CES 2026 Reflections: Media AI at the Edge

Turning hype into real value for pay TV and media operators

Connected Devices, Consumer Electronics, Edge AI, Media, RDK

Before we dive into the why and how, here’s the what: at CES 2026, Qualcomm unveiled the AI Media Station – a proof-of-concept next-generation set-top box powered by the Qualcomm Dragonwing™ QCS8550 processor that showcased what’s possible when bringing advanced on-device AI to the heart of the living room.

It’s not a concept video or a slide deck. It’s a real, functioning solution that shows what’s possible when intelligence moves to the edge. Working alongside KTC, Consult Red played a pivotal role in bringing the AI Media Station to life, from shaping media AI use cases to designing and developing new user experiences.

This article explains why on-device AI at the edge matters, what it enables, and how operators can turn hype into measurable business outcomes. But if you want to see the future in action, start with the video. Then come back and read how we make it real.


Why This Matters Now

Artificial Intelligence (AI) dominates headlines. Every major tech event, every industry blog, every analyst report seems to promise that AI will transform everything. For Pay TV and media operators, the question isn’t if AI matters – it’s how to make it work in the real world without breaking budgets or adding complexity.

The reality? Most AI initiatives stall. They sound exciting in boardrooms but fail to deliver measurable outcomes because they’re too expensive, too cloud-dependent, or too disconnected from the operator’s core business.

At Consult Red, we believe AI should do more than generate gimmicky hype. It should generate revenue, reduce costs, and improve the customer experience. We focus on media AI at the edge – a practical, scalable way to bring intelligence closer to the user and unlock real business value.


The Pressure on Pay TV Operators

The ‘traditional’ Pay TV market is under strain. Operators face:

  • Subscriber churn as streaming platforms compete for attention.
  • Rising operational costs driven by cloud infrastructure and bandwidth demands.
  • Demand for innovation from customers who expect voice control, personalisation, and seamless UX.

AI promises solutions to these challenges. Smarter recommendations, voice-first interfaces, predictive maintenance and support – all sound great. But here’s the catch: most AI deployments rely heavily on cloud processing, which means high latency, data privacy concerns, and unbounded costs (the more popular your AI feature is, the more your operating costs will increase).


The Edge Advantage

Media AI at the edge changes the economics and the experience. Instead of sending data to the cloud for processing, intelligence happens locally – on the device in the subscriber’s home.

Why Edge AI Works for Pay TV

  • Lower latency: Real-time responses for voice commands and interactive features, important for use cases such as upscaling or real-time translation (<50ms for Edge processing vs. +100ms for Cloud).
  • Privacy compliance: Sensitive data stays local, reducing regulatory risk.
  • Reduced cloud dependency – and lower cost: Processing at the edge means fewer cloud calls and lower operating costs (no per-transaction fees).
  • Better user experience: Voice-first navigation, personalised content, and faster UI.

While on-device AI is quicker, cheaper and more secure, it’s important to recognise that not every use case can be handled locally. Some complex or resource-intensive tasks, such as deep video analysis or large-scale data modelling, still require cloud processing.

In reality, the most effective approach is a hybrid architecture that combines on-device intelligence for speed and privacy with cloud capabilities for heavy lifting. This balance ensures operators get the best of both worlds – performance and scalability without compromising cost or user experience.

Hybrid AI Processing - SLM | LLM | Cloud

ApproachBenefitsDrawbacks
Edge AI
(On-Device)
  • Ultra-low latency for real-time UX (voice, gesture, presence)
  • Strong privacy: data stays local
  • Lower ongoing cloud costs
  • Works offline or with limited connectivity
  • Limited by device processing power
  • Complex AI models may not run efficiently
  • Updates and scaling can be harder across large fleets
Cloud AI
  • Virtually unlimited compute for complex tasks
  • Easier to update and scale globally
  • Centralised data for advanced analytics
  • Higher latency for interactive features
  • Ongoing bandwidth and unbounded cloud costs
  • Privacy concerns with sensitive data
Hybrid AI
  • Best of both worlds: speed and privacy for local tasks, heavy lifting in cloud
  • Flexible architecture for evolving use cases
  • Easier to optimise cost-performance balance
  • More complex to design and manage
  • Requires robust orchestration between device and cloud
  • Potential integration challenges

Return on Investment Chart - Cloud vs. Edge vs. Hybrid AI

Why It’s Viable Today

These benefits aren’t just theoretical. They’re achievable because of the powerful on-device AI processing capabilities now available in consumer-grade hardware. The Qualcomm Dragonwing™ QCS8550 processor brings advanced neural processing directly to the device, enabling real-time voice control, gesture recognition, and a personalised UX without relying on the cloud.


