November 12, 2026
schedule3 Min ReadImage by Siarhei via Adobe Stock.What purpose does generative AI serve in game development?
That question is one developers have sought to answer since generative AI technology came onto the scene and started popping up in every tool, platform, and service with the commercial advent of large language models (LLMs) in 2022. Recently, the role of generative AI in coding has risen to the top of many of these discussions, but new data from the GDC Festival of Gaming State of the Game Industry report indicates that's not the number one use among industry professionals.
According to the report, 40 percent of industry professionals use generative AI in the workplace. Of those, 73 percent of respondants marked that "research/brainstorming" was their number one use case. 62 percent said they used it for "data analysis and summarization" and only 56 percent said they use it for "code generation/debugging." Respondents were allowed to select multiple options that described their use of the tool.
That indicates that in the world of professional game development, only half of generative AI users are using the technology to generate code.
Meanwhile 37 percent of respondents said they use the technology for game prototyping. 22 percent said they use it for "concept art and visual ideation." While some respondents said they use generative ai for content personalization or procedural generation, ultimately only six percent of player said they use the technology to create what will eventually become "player-facing content"
What forces are shaping the use of generative AI?
Adoption of generative AI tooling has been met with exceptionally fierce resistance by segments of the professional game development community, with previous data indicating that half of developers are worried that the tech may lower the quality of games. Throughout both this year's survey and reports from prior years, respondents explaining their feelings about generative AI also remain concerned over the environmental impact of AI tools and the use of copywritten material in their foundational training data.
The survey also captures sentiment from developers who say generative AI tech has enhanced their programming capabilities. This is similar to earlier comments from experts programmers like DayZ creator and Rocketwerkz creator Dean Hall have explained the tool has accelerated their ability to make games using complex programming languages and frameworks. This isn't done through "vibe coding," a practice of progressively prompting AI to make software features, but rather taking advantage of LLMs' capability to "tokenize language."
The use of generative AI to make in-game audio/visual assets or other content has been a particularly risky landmine for studios, who often have had to backpedal or alter course after unveiling said content to players.
This data from the latest edition of the State of the Game Industry report highlights how vastly adoption of and use cases for generative AI technology can vary from role to role and studio to studio. From the outside looking in, generative AI is proselytized as a tool capable of generating entire games, replacing artists, and creating fully-simulated non-playable characters, and generating entire games.
And yet the data also indicates that for game developers across many markets, disciplines, a rather different use case has started to form.
GameDeveloper.com and GDC Festival of Gaming are sibling organizations under Informa Festivals.
Top StoriesGenerative AI, Machine Learning, & LLMsGame & Production TechnologyGDC Festival of GamingAbout the Author
Bryant Francis
Senior Editor, GameDeveloper.com
Bryant Francis is a writer, journalist, and narrative designer based in Boston, MA. He currently writes for Game Developer, a leading B2B publication for the video game industry. His credits include Proxy Studios' 4X strategy game Zephon, Iron Anchor Studios' Down With The Ship, and Amplitude Studio's 2017 game Endless Space 2.
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