Automation in broadcast: The line between empowerment and overreach

The media and broadcast sector has always been an early adopter of workflow automation – and for good reason. From master control playout to newsroom Media Object Server (MOS) workflows, the industry has spent decades streamlining processes in the pursuit of greater reliability and less human error.

But the recent surge in AI-driven automation often marketed as ‘transformative’, but sometimes feared as ‘disruptive’, had pushed the conversation into a different territory. This surge rings true in the stats – according to a report by Thunderbit, the global industrial automation and control systems market is expected to hit a whopping $226.8 billion in 2025 – up from $206 billion in 2024 – with a projected 10.8% compound annual growth rate (CAGR) through 2030.

Vendors promise smarter diagnostics and predictive failure analysis. Broadcasters promise their teams will be freed from repetitive maintenance tasks. But the question remains: at what point does automation stop helping and start overrunning the human element?

From reactive to proactive

One of the biggest drivers behind the push for automation is the complexity of modern media infrastructures. Distributed operations and mixed estates of AV and broadcast, all strain small engineering teams.

Nicole Corbin, VP of product at Utelogy, describes it plainly: “We see our role as helping organisations move from manual operations to smarter, automated workflows that are easier to manage.”

In both corporate media studios and broadcast-adjacent environments, teams still lose time to system checks, device routing or repeated troubleshooting. Corbin says the opportunity lies in automating the predictable work so staff can shift their focus elsewhere: “Our goal is to automate the predictable parts of those workflows so AV/IT teams can focus on their larger initiatives, not repetitive technical maintenance.”

This emphasis on predictability is important. The emerging view is that automation shouldn’t attempt to reinvent human judgement but instead handle the routine technical steps that consume too much of it.

AI expansions

While rule-based logic still underpins the bulk of production workflow automation, AI is increasingly taking on tasks that historically required human oversight. Corbin explains that today’s customers lean heavily on ‘rule-based workflows, scheduled actions, self-healing based on triggered events and automated health checks,’ but the real change is only just beginning.

Utelogy are now investing in predictive and agentic AI models. As Corbin puts it, they’re developing ‘models that can spot early signs of failure before they affect users, and agentic AI that can take contextual actions automatically, such as running diagnostics or initiating remediation steps.’

Broadcasters experimenting with similar systems describe immediate benefits: fewer false alarms, faster root-cause analysis and less time spent repeating the same fixes across dozens or hundreds of devices.

The biggest payoff, Corbin says, is reducing repetitive operational work. “Daily system tests, remote troubleshooting, alert triage and even the repetitive ‘fix-once-a-day’ tasks that can be automated safely and consistently.”

Managing mission-critical

In live production or broadcast operations, seconds matter – and a minor configuration failure can quickly escalate.

“Reliability improves when you eliminate assumptions about the room,” Corbin notes. Automated workflows that validate connectivity, confirm device health or flag anomalies, give operators the visibility they need before a show or recording goes live.

Instead of discovering an issue at the worst possible moment, automation offers a buffer. According to Corbin, “Teams get early warnings, self-heals and remote remediation capabilities.” When something does go wrong, ‘automated remediation such as reboots, configuration resets or failover routing can address many issues instantly.’

For broadcast networks with lean technical teams, this layer of resilience is becoming indispensable – as long as automation enhances rather than replaces the engineers who oversee it.

Beyond operational reliability, automation plays a growing role in meeting organisational sustainability goals. Corbin points out that automation can ‘directly support sustainability by powering down unused spaces, adjusting device behaviour based on occupancy, and reducing unnecessary runtime on displays, lighting and back-end hardware.’

These savings scale quickly across large estates, especially in media facilities running dense clusters of screens and remote studios. Even simple routines like after-hours shutdowns or occupancy-based room consolidation can reduce significant waste.

Combined with usage analytics, these insights help organisations make more strategic decisions about redesigning rooms or retiring underutilised devices.

As Corbin explains, this ‘aligns well with current sustainability priorities in European and global markets.’

Open architectures unlocking scalability

One concern frequently raised in discussions with broadcasters is interoperability. In an industry built on long-life hardware and mixed-generation systems, automation is only as strong as the data and control pathways it can reach.

Utelogy’s hardware-agnostic philosophy echoes a broader trend across the sector: vendors increasingly rely on open APIs, modular drivers and normalised data models to ensure longevity.

“Interoperability at scale comes from focusing on open standards, APIs and a modular driver framework rather than locking customers into specific brands,” Corbin says. Automation workflows shouldn’t need to know ‘whether a camera, display or switch came from manufacturer A or B.’

That abstraction layer, she argues, is what enables customers to build automated processes that survive hardware refresh cycles and evolve over time.

Analytics are no longer a ‘nice to have’, they are the foundation for intelligent automation. Corbin is explicit about this: “Analytics are the backbone of intelligent automation.”

Telemetry, usage patterns and performance data increasingly dictate when automations should trigger and why. Instead of relying solely on scheduled routines, systems can react to real conditions. Corbin gives a practical example: “If a space becomes occupied or unoccupied you might want to trigger the room to start up, or potentially release a scheduled meeting to open the space.”

Just as importantly, analytics help teams refine automations over time by showing whether they reduced alerts, accelerated response times or cut energy use. That feedback loop is key to achieving the right balance between helpful automation and over-automation.

When is enough, enough?

For many organisations, this is the defining question, and one increasingly heard in broadcaster engineering rooms. Automation can be a double-edged sword: helpful when transparent, frustrating when over the top.

Corbin emphasises the need for ‘transparency and clear boundaries.’ Automation should ‘support teams, not override them.’

Utelogy designs workflows so humans set the rules and thresholds while the systems execute the repetitive actions. “Critical changes and potentially disruptive actions remain opt-in and supervised,” Corbin notes. The goal is ‘not to replace operators or engineers, but to give them reliable and predictable tools that remove the noise from their day, while leaving expert judgement firmly in human hands.’

Looking forward, the most exciting developments revolve around agentic AI systems capable of reasoning through problems and selecting the best response autonomously. Corbin sees enormous potential in ‘systems that understand context, reason through problems and take responsible actions across complex environments.’

Paired with predictive models, she envisions a future ‘where AV and media systems can self-diagnose, self-correct and communicate clearly with operators.’ Automation won’t eliminate human roles – it will elevate them. As Corbin puts it, the ultimate goal is ‘an environment where spaces operate reliably with minimal friction, and teams spend their time on creative and strategic work – rather than fighting fires.’

Check out the rest of the December Signal here.