Broadcasting is being reshaped by platform economics, as the old linear chain of producers, distributors and audiences gives way to multi-sided digital ecosystems that connect creators and consumers more directly. The change is being driven by cloud computing, AI-based recommendation systems and richer analytics, which are allowing newer digital-native operators to improve discovery, increase engagement and take more of the value created around content.
The shift is also exposi...
Continue Reading This Article
Enjoy this article as well as all of our content, including reports, news, tips and more.
By registering or signing into your SRM Today account, you agree to SRM Today's Terms of Use and consent to the processing of your personal information as described in our Privacy Policy.
ng how much of broadcasting’s traditional model depends on friction. Rights are often split by territory, language, device and window, while measurement remains inconsistent and commercial terms are frequently opaque. That creates space for platforms that can simplify access, aggregate inventory and make audience behaviour more visible to buyers and sellers. In practice, the winners are those that can combine distribution, data and monetisation rather than merely carry content from one party to another.
This is already visible in the growth of streaming, FAST and connected TV operations, where broadcasters are increasingly acting like full-scale digital publishers. Industry commentary published by NewscastStudio in April said broadcasters are demanding greater transparency over audience data, revenue attribution and performance metrics, as control over the user experience becomes more important than old-style carriage relationships. That reflects a broader reality: distribution alone is no longer enough, because audiences now expect instant access on every device, and media companies are being pushed to rethink workflows, cloud infrastructure, advertising and analytics.
AI-led content discovery is becoming central to that effort. ThinkAnalytics says its recommendation platform generates more than 8 billion recommendations a day and is used across live, VOD, catch-up, FAST and OTT services in hundreds of millions of homes and devices. The company says its system uses deep learning and enriched metadata to personalise viewing and reduce churn, while also lifting advertising performance and viewing time. Parrot Analytics makes a similar case with its own AI-driven audience intelligence tools, arguing that unified data across linear, streaming, mobile and web can help media organisations sharpen recommendations and commercial decisions.
But the strategic stakes go beyond better personalisation. According to industry commentary from the International Screen Institute in Europe, OTT did not kill broadcasting so much as force it to change the rules, pushing the sector towards more flexible ecosystems rather than a simple contest between old and new. That has consequences for channel operations too. Mediagenix has warned that programming at scale is reaching a breaking point, because many workflows still assume a simpler broadcast era even as content multiplies across business models, markets and audience segments.
For broadcasters, the opportunity lies in building platforms that can manage that complexity. The more data, metadata and workflow control they possess, the better positioned they are to optimise content packaging, target advertising and attribute revenue accurately. The risk is that legacy operators who fail to modernise will be left with weaker margins, less audience insight and little influence over how value is captured elsewhere in the ecosystem.
Source: Noah Wire Services
