Bain spoke with gaming industry executives about the potential and challenges of generative AI for their industry. Most have high expectations for generative AI and the machine learning that underlies it, and expect it to have a greater impact on their business than other transformative technologies, such as virtual or augmented reality and cloud gaming.
Most of these executives see generative AI as improving quality and bringing games to market faster. Generative AI will also help make larger, more immersive, and more personalized experiences a reality. Interestingly, only 20% of executives believe generative AI will reduce costs, which may be disappointing for some, given that developing high-level games can cost up to $1 billion. As with any form of automation, there may be concerns about AI taking over jobs. But most of the executives we spoke to (60%) don’t expect generative AI to have a significant impact on their talent model or alleviate the industry’s critical talent shortage.
Of the four steps in the video game lifecycle — pre-production concept development and planning, game building (production), testing and launch, and ongoing live operations (post-launch) — executives say they deploy generative AI mostly in the pre-production phase. Production. For example, Blizzard Entertainment created Blizzard Diffusion, an image generator that was trained on its successful titles, including World of WarcraftTo produce concept art for new ideas.
How will the use of generative AI evolve?
Over time, most executives expect generative AI to show greater potential in production and later stages, particularly in several key areas (see Figure 1).
- Creating the story and NPCs: Generative AI can enable limitless interactive stories tailored to each player. NetEase, a Chinese game publisher, has already announced that it will use generative AI to create a non-playable chat function in the upcoming mobile version of its online multiplayer game. Justice Online.
- Game assets: As confidence in the tools increases, generative AI can be used beyond conceptual art, for example, to fill out or even create drafts of entire maps.
- Live operations: While the executives we spoke with mostly focused on the ability to quickly create new in-game assets, such as custom skins, we see a huge opportunity for generative AI to improve community management and player support.
- User generated content: Giving players access to creative AI tools can 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 mostly used in pre-production today, but game executives see more opportunities in production over the next five to 10 years.