[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-81777-en":3,"doc-seo-81777-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},81777,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","AI-Native Games: A Survey and Roadmap","Generative AI now enables games to create dialogue, quests, characters, images, and worlds during runtime, but generation alone does not guarantee that gameplay is meaningfully AI-native. The paper defines AI-native games using a counterfactual criterion: removing or trivially replacing the runtime generative AI collapses or fundamentally changes the core loop. It screens candidates and analyzes 53 public AI-native games and prototypes, proposes a dual-axis G/N taxonomy, and argues that stable gameplay requires mechanical invariants supporting interpretable, consequential open-ended output. A roadmap covers controllable generation, AI-as-mechanic design, multimodal and multi-agent systems, evaluation, safety, and regulation.","AI-Native Games: A Survey and Roadmap  \nZhiyue Xu 1,2 , Fandi Meng 2,3 , Kaijie Xu 4 , Clark Verbrugge 4 , Simon Lucas 5 , Jian Zhao 2,3  \n1 Institute of Automation, Chinese Academy of Sciences 2 Zhongguancun Academy  \n3 Zhongguancun Institute of Artificial Intelligence  \n4 School of Computer Science, McGill University, Montreal, Quebec, Canada  \n5 Game AI Research Group, Queen Mary University of London, London, United Kingdom [Email: xuzhiyue2026@ia.ac.cn](Email: xuzhiyue2026@ia.ac.cn), [mengfandi@zgci.ac.cn](mengfandi@zgci.ac.cn), [kaijie.xu2@mail.mcgill.ca](kaijie.xu2@mail.mcgill.ca), [clump@cs.mcgill.ca](clump@cs.mcgill.ca),  \n[simon.lucas@qmul.ac.uk](simon.lucas@qmul.ac.uk), [jianzhao@zgci.ac.cn](jianzhao@zgci.ac.cn)  \narXiv :2607 .00527v2 [ cs .AI] 3 Jul 2026  \n~~ ~~ ✦ ~~ ~~  \nAbstract—Generative AI now enables games to produce dialogue, quests, characters, images, and worlds at runtime. Yet generation alone does not make a game AI-native, nor does it guarantee playability. This paper defines AI-native games by whether runtime generative AI is constitutive of the core loop: if the AI component were removed or trivially replaced, the central form of play would collapse or become fundamentally different. This counterfactual criterion separates AI-native games from AI-augmented games and adjacent boundary artifacts. Using this definition, we screen candidate artifacts and analyze 53 publicly available AI-native games and prototypes. We introduce a dual-axis G/N taxonomy: the G-axis captures player-facing game type, while the Naxis captures the dominant AI mechanic that makes generative AI indispensable to play. The corpus is concentrated around language-forward designs, especially narrative adventure, epistemic interaction, and generative narrative, while categories such as semantic adjudication, multiagent simulation, generative construction, and relationship/companion play remain less represented. We argue that the central design problem is organizing semantic openness into stable gameplay. AI-native design depends on mechanical invariants: goals, rules, state, feedback, pacing, and player agency that make open-ended AI outputs interpretable and consequential. We conclude with a roadmap for controllable generation, AI-as-mechanic design, multimodal and multi-agent systems, inference economics, evaluation, safety, and regulation. The curated game corpus, source links, and coding records are available at Awesome-AInative-games-collection repository.  \nIndex Terms—AI-native games, large language models, procedural content generation, game AI, interactive narrative, controllable generation, AI safety.  \n1 INTRODUCTION  \nGenerative artificial intelligence is increasingly moving from a production-side tool for game development to a runtime component of game systems. Earlier computational and generative methods were mostly applied before play, helping designers, artists, writers, and programmers create or explore assets, levels, rules, and code [1] . A more consequential shift for game design is now emerging: foundation models are being integrated into games during play, where they interpret player input, generate responses, update fictional worlds, control characters, and sometimes arbitrate outcomes. AI is no longer only a tool used to make the game; it becomes part of the playable system itself [2]–[5] .  \nRuntime generation, however, does not by itself produce engaging gameplay. Games depend on constraints, goals, feedback, and opportunities for strategic understanding [6], [7] . Generative models invoked at runtime may produce plausible dialogue, quests, items, or worlds, but these outputs can be inconsistent, unbalanced, unsafe, or disconnected from player agency. Unbounded generation can therefore increase variety while weakening the very structures that make play meaningful. The question, then, is how generative AI can move beyond content generation and become part of reliable, compelling game mechanics [2],[8] .  \nTo st","cbCaiilIFEuWIsmX","https://ap.wps.com/l/cbCaiilIFEuWIsmX","pdf",888536,3,1,14,"English","en",105,"# Abstract\n# Introduction\n## From tool to runtime component\n## Why runtime generation is not enough\n## Defining AI-native games\n## Distinguishing from traditional game AI\n## Connections to interactive drama and PCG","[{\"question\":\"What makes a game “AI-native” in this paper’s definition?\",\"answer\":\"A game is AI-native when runtime generative AI is constitutive of the core loop—removing or trivially replacing the AI causes the central form of play to collapse or become fundamentally different.\"},{\"question\":\"How does the paper differentiate AI-native games from AI-augmented or boundary artifacts?\",\"answer\":\"The counterfactual criterion separates AI-native games from cases where AI is only supplementary; traditional authored assets or deterministic mechanisms would otherwise preserve the core gameplay structure.\"},{\"question\":\"What is the dual-axis G/N taxonomy introduced in the survey?\",\"answer\":\"The G-axis characterizes the player-facing game type, while the N-axis captures the dominant AI mechanic that makes generative AI indispensable to play.\"}]",1784176086,35,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"ai-native-games-a-survey-and-roadmap","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,50],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":20},"https://docshare.wps.com/document/research-report/",{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/ai-native-games-a-survey-and-roadmap/81777/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-24","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What makes a game “AI-native” in this paper’s definition?","Question",{"text":75,"@type":76},"A game is AI-native when runtime generative AI is constitutive of the core loop—removing or trivially replacing the AI causes the central form of play to collapse or become fundamentally different.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the paper differentiate AI-native games from AI-augmented or boundary artifacts?",{"text":80,"@type":76},"The counterfactual criterion separates AI-native games from cases where AI is only supplementary; 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