Beyond news and sports, many viewers have seemingly replaced standard linear broadcast with on-demand. This is particularly true with the generation that grew up with MP3 players and making their own playlist, rather than simply listening to a whole album. Now we appear to be moving back into a type of customized linear viewing habit. Whether you’re sitting at home (or anywhere for that matter) people are back to just watching programs which we called “couch potatoes”. They are series binge watching, continuously locked into niche channels, or just sitting there watching clips flying by endlessly. When you look at the Nielsen Research, YouTube has captured 11% of the main TV screen in the home.
I call this “on-demand linear”. We are even seeing these niche FAST channels delivered over-the-air now and I wanted to dig deeper into this with respect to advertising as linear is still the “cash-cow” for the broadcast business due to advertising.
I had the fantastic opportunity to ask these questions to Jiří Gabriel, COO of MISTV, who supplies complex solutions for advertising sales, rights, content and broadcast management worldwide.
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Independent content creators are no longer just challengers. They’re redefining the media landscape and going toe-to-toe with traditional broadcasters and major streaming giants for audience loyalty. A prime example of this shift? The recent Sidemen Charity Match, where over 90,000 fans packed Wembley Stadium to watch YouTube’s biggest stars compete on the football field. This event demonstrates how online influencers can now command the type of dedicated audiences once reserved for mainstream sports and entertainment events.
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Our industry stands at a fascinating crossroads. AI and automation have evolved beyond mere efficiency tools to become genuine catalysts for creative expression. Content teams everywhere face mounting pressure—viewers want more content, they want it faster, and they want it accessible across global markets. Would AI be capable of meeting these challenges without sacrificing the human touch that makes great content resonate?
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Traditionally, TV programming has relied on manual scheduling, which can be time-consuming and repetitive. As the media landscape becomes increasingly fragmented with the rise of numerous streaming platforms and broadcast channels, traditional scheduling methods are proving inefficient. The challenge for broadcasters and channel programmers today is to deliver engaging content while optimizing operational efficiency. AI-powered automation has emerged as a solution, transforming linear TV scheduling into a seamless process, enabling programmers to focus on creative storytelling and audience engagement.
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It happens all too often. A high-profile live broadcast is in progress, millions of viewers are tuned in, and suddenly—buffering. The screen freezes. Panic sets in. Engineers scramble to identify the cause, only to be met with the all-too-familiar response from network providers: “It’s not on our end.”
For years, media and broadcast companies have battled invisible network disruptions, struggling to pinpoint whether the issue stems from their infrastructure, a third-party provider, or somewhere deep within the network maze. Traditional monitoring solutions fail to provide real-time, end-to-end visibility, leaving teams playing an endless game of blame and guesswork.
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The evolution of professional audiovisual technology was once limited to organizations with significant financial and technical resources. However, rapid advancements in computational power, cloud computing, and artificial intelligence have altered this landscape. Today, sophisticated audiovisual tools are no longer restricted to large studios but are transforming industries such as media, fashion, sports, and luxury.
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As television consumption continues to evolve, service providers must embrace new technologies to remain competitive. The traditional model of content delivery, where viewers passively consume programming on rigid schedules, is long gone. Today, audiences expect seamless, personalized, and on-demand experiences that cater to their preferences, interests, and habits. At the same time, monetization strategies are becoming more sophisticated, moving beyond basic subscription models to incorporate advertising, hybrid AVOD/SVOD approaches, and real-time data-driven revenue opportunities.
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In today’s digital landscape, the demand for high-quality video content is ever-growing, driving the need for robust platforms that can support the development of modern video applications and streaming media services. One of the key challenges for enterprises, broadcasters, and content creators lies in effectively managing and delivering video content across various channels and devices. The first hurdle consumers encounter when wanting to view content is being able to access it. We’ve all heard or seen about big events where people haven’t been able to sign in at the time the event begins or where the video streaming quality has suffered.
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As millions of users consume streaming video content across various platforms daily, video app providers and mobile network operators face immense pressure to manage data usage and bandwidth efficiently. This challenge presents an opportunity to make the industry more sustainable. Leveraging data analytics captured through real device testing, streaming video service providers can not only optimize data transmission but also reduce energy consumption and promote sustainable user behavior. Vodafone, Telefonica, and Meta have already communicated interesting results in this field.
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When none other than Tyler Perry halts an $800 million studio expansion after seeing a text-to-video AI demo, you know something major is happening in media and entertainment. AI isn’t new to the industry—Netflix has used machine learning (ML) to serve up recommendations since the early 2000s—but generative artificial intelligence (GenAI) is changing more than distribution and marketing. GenAI is primed to change how film, television, and music are imagined and produced.
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