Veritone – So, Your Content Is Finished…Now What?

Veritone – So, Your Content Is Finished…Now What?

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Veritone – So, Your Content Is Finished…Now What?

Fri 06, 10 2023

Veritone – So, Your Content Is Finished…Now What?

AI’s influence in media: managing and monetizing completed content

Paul Cramer, Managing Director, Broadcast Solutions at Veritone, Inc.

Media has come a long way from its traditional production journey. The advent of artificial intelligence (AI) has revolutionized the previously linear path of content production, transforming the process by creating new efficiencies and allowing content to have a second life beyond its initial creation and broadcast.

With AI’s robust capabilities in tagging, managing, and preparing content, production teams can now maximize content usage while optimizing resources, creating a more reliable flow of content even in times of high demand or disruption. In this article, I’ll delve into the evolving media ecosystem, highlighting the role of AI in content management, monetization, and the industry’s future.

The evolution of media

In the past, completed content was confined to one-time use, primarily destined for theaters or television. It would then be confined to physical archives or trotted out for reruns or home video. Later, with the advent of technologies such as the cloud and streaming, content could more easily get a second life. But this process often neglected underused content that rights holders may not have known was in their archives. In addition, it neglected additional footage, from alternate takes to B-roll footage, that can have a myriad of uses for those who license content.

Now, with the integration of AI, the workflow has shifted to a more dynamic process. Content can be mined from archives by automating the tedious, resource-heavy, and error-prone process of metadata tagging and management. So, not only can content be tagged with relevant metadata at the point of ingest, older, archival content and unused footage can be surfaced via that same technology, opening a myriad of new possibilities.

The changing landscape of content management

Traditionally, content creation was constrained by limited use, hindering its potential reach and impact. However, with AI’s ascension, media can now leverage completed content in a variety of additional ways and formats, reaching broader audiences, creating better customer experiences, and generating more business value.

By leveraging AI-powered digital asset management and creative tools, production teams can optimize their content usage by strategically recycling, renewing, or recreating it. The ability to localize content further increases its appeal to diverse audiences, initiating the cycle anew in a managed and monetized manner.

And with this increased level of optimization, teams can focus on the creative aspects of content production as well as distribution strategy, enhancing overall productivity and content revenue—and preventing unnecessary burnout.

Another example of how AI maximizes content usage can be seen through the automation of promos to a larger scale with the help of generative AI. Generative AI technology can automate or streamline the creation of promos, trailers, and teasers, helping production teams to create these assets on a larger scale while also catering to diverse platforms and audiences, and enhancing the content’s promotional reach.

Much like content creation, the landscape of content management has changed drastically from its traditional workflow, making way for a new avenue for keeping up with modern content demands and creating more opportunities for accessing and repurposing content in the future.

How AI-powered workflows play out in real life

It’s easy to get lost in the hypothetical when it comes to incorporating AI into content workflows, so it’s helpful to look at some high-profile use cases. One success story follows the San Francisco Giants and the club’s legacy project, which was initiated in 2020 in an effort to share content with fans during pandemic lockdowns, a time when little to no new baseball content was being produced.

With the help of an AI-powered digital asset management tool, the Giants were able to automate the process of tagging recently digitized analog content from the past 60 years—a process the club estimated would take 15 interns an entire year to complete. This digital asset management tool enabled the team to quickly tag, manage and access all of its branded content in a fraction of the time, allowing the club’s production team to start creating content for fans during a time it was needed most.

Monetizing completed content

The rise of streaming platforms has breathed new life into old content, giving it a second chance to reach audiences. Streaming’s global reach and on-demand nature have provided a new revenue stream for content creators and distributors—one that has surged in popularity and need since 2020. But with that increased demand comes the need to better organize, discover, and monetize a greater cross-section of content archives than ever before.

Disruptions such as the COVID-19 pandemic and the Writers Guild of America strike have caused major setbacks in content production and distribution. However, AI technologies have offered innovative solutions to address these challenges, ensuring continuity in content delivery.

AI-driven automation and remote collaboration tools have allowed production teams to continue their work despite physical barriers, showcasing AI’s resilience in the face of unforeseen obstacles.

In an era in which content can have a prolonged life cycle, strategic planning becomes essential. Content creators must focus not only on old content and reruns but also explore their archives for unreleased or unseen material that can still captivate audiences while providing new monetization opportunities. By thoughtfully planning the release and licensing of content, creators can maximize revenue and audience engagement, transforming seemingly outdated content into valuable assets.

Unlocking hidden gems: leveraging archived footage

Content archives can hold hidden gems that have never been seen or released before. By tapping into these archives and curating fresh content, broadcasters can provide audiences with unique and exciting viewing experiences.

Some options include:

  • Legacy footage: As mentioned in the San Francisco Giants case study, archived footage can be accessed to create legacy projects, introducing past footage to new audiences.
  • Licensing opportunities: Once content goes live, licensing it for distribution offers additional revenue streams. AI-driven platforms can assist in identifying potential licensing opportunities and efficiently managing licensing agreements.
  • Creating a content marketplace: Establishing a marketplace for completed content, clips, and B-roll footage allows content creators to monetize assets that might not have been used in the primary production. AI can help manage and organize these resources, ensuring a smooth exchange between content buyers and sellers.

However, in order for content archives to work in an organization’s favor, the content must be tagged well and made easily searchable and accessible.

Ensuring efficient content retrieval

The success of content management relies on effective archiving systems. AI-driven tools enable intelligent content tagging and categorization, simplifying content retrieval and usage. In a fast-paced media landscape, quick content retrieval is crucial. AI’s ability to search and locate specific footage within vast archives reduces downtime and maximizes productivity.

While AI presents immense possibilities, it is imperative to ensure that the solutions implemented are user-friendly and operable. Streamlining AI integration ensures that production teams can fully leverage AI’s potential without facing unnecessary complexities.

Closing thoughts

The evolution of media with the integration of AI has resulted in a transformative shift in content management and distribution. AI’s capabilities in optimizing resources, automating processes, and ensuring efficient content retrieval have reshaped the industry.

As AI continues to advance, it will play an increasingly critical role in the media industry. AI-powered systems will likely become more sophisticated, enhancing content discovery, audience engagement, and revenue generation.

The synergy between AI and media has unlocked endless possibilities, enabling content creators to reimagine their approach to production, distribution, and monetization. By leveraging AI technologies effectively, production teams can navigate the ever-evolving media landscape and deliver captivating content to audiences worldwide.

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