to some degree.
Quality is another potential casualty. YouTube excels in volume and variety, but not every video meets the production standards of traditional TV. As streaming platforms race to integrate algorithmic curation, there’s a risk that premium, carefully crafted content could be deprioritized in favor of what’s quick, cheap, and likely to go viral.
Finally, viewer agency may erode. Paradoxically, while platforms promise choice, the reliance on algorithms can make viewers passive participants. What you watch is increasingly shaped by invisible machine learning systems. The result? An entertainment landscape that feels curated just for you - but subtly steered by what keeps you watching the longest.
These risks underscore a critical tension: convenience versus curation. As television becomes more YouTube-like, the challenge will be preserving quality, diversity, and viewer autonomy in an era defined by infinite choice.
What Comes Next?
The YouTube-ification of television is far from over. In fact, we’re likely only at the beginning of a deeper convergence between traditional media and algorithmic platforms. As these worlds blend, the future of entertainment will likely be shaped by a few key developments:
Hybrid Models – The line between streaming platforms, live broadcasts, and algorithmic feeds will continue to blur. Platforms like Netflix and Disney+ may lean further into YouTube-style recommendations while platforms like YouTube may invest more in premium, long-form content and live events. Expect more platforms to offer a mix of lean-back autoplay channels alongside their traditional libraries.
Creator-Led Premium Content – As creators gain larger audiences and build direct relationships with fans, we could see a new class of “creator studios” producing high-budget content rivaling traditional networks. Think of YouTube stars directing feature-length films, or TikTok creators producing docuseries - all distributed natively on the platforms where they built their followings.
AI-Generated Content – The next evolution of algorithmic curation could be algorithmic creation. AI-generated hosts, procedurally created news summaries, or dynamically generated sports highlights—all customized for individual viewers—may become part of the media landscape.
Interactive and Personalized Storytelling – With the rise of data-driven platforms, entertainment could become even more interactive. Viewers might shape storylines in real time, or see different endings based on their viewing habits. Personalized narrative experiences, blending gaming and streaming, could become a new frontier.
The Return of Curation as a Differentiator – this one is ironic, but we’ve seen it happening in similar situations. As algorithms dominate, there may be a growing counter-trend: human curation as a premium feature. Platforms could emphasize “editor’s picks,” trusted critics, or curated playlists to stand out in an increasingly automated landscape.
Performance-Based Content Licensing – The shift to algorithm-driven distribution could reshape how premium content is licensed and monetized. Studios that once relied on upfront licensing deals with streaming platforms may increasingly move toward performance-based models, where revenue is tied to viewership metrics and algorithmic promotion. This would incentivize content that resonates algorithmically, potentially altering creative and production strategies.
Ultimately, the future of television won’t be a return to the past - it will be something new. A fusion of the precision of data, the creativity of creators, the timeless appeal of a great story, and an endless lean-back experience.
The remote control may never feel the same again.