AI Use Cases in Hollywood

What’s Possible Now and Where It’s Going

Starting April 2025, all full posts, including archived posts, will be available on my Substack, The Mediator.

Over the last nine months, I’ve been writing about why several new technologies, especially AI (including generative AI), are poised to disrupt Hollywood in coming years by lowering the barriers to high quality video content creation. (See The Four Horsemen of the TV Apocalypse and Forget Peak TV, Here Comes Infinite TV). The one-sentence summary: the last decade in film and TV was defined by the disruption of content distribution and the next decade will be defined by the disruption of content creation.

That’s pithy and all, but it also raises a lot of questions too. In a recent post, for instance, I addressed how fast and to what extent Hollywood may ultimately be disrupted (How Will the “Disruption” of Hollywood Play Out?)

In this post, I try to answer a different set of questions: How exactly will AI lower entry barriers in content creation? Which parts of the production process will be most affected? Which use cases are the most promising? When will these savings be available? What’s feasible today vs. what’s coming next? And even if these technologies lower entry barriers, could established studios — aka Hollywood — benefit too?

Tl;dr:

• Today, production costs for the median big-budget film release run about $200 million. The most expensive TV shows easily top $10 million per episode. About 15–20% of these costs are “above the line” (ATL) talent, 50% is “below the line” (BTL) crew and production costs, ~25–30% is post production (mostly VFX) and the remainder is other. All in, roughly 2/3 of these costs are labor.
• It is a sensitive topic for good reason, but over time GenAI-enabled tools promise (and threaten) to replace large proportions of this labor.
• Practical use cases are already cropping up across all stages of the TV and film production process. These include story development, storyboarding/animatics, pre-visualization (or “previs”), B-roll, editing, visual effects (VFX) and localization services.
• How far will this all go? Ultimately, the prevalence of GenAI in the production process will be gated by consumer acceptance, not technology.
• Even making the relatively conservative assumption that TV and film projects will always require both human creative teams and human actors, future potential use cases include: the elimination of soundstages and locations, the elimination of costumes and makeup, first pass editing and VFX co-pilots, “acting doubles” that stand in for talent, increasingly cinematic text-to-video generators that offer higher resolution and give creatives much more control, custom-trained video generator models and new forms of content.
• All of this will likely have a profound effect on production costs. Over time, the cost curve for all non-ATL costs may converge with the cost curve of compute.
• For Hollywood, like any incumbent, lower entry barriers are bad. The potential for lower production costs is a silver lining, but it presents a daunting change management challenge. Studios should start either by experimenting with non-core processes or developing skunkworks studios to develop “AI-first” content from scratch.

Figure 1. Almost No One Was Using the Term Generative AI a Year Ago

Source: Google Trends

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