With the rise of alternate media channels and changing viewer behaviour, TV broadcasters are now providing value add to retain their subscribers.  As consumers demand highly personalized content and flexible viewing experience, it is impossible for humans to manage complexities without cognitive support systems and tools. With such high demands at every stage of the content lifecycle, production houses need to continually update their workflows to stay on top of the game.

The US media and entertainment industry is expected to grow at a CAGR of 3.6% for the next two years. As the industry combats the challenge of getting the right content to the right consumer at the right time, media companies that proactively invest in advanced analytics, AI, machine learning, and blockchain will gain critical first-mover advantage. AI is rapidly being used across several parts of the broadcast production and delivery workflows as well as in the consumer services to enhance the viewing experience and bring forward new monetization opportunities.

Traditional post-production processes are heavily manual and repetitive, which takes a toll on the people doing the work. They can be made more efficient by training an AI model to handle the majority of decisions a human would typically make in a traditional workflow. Some of these solutions include:

OTT & International Distribution Accelerators

By 2020, Gartner predicts that there will be over 82 million millennial digital video customers in the US. With the increasing non-linear media channels, companies are trying to garner on the revenue opportunities from newer OTT channels and increased need for distribution across platforms along with taking it internationally. There are various compliance guidelines that they need to adhere to. The operations team needs to ensure that every visual asset complies to the custom specifications for each platform. Broadcasters, therefore, need to package their content in such a way that it can be consumed easily by any international broadcaster/OTT platform.

Broadcasters can augment their existing media workflows with these features:

  • Audio Conformance
    By performing synchronization detection, AI aligns disparate audio and video elements to ensure smooth flow of a video asset, thus allowing the content to be repurposed at a later stage. This helps broadcasters align a master video feed with proxy audio feeds and automatically generate a single video asset with multiple audio versions. With AI you can automate this process to reduce the total quality control time by 80%. For instance, earlier an editor was taking 45 minutes to edit a 22-minute video file, with AthenasOwl Smart Workflows, we were able to bring down this processing time to 6 mins per file which means that a team of 10 editors were now able to process 100 files in an hour and 800 files in a day which leads to an increase in the team’s speed-to-market by around 80%.
  • Subtitle Conformance
    Multiple language versions of an audio asset are not always in sync because they were created across different geographies. Editors can use AI to align the subtitles in different languages to the corresponding scenes to automatically generate a conformed asset complying with Netflix/OTT standards.
  • Textless Element
    AI identifies shots with overlaid text and subtitles in a show and map those to the corresponding textless (clean) counterparts which enables faster content localization required for international distribution.

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Augmenting post-production with AI

  • Scene Segmentation
    AI is trained to categorize video clips based on location, framing, lighting, audio and automatically identifies the contextual scenes in video content for the creation of promos, teasers, previews, documentaries and more.
  • Highlights Assistant
    AI identifies and compiles highlight-worthy moments of long videos instantly and creates multiple options of auto highlights, without conveying any information that could act as a spoiler. By recognizing patterns in large datasets, AI clusters different video clips into categories, working as a smart assistant to directors.

Business benefits of adopting AI in media workflows

Emerging applications of AI in the media and entertainment industry deliver the most significant benefit over time, improving the efficiency of the production process. As a result of agile and iterative methods, intelligent workflow management is now an integral part of filmmaking, writing, pre- and post-production. Broadcasters, studios, and production houses can leverage this knowledge engineering to automate their processes and make impactful outcomes. For optimum results, seasoned creative directors can continually train AI to improve processes in their system.

AI-assisted  automated workflows can:

  • Increase Speed to market – AI increases the speed to market by optimizing turnaround times and reducing redundant processes in post-production.
  • Improve operational efficiencies in content transformation & QC process – Adopting AI in post-production can ramp up the team’s efficiency by 5X. Automation can free up employee bandwidth so they can focus on more strategic initiatives and drive up operational efficiency.
  • OTT & International distribution readiness – The post-production team gets to make a ready-to-onboard repository of accurately conformed master video feeds, audio feeds, and subtitles for OTT platforms. This drastically reduces the effort involved in manual QC/editing processes.
  • Unlock Content Monetization opportunities – With a metadata-enriched content library, deep search and retrieval not only enables latent content monetization potential but also helps speed up content transformation and delivery through multiple digital platforms in different formats.

AI is the key to keeping your organization competitive, compliant, and efficient. Download our e-guide on Broadcasters’ Ultimate Guide to AI-Assisted Production to take the next step toward your AI transformation.


AthenasOwl is an AI-embedded smart suite for media companies that create and distribute content on linear and OTT platforms. It offers next-gen capabilities such as “deep search” in vast video archives, data-driven insights into audience preference, and automation of several media workflows in post-production and distribution.