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Razer CEO Min-Liang Tan argues that players can welcome AI when it helps developers make better games, even if they dislike conspicuous, low-quality AI-generated content. That is a case for useful tools—not proof that gamers broadly love AI. A 2025 McKinsey survey found a mix of opposition and conditional support, while Razer’s own account distinguishes development assistance from replacing human creativity.
What Tan means by “gamers love AI”
Razer’s February 4, 2026 recap of Tan’s appearance on The Verge’s Decoder podcast frames his point around a distinction: players want engaging, polished games, and AI may help developers deliver them. The statement is Tan’s argument, not an established consensus about gamers. The available wording is quoted by Razer; it should not be treated as a complete, independently checked transcript. Razer’s recap.
Tan objects to poor generative output: “As gamers… what we’re unhappy with is GenAI slop. When I play a game, I want to be engaged. I want to be immersed. I want to compete. I don’t want to see characters with extra fingers or shoddily written storylines.” In the same recap, he describes AI as “a tool to help game developers make better games… rather than replace human creativity.”
That is a narrower claim than saying players approve of every use of AI. A bug-finding system that improves stability is different from AI-written dialogue, generated art, or an in-game assistant. Players may judge each by its effect on quality, creative control, employment, and whether AI-created material is visible or disclosed.
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What the survey says about gamer attitudes
McKinsey’s 2025 report, The ‘attention equation’: Winning the right battles for consumer attention, draws on a survey of 7,000 consumers worldwide, including 3,000 in the United States. Its reported gamer responses show conditional views, not blanket enthusiasm or rejection:
| Reported view | Share |
|---|---|
| Believe generative AI should not be used at all in video game development | 25% |
| Favor generative AI if it does not result in job losses | 30% |
| Favor its use for less-important game elements | 15% |
| Favor its use across all aspects of games if it results in better-quality gameplay | 15% |
These are categories reported by McKinsey, not a direct poll on Tan’s specific claim that gamers love AI. They show why the qualification matters: some respondents oppose generative AI in games, while others accept it under conditions such as protecting jobs, limiting it to less-important elements, or improving gameplay. McKinsey’s report.
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AI in game development covers different jobs
“AI in games” can mean many things. Conventional game AI—such as systems that control non-player characters or procedural systems—has existed for years. The recent debate often focuses on generative AI, which can produce content. Razer’s framing also includes tools used behind the scenes and AI that interacts directly with players.
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- Quality assurance and workflow support: Tools may help identify bugs, organize reports, or automate repetitive tasks. The intended player benefit is a more stable or polished game; the actual result depends on how well a studio validates the tool’s output.
- Player-facing coaching or assistance: An AI coach or companion interacts with the player directly. Its usefulness depends on whether it adds a helpful, responsive experience rather than distracting from play.
- Generative content: AI may create or assist with art, dialogue, stories, or other game elements. This makes questions of quality, authorship, disclosure, and human approval especially visible to players.
These uses should not be treated as interchangeable. Support for invisible bug triage does not automatically imply support for generated characters or stories. Nor does a company’s description of a tool establish its effectiveness or its impact on jobs.
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What Razer’s examples do—and do not—show
Razer’s announcements illustrate its AI strategy, but they are not evidence that gamers endorse it or that every announced concept is a finished, widely available product.
Project AVA
Razer described Project AVA at CES 2025 as a conceptual virtual esports coach. At CES 2026, it presented the concept as an animated AI desk companion with a 5.5-inch display and PC Vision Mode. Razer said the CES demonstration used xAI’s Grok model and that the platform was intended to support multiple models. Its January 6, 2026 announcement said the companion was available for reservation in the United States at that time; that dated status should not be read as a statement of current availability. These are Razer’s descriptions of a concept and plans, not independent performance tests. Razer’s CES 2026 announcement.
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Tan also said, as quoted in Razer’s February recap, “We picked Grok because it currently has the best conversational personality… but AVA is an open platform.” That quote describes the company’s choice for its demonstration and its stated platform direction; it does not establish that the system is a finished game-development tool or that players prefer it.
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Razer’s CES 2026 announcement also introduced the Forge AI Developer Workstation and open-source AIKit for local-first AI development. Its Developer Portal lists AI Gamer Copilot and AI QA Copilot alongside other developer resources. Those listings establish that Razer markets developer offerings; they do not independently verify their results. Razer Developer Portal.
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Razer has also described QA Co-AI as a cloud plug-in for logging bugs and generating reproduction steps. In an August 18, 2025 blog, it repeated figures reported by Digital Trends from internal tests: 50% faster QA cycles, 25% more bugs discovered, and 50% fewer total QA hours per build. These are company/internal-test claims relayed through a secondary report, not independent benchmarks, so they should not be taken as proven outcomes for other studios. Razer’s newsroom.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to judge an AI feature in a game
The useful question is not simply whether a game uses AI. Consider what the system does and what changes for players and creators:
- Function: Is it testing, bug triage, repetitive production work, player coaching, or content generation?
- Player impact: Does it demonstrably improve stability, playability, or responsiveness, or is it mainly a production claim?
- Creative control: Do people retain meaningful authorship and approval over creative decisions?
- Labor impact: Is the tool assisting workers, changing how work is organized, or substituting for roles? Survey responses alone do not establish a particular employment effect.
- Visibility and disclosure: Does the player encounter generated content directly, and can they tell how it was made?
- Evidence: Is the claim a company description, an internal test, an independent evaluation, or a survey result? Each supports a different conclusion.
Does the evidence show that gamers love AI?
No. Tan’s argument is that players may welcome AI when it helps produce better games, even as they reject low-quality generative content. McKinsey’s 2025 figures support a more mixed picture: opposition coexists with support conditioned on outcomes and use. Razer’s products and announcements show what the company is pursuing, not what gamers as a whole want. The strongest conclusion is that acceptance depends on what AI does, whether it improves the game, and how it affects creative work—not on the label “AI” alone.
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