AI in Media Operations

AI can speed up media workflows and reduce the burden of repetitive tasks. It also raises new questions: how predictable will the system be, who controls its decisions, and what happens if something goes wrong?

According to Devoncroft Partners’ 2026 Big Broadcast Survey, AI/ML/GenAI ranks second among technology trends in commercial importance to media technology buyers, behind IP Networking & Content Delivery.

Grant Thornton's 2026 AI Impact Survey found that only 17% of surveyed media and entertainment executives reported fully integrating agentic AI into their workflows, while 28.8% had a tested AI incident response plan.

Following IBC2026, Caretta Research noted that end-to-end autonomous AI workflows in media operations remain largely experimental. The main barriers include high and unpredictable AI costs, data quality requirements and the need for broadcast-grade reliability to meet SLA commitments.

One way to reduce these risks is to choose the right technology for each task.

Repetitive operations that follow a predefined sequence can be automated without AI. If this delivers the required quality and reliability, there is little reason to add complexity. AI should be used where it brings additional value, with appropriate controls in place.

Cosmonova Broadcast follows this approach in COSMO | PLAYOUT.

The service combines rules-based automation, AI capabilities and human oversight, depending on the type of operation.

Routine operations are automated according to agreed rules. During media file health checks, the system detects technical issues, notifies the responsible operator and suggests corrective actions. It carries out the agreed actions after approval. Transcoding follows the same principle: the system identifies when transcoding is needed, recommends a course of action and executes it once approved.

AI-assisted dubbing and automated subtitling are supported by editorial review.

Technology handles the operations, while specialists retain control over decisions that affect the output.

AI adoption is not an end in itself. The value of automation depends on how reliable, manageable and predictable the entire media workflow remains.