Generative AI is just beginning to have an effect on video games, but gaming industry executives believe that over the next 5 to 10 years, it will contribute to more than half of the video game development process.
Bain spoke with gaming industry executives about the potential and the challenges of generative AI for their industry. Most have high expectations for generative AI and the machine learning it’s based on, and they expect it to have a greater effect on their business than other transformative technologies, such as virtual reality or augmented reality and cloud gaming.
Most of these executives see generative AI improving quality and bringing games to market faster. Generative AI will also help make bigger, more immersive, and more personalized experiences a reality. Interestingly, only 20% of executives believe that generative AI will reduce costs, which might be a disappointment to some, given that top-tier games may cost as much as $1 billion to develop. As with any form of automation, there may be concerns about generative AI taking jobs. But most of the executives we spoke with (60%) don’t expect generative AI to have a significant effect on their talent model or alleviate the industry’s critical talent shortage.
Of the four steps in the video game life cycle—namely, preproduction concept development and planning, building the game (production), testing and launch, and ongoing live operations (postlaunch)—executives say they are deploying generative AI mostly in preproduction. For example, Blizzard Entertainment created Blizzard Diffusion, an image generator trained on its own hit titles, including World of Warcraft, to produce concept art for new ideas.
How will the use of generative AI evolve?
Over time, most executives expect generative AI to show more potential in production and later phases, particularly in several key areas (see Figure 1).
- Story generation and nonplayable characters (NPCs): Generative AI could enable limitless interactive stories personalized for each player. NetEase, a Chinese game publisher, has already announced that it will use generative AI to create an NPC chat function in the upcoming mobile version of its massively multiplayer online game Justice Online.
- Game assets: As confidence in the tools grows, generative AI could be used beyond concept art—for example, to fill in or even generate drafts of whole maps.
- Live ops: While executives we spoke with focused mostly on the ability to rapidly generate new in-game assets, such as personalized skins, we see a significant opportunity ahead for generative AI to improve community management and player support.
- User-generated content: Giving players access to generative AI tools could allow them to play a more central role in the story, increasing engagement and inviting players to support the never-ending demand for content.
Generative AI is used mostly in preproduction today, but gaming executives see more opportunities in production over the next 5 to 10 years