Recent debate around artificial intelligence in the audiovisual industry has largely centered on creative questions: Can it write scripts? Will it replace actors? Can it generate images from scratch? Yet while panels at international content markets debated its impact on creators, the real transformation has been unfolding quietly inside distribution and sales teams.

Today, the industry’s most significant shift is taking place not on set, but at the negotiating table and across the global content distribution business. AI is no longer just a creative promise—it has become the technology redefining how catalogs are managed, how content is localized, and how licensing deals are identified, negotiated, and closed.

According to PwC’s Global Entertainment & Media Outlook 2026–2030, the industry’s future growth will depend on companies’ ability to integrate data and artificial intelligence across the entire value chain.

“AI has evolved from an experiment into an integrated operational capability. The challenge is no longer testing the technology, but identifying where it creates a genuine competitive advantage. In distribution, that advantage lies in selling with greater precision,” Deloitte said in its latest analysis.

Traditionally, an international sales catalog was little more than a static database containing titles, synopses, technical information, and a handful of production materials. AI has transformed it into an intelligent, dynamic asset.

By automatically analyzing thousands of hours of content, AI can identify characters, recognize locations, classify emotions, generate episode summaries, and tag genres without human intervention. For buyers, this fundamentally changes the discovery process.

Semantic search: Buyers no longer need to sift through hundreds of PDFs or screener lists. Instead, they can perform highly specific searches—for example, “family dramas set in rural communities with suspense-driven storylines”—and instantly identify relevant titles.

Greater content discoverability: Titles no longer depend solely on a sales executive’s memory or availability. Instead, the intelligence built into the catalog surfaces the most relevant content based on each buyer’s needs, making libraries significantly easier to navigate and monetize.

For years, adapting a high-end drama or an entertainment format for dozens of international markets meant weeks of work—and significant costs—for translation, subtitling, dubbing, and quality control.

Today, generative AI is fundamentally changing that process. Leading localization companies such as Deluxe, Iyuno, and TransPerfect have adopted hybrid workflows in which AI generates first-pass subtitles, translations, and lip-synced dubbing, while human specialists refine, validate, and approve the final versions.

The business impact is significant:

Faster release windows: Distributors can now present buyers with subtitled or dubbed screeners in a matter of hours rather than weeks, accelerating negotiations and shortening the path to licensing deals.

Expanding commercially viable markets: Mid-sized and smaller territories that were once considered uneconomical because of localization costs can now be served profitably, opening new revenue opportunities for distributors and rights holders.

One of the clearest examples is Banijay Entertainment. The company has forged a strategic partnership with AWS and Base to migrate more than 200,000 hours of content to an AI-optimized cloud infrastructure.

The goal was not to use AI to create content, but to transform one of the world’s largest audiovisual libraries into a smarter business asset. The initiative enables automated metadata indexing, intelligent search capabilities, enhanced collaboration across international teams, and new opportunities for content monetization.

Personal relationships will remain at the heart of international markets such as MIPCOM, Content Americas, and NATPE. But today, they are increasingly being enhanced by predictive analytics.

New AI-powered systems analyze platforms’ acquisition histories, historical genre performance across territories, and audience trends to recommend exactly which projects distributors should pitch to specific buyers. Welcome to the era of intelligent matching.

At the same time, enthusiasm is tempered by caution. While AI dramatically accelerates workflows, it still requires human oversight. Cultural adaptation, intellectual property rights, and translation quality remain among the industry’s biggest challenges.

This reflects a growing consensus among media executives: automation should drive efficiency, while human expertise safeguards creative value. The competitive advantage will not come from using more AI—but from using it more effectively.

Companies including Deluxe, Iyuno, and TransPerfect are already applying this hybrid approach to localization and distribution, combining generative AI with human review across dubbing, subtitling, and multilingual quality control workflows.

One of the industry’s biggest long-standing challenges has been what many executives call “sleeping content”—thousands of hours of programming that become underutilized once their initial distribution window closes. By enriching metadata and dramatically improving discoverability, AI is bringing previously overlooked titles back into view within massive content libraries.

As a result, monetization is no longer driven solely by new releases. It increasingly depends on rediscovering existing intellectual property and matching it with new buyers, streaming platforms, and FAST channels. It’s no coincidence that the largest AI investments by major media companies are focused on library management as much as on content creation.

The past decade was defined by the streaming wars and an industry-wide race to produce more original content at almost any cost. The next decade will be defined by sales efficiency.

Artificial intelligence in content distribution isn’t designed to generate headlines—it is designed to generate revenue. In an environment where financial optimization has become a strategic priority, the winners won’t necessarily be the companies using the most AI to write scripts. They will be the ones using AI most effectively to transform their content libraries into long-term revenue-generating assets.