From Concept to Reality: CES 2026 Demo

At CES 2026, Qualcomm unveiled the AI Media Station, a full-stack demonstration of on-device AI in action. This wasn’t a lab experiment – it was a working solution designed for Pay TV operators.

Take a look as Matt Clayton (Solution Architect, Consult Red) walks you through the full demo from CES.

What We Delivered

  • Experience: Voice-first UX reimagining content discovery with conversational content exploration, alongside user recognition and content personalisation.
  • Platform: Built on RDK-V, an advanced open software platform for Pay TV devices, with extended application support.
  • Interface: Custom, high-performance Flutter UI for flexibility and speed.

Qualcomm’s trust in Consult Red to deliver this integration reflects our proven ability to turn advanced technology into a viable solution for real-world operator environments.


Practical Use Cases: What Edge AI Enables Today

Here’s where it gets exciting. On-device AI isn’t just about speed and privacy; it unlocks experiences and services that were previously out of reach. All of these are viable today with the right strategy and investment.

AI-Enhanced User Experiences

Imagine this: you walk into the living room, and the TV recognises who’s present. The UI adapts instantly – your favourite shows front and centre, recommendations tailored to your profile. That’s viewer presence and demographics at work.

Or picture this: you say, “Go to the T-Rex scene” while watching a film, and the system jumps straight there. Or “Turn on subtitles” without fumbling through menus. That’s natural-language navigation, powered by edge AI.

Fitness apps on TV? No problem. Gesture control tracks skeletal movement for workouts, education, or gaming – without sending video to the cloud.

Household profiles? Face or Voice recognition personalises the experience for consenting members, keeping it private and secure.

And for accessibility? Live subtitling and on-device translation make content inclusive for everyone, without latency or cloud dependency.

AI-Enabled Value-Added Services

Edge AI isn’t just about entertainment – it’s also about enabling new revenue streams.

  • Shoppable video: Spot a brand in a show? A QR code pops up for instant purchase. Contextual commerce, triggered locally.
  • Targeted advertising: Hyper-targeted ads at the household or individual level, with granular consent and clear value exchange.
  • Home security: Doorbell camera detects a visitor and announces who’s at the door via your TV – processed locally for privacy and cost savings.
  • Telehealth and ageing in place: Fall detection, routine-change alerts, and live subtitling for video calls – all handled on-device.
  • Home automation: Presence-aware smart home orchestration using Matter/Thread, with dashboards for control.

These aren’t futuristic ideas – they’re practical, commercially viable applications that media AI at the edge makes possible today.


Why Consult Red?

We’re not just technologists. We’re enablers. Our role is to take operators from “AI sounds interesting” to “AI drives measurable value”. How do we do that?

  • Consultancy and business case development: We help you identify where AI delivers ROI.
  • Rapid prototyping:  To secure early stakeholder buy-in.
  • Practical implementation: From architecture to deployment, we make it real.
  • Trusted partnerships: Qualcomm chose us for innovation. That speaks volumes.

Our mission is simple: turn complexity into clarity and hype into outcomes.


The Business Impact

Edge AI isn’t just a technical upgrade. It’s a commercial lever:

  • Cost savings: Reduced reliance on cloud infrastructure means lower ongoing costs.
  • Customer retention: Better UX keeps subscribers engaged.
  • Revenue growth: Personalised services open new monetisation paths.

What Could Go Wrong – and How We Handle It

What’s the biggest objection we hear? “This sounds complex.” And it’s true – AI projects can be daunting. But here’s the reality: investing in AI isn’t all or nothing. With Consult Red on board, you can move at a pace that fits your business. We start small and build confidence, step by step:

  • Business case first: Identify where AI delivers measurable ROI.
  • Proof of concept: Validate the idea before committing big budgets.
  • Trial or experimental deployment: Test in a controlled environment.
  • Full rollout: Scale when you’re ready, with risk managed at every stage.

This incremental approach means you never have to bet the farm. You can learn, adapt, and grow into AI without disruption, while we handle the complexity so you don’t have to.

Ready to explore edge AI?

Media AI on device, at the edge, is no longer a future concept. It’s a competitive advantage. If you’re ready to cut through the hype and discover what edge AI can do for your business, book a discovery session with our team today.