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Where AI really fits in broadcast operations

For several years, artificial intelligence has dominated industry conversation. Nearly every new tool, platform or workflow arrived with an AI label attached. As with most technological waves, the early stage was defined as much by expectation as by practical reality.

As we move through 2026, that conversation is beginning to settle. AI is transitioning from a speculative hype cycle into something more useful and more grounded, an operational layer that sits alongside existing systems. That shift matters particularly in broadcast environments, where reliability and precision are non-negotiable.

At Pebble, we take a pragmatic view of where AI can genuinely help. Our core playout technology operates in a world that demands deterministic behaviour. When a channel is on air, every event must happen exactly when it is scheduled to happen. Synchronisation down to the video frame is not a desirable feature. It is the basic requirement for professional broadcast delivery.

That level of precision is still the domain of traditional computing. AI excels where the problem is less rigid, interpreting patterns, analysing large volumes of data, responding to situations that are not perfectly defined in advance. It is comfortable operating where ambiguity exists.

For broadcast operations, those two capabilities are complementary rather than competitive. This is why our strategy is not to place AI at the centre of the playout engine. The opportunity lies in surrounding deterministic systems with intelligent layers that can assist operators, improve visibility and help manage growing operational complexity.

Modern playout environments generate a vast amount of telemetry. Systems continuously report status information, performance indicators and operational events. Historically, monitoring platforms have relied on alarms and thresholds, alerting engineers only when something has already gone wrong.

AI provides the opportunity to move beyond that reactive model. By analysing telemetry in real time, intelligent monitoring layers can recognise patterns that suggest a potential issue is developing. Rather than simply raising an alert, the system can highlight the likely cause and suggest the next best action for the operator. The goal is not to remove the human from the process, but to reduce the cognitive load involved in interpreting large volumes of operational data.

There is also a practical case for AI in routine operational management. Broadcast facilities often run continuously, including overnight periods where activity levels are lower but vigilance is still required. Through carefully designed interfaces and control APIs, it becomes possible to introduce a human-in-the-loop model, where AI systems handle predictable operational tasks while escalating unusual situations to human supervision. This preserves control while allowing teams to manage increasingly complex infrastructures without proportional increases in staffing.

AI also makes possible specialist integrations that would previously have required entirely separate workflows. Real-time caption generation, automated metadata enrichment and other forms of intelligent media analysis are evolving rapidly. By working with specialist providers, these capabilities can be incorporated into existing broadcast environments in ways that complement rather than disrupt.

The impact is not limited to the products we build. It is also changing how we build them. AI-assisted coding tools are becoming genuinely capable, helping engineers navigate large codebases, accelerate testing and improve quality assurance. Used carefully, they give experienced developers better tools to work with. In a software-driven industry, improvements in development efficiency ultimately translate into more resilient products and faster delivery of new capabilities.

AI will undoubtedly continue to evolve. New techniques and architectures will emerge, and some of today’s limitations will gradually diminish. But the most productive way to approach it now is not as a universal solution, but as a set of tools that can enhance specific parts of a workflow.

In broadcast operations, deterministic systems remain the foundation of reliable delivery. Around that foundation, there is significant room for intelligence to improve how systems are monitored, managed and scaled.

If the past few years were about discovering what AI might become, the next few will be about learning how to apply it responsibly in real operational environments. That is where real value will emerge.

An editorial view from Pebble

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Why broadcast technology is no longer the hard part 

For most of broadcasting’s modern history, progress was defined by technical constraint.

Could systems stay on air without interruption? Could devices be synchronised precisely? Could storage, processing and networking cope with growing channel counts? For decades, competitive advantage came from overcoming engineering limitations. If you could make the technology work seamlessly, you were ahead.

Today, that is no longer the defining constraint.

Modern computing power is extraordinary. Virtualisation is mature. IP transport is proven. Automation platforms are sophisticated and resilient. Monitoring is richer than ever. From a technical perspective, the industry is remarkably capable.

And yet, across broadcasters, service providers, streamers and vendors alike, there is a shared sense that the environment has become more difficult, not less.

That tells us something important.

The hardest challenges facing our industry in 2026 are not technical. They are commercial, structural and cultural.

For broadcasters, the pressure is obvious. Advertising models are shifting. Rights costs continue to rise. Audiences are fragmented across platforms. Delivering seamless channels is no longer enough; the question is how to monetise them sustainably.

For streaming platforms, the realisation has been equally stark. Moving into premium live content exposes operational complexity that cannot be hidden behind user interfaces. Reliability expectations are broadcast grade, whether the business originated online or not.

Service providers and playout centres face their own tension. Customers demand flexibility, regionalisation and rapid deployment, but without proportional increases in cost. Scaling capability without scaling overhead has become a daily balancing act.

Even vendors are not immune. The pace of innovation is relentless, yet customers are more cautious. Investment cycles are longer. Procurement scrutiny is sharper. The consequences of failure, technical or commercial, are simply higher than they used to be.

There is also a persistent assumption across the industry that the next platform shift will unlock the next wave of revenue. Cloud, FAST, IP, streaming, virtualisation – each has been presented at some point as transformative.

In reality, technology enables opportunity. It does not guarantee commercial success.

Automation makes scale possible. IP makes distribution flexible. But none of these tools define strategy. They support it.

A pattern we see regularly across our customer base is that broadcasters are not struggling to make the technology work. The real challenge is aligning operational systems with changing commercial priorities, whether that means launching new services quickly, regionalising content, or managing costs more tightly.

At Pebble, we see this reflected in the long-term relationships we build with broadcasters, service providers and technology partners. In complex operational environments, trust, transparency and a shared understanding of workflows often matter as much as the technology itself.

The uncomfortable truth is that most organisations in our sector are not constrained by what their technology can do. They are constrained by clarity of direction, by structural complexity, and by the difficulty of aligning operational capability with commercial intent.

This is where leadership becomes decisive.

The organisations that will thrive are not those chasing every new technical development. They are those disciplined enough to decide what not to pursue. They will simplify where others complicate. They will align teams around clear outcomes rather than new features.

Partnership also becomes more significant in this environment. When markets are stable, supplier relationships can be transactional. When markets are volatile, long-term trust matters. Broadcasters, streamers, service providers and vendors all benefit from stability and transparency across the ecosystem.

Our industry has successfully solved many of the engineering problems that once defined it. Reliability, resilience and precision are now established disciplines.

The harder question facing all of us is not whether we can build it.

It is whether we can build businesses around it that remain viable in a far more competitive world.

Peter Mayhead, Pebble CEO

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