If there’s ever an industry that wrestles with legacy equipment and processes, it is broadcast. “Only they themselves can solve the legacy infrastructure problem,” agrees Chugh. “They need to look at replacing that – but on top of this the outlook towards AI needs to be changed by the leadership. Right now, leaders think of it as a technology problem and hand it over to their CTOs. In reality, this needs to be shared across the organisation – and each department needs to prioritise it. AI isn’t just an overlay above your existing infrastructure, it’s a complete transformation to all the workflows and processes you have.” Neal and his team’s work at RedSquid has only just begun, and as he did with M Star, he is starting to put a pen to that blank sheet of paper. He says: “If you put the team that pioneered the smart TV movement with the team that’s beginning to make a real difference in agentic AI, what can you really create? Television goes in waves. We had analogue, we had digital, we had smart. Those eras come and go. The next era is going to be intelligent.” There is certainly a sense that we are on the precipice of something great when it comes to agentic AI. Minaricova takes us back 20 years to the last time this happened, to demonstrate just how great this might be. “Think back to the nineties and noughties when the internet came along and no one really understood what it could achieve – and how much it would totally transform our lives. Now, here we are 30 years later and the internet plays a central role in almost every area of our lives. “But I like to think of the internet as two dimensional. It’s just information you search through. But agents offer that third dimension; where they go out, armed with information and goals from the owners, and then actively reach out to other agents to achieve those goals.”
homes, and most people aren’t using all that capability. As new applications surface, that unused broadband pipe can start getting truly leveraged. That leads onto the idea of the whole chain beginning to come from broadband operators themselves, where they also supply the display; making sure that Wi-Fi and TV works perfectly with your router – and using AI in the background to help ensure that.” If broadband providers took control of the TV platforms themselves, this could in theory allow more effective monetisation – which aligns neatly with the findings of Chugh’s HFS report. “At the moment, smart TVs monetise largely through user data and home screen advertising,” Neal elaborates. “If the intelligent TVs were supplied by the broadband operators, they’re already monetising through your £20-a-month payment. That therefore means they are able to provide you a much better-quality service, while giving intelligent TVs the potential for the user to have a refreshingly clean viewing experience.” Broadband providers around the world tend to be national companies. Neal believes that, if they sat at the start of the television-set chain, that would keep people’s data both in their television and the country they are watching it from. “The privacy angle is really important because at the minute, every TV you buy on the high street is monetised by a foreign TV platform owner. You have no control over the data it collects about you, or any idea of where it goes.” Is the industry ready? Fears around human oversight and privacy aside, one of the biggest hurdles facing businesses when it comes to effective agentic AI rollout is actually the one already on the track. “What we’re seeing across industries is that enterprises are getting stuck at the pilot stage,” says Chugh. “As a result, they’re unable to reach AI adoption at an enterprise-wide level, where the true value of AI gets unlocked.”
Read the full report from HFS here: hfsresearch.com/ research/growth-wave-reclaim-value
The DREAM framework for establishing AI-native M&E enterprises
Content supply chain Define Across the ecosystem Associate D R E A Data and platforms Reinvent New operating model Establish
Audience persona and KPIs Measure M
l Story-centric production
l Unified data platform
l Agentic AI
l Strategic
l Personalisation
architecture
partnerships
l Automation and collaboration
l Platform
l Governance and org structure
l Compliance and interoperability
l Audience
consolidation
measurement
SOURCE: HFS RESEARCH, 2026
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