conclusion
Like most companies, studios, streamers, and creative talent are fascinated and concerned about the capabilities of Gen AI. For studios looking to create generative AI content in the year ahead, a key driver of adoption will be the magic and creativity it seems to enable, a strange frontier model that remixes human creativity into new forms. It could be a fever dream. They will also be driven by concerns that new forms of media may emerge from outside the Hollywood ecosystem.
More and more independent content creators are demonstrating what can be done with the latest synthetic media capabilities that are rapidly entering the market. Hollywood studios were once successful in controlling scarcity of content and distribution, but now they are both abundant and democratized32. The sense of impending content destruction is likely to grow even more in the year ahead.
Almost every month, there are new developments in frontier models that further advance their capabilities toward human intelligence, creativity, and insight. A year ago, it was thought that by 2030, nearly all blockbuster movies would likely be generated by AI.33 By 2025, that lofty goal may look a little more achievable. I don’t know.
Meanwhile, content owners will seek to strengthen the competitive moat around their intellectual property by pursuing further litigation and regulation of public models deemed to be copyright infringement. Regulators may require major model providers to prove that their training sets do not infringe on existing content rights. Most major studios are likely to resist offers from model providers to license their content catalogs into their public training sets, and if economic conditions are favorable, they will be more likely to develop a more tailored portfolio around their studio IP. They may prefer to partner with small businesses that can build a made and protected model.
At a macro level, generative AI will require significant capital intensity and growth may slow unless a path to broader economic value becomes clear within the next year or so34 (on-device (See this year’s TMT predictions for Generative AI). , capabilities could advance rapidly if the next generation of Frontier models can overcome existing challenges. Efforts may be made to reduce the cost of training and running models and reduce the amount of data required.
Large studios are also large enterprises likely to deploy more generation AI capabilities focused on reducing costs, optimizing business, increasing productivity, and expanding and accelerating customer reach. . In Deloitte’s 2024 State of Generative AI in the Enterprise study, 42% of executives surveyed cited efficiency, productivity, and cost savings as the most important benefits of using AI. 58% reported a variety of other benefits, including increased innovation, improved products and services, and stronger customer relationships. 35 There appears to be growing interest in applying these capabilities to modern business.
As the saying goes, a rising tide lifts all ships. Gen AI tools appear poised to help more small businesses and creators achieve productivity and quality levels previously reserved for large companies. Small studios and independent creators have the potential to be much more capable while being relatively immune to the risk and cost overheads that large studios pose. The biggest studios may need to cut costs and accelerate time to market if they want to compete not only with each other, but also with user-generated content platforms, social media, games, and more. Production and distribution may not be so scarce, but attention remains a finite resource.
