🧠 AI Automates Television Workflows

Today, in a television landscape driven by massive content volumes and tight deadlines, manual processing is no longer scalable. In this environment, AI has evolved from a “trendy accessory” into a highly practical tool that directly drives speed, cost reduction, and process management.

AI as Core Digital Infrastructure

The primary value of deploying AI in the media industry lies in its ability to handle routine tasks along the everyday technological value chain.

“We view artificial intelligence not as an experiment, but as an element of core digital infrastructure for the media industry. The focus of the Mediabaza B2B industry platform is on practical tasks that cannot be efficiently handled manually given massive content volumes and rapidly evolving regulatory requirements,” emphasizes Grigory Kuzin, Director of Media Platforms at MSK-IX.

Integrating AI into streaming workflows delivers measurable economic and operational impacts: it accelerates broadcast preparation, lowers the cost of routine operations, and reduces the number of scheduling revisions.

One of the most mature areas of automation is content compliance monitoring, implemented via a “compliance by design” approach. Verifying video, audio, and context for regulatory compliance is now embedded directly into the production cycle. Neural networks automatically detect profanity and generate timecodes for edits, while also removing artifacts and blurring brand logos, alcohol, and tobacco products.

Localization and Reducing Time-to-Market

In an environment of fierce competition among video services to retain viewer attention, time-to-market has become a critical metric. Satellite operators and online platforms are leveraging AI for the instantaneous localization of international releases.

For instance, within the Mediabaza Mdisk cloud storage ecosystem, a rights holder can upload a new episode of a foreign-language series and receive a finalized version with translated subtitles—fully compliant with Russian state standards (GOST)—within an hour. This enables global premieres to debut in Russia day-and-date with their original release.

According to Max-Media, automated transcription and translation cut content preparation time from several hours down to thirty minutes per asset.

AI Across All Production Stages

Neural networks are currently deployed at every stage of the television product lifecycle.

• Pre-production and Ideation: The Yarko animation studio (part of Gazprom-Media) uses AI to source visual references and build pitch decks, while 1-2-3 Production utilizes it to illustrate script treatments. At the NTV Style channel, AI generates initial visuals and mood frames. According to Dmitry Romakhin, Chief Director of NTV’s Thematic Channels Department, this allows the creative team to visualize an idea in motion and color beforehand, avoiding costly reworks during the final stage. The thematic channels Moto Drive and Extra TV have used AI to fully synthesize voiceovers and generate visual avatars for on-screen presenters.
• Packaging, Promo, and Audio: Channels are adopting a hybrid approach that synthesizes AI and manual motion graphics. In audio production, neural networks successfully generate musical beds, transitions, and jingles for the editing bay.
• Post-production and Archival Work: AI effectively executes precise visual adjustments, such as face replacement and generating seamless frame transitions. A standout example of archival optimization is the deep remastering of the legacy series The Return of Mukhtar by the Gazprom-Media holding, where the 20-year-old project was fully upscaled to HD and reformatted to a modern 16:9 aspect ratio.

Human Editors Retain Final Control

Although the utilization of AI reduces media production costs by an average of 30%, industry executives unanimously agree that neural networks will not replace human professionals. The primary deterrents are the exceptionally high cost of editorial and creative errors, alongside the algorithms’ tendency to “hallucinate.”

Alexander Zharov, CEO of Gazprom-Media, explicitly outlines the conglomerate’s stance: AI is uniquely valuable for accelerating routine processes, but it cannot be trusted with final decisions due to the risk of generating misinformation. In creative execution, curation, narrative structure, and artistic discretion, accountability remains entirely with creative teams, producers, and editors.