40 Questions Gaming Studios Should Ask Before Trusting AI
AI tools like Midjourney, Inworld AI, and GitHub Copilot are now making suggestions about your game design, player monetisation, and creative direction. Your team needs to know which recommendations come from your actual vision and which ones come from an algorithm optimising for engagement metrics you never chose.
These are suggestions. Use the ones that fit your situation.
1When ChatGPT or GitHub Copilot suggests a game mechanic, can you trace back why that mechanic serves your specific creative vision instead of just matching patterns from popular games in its training data?
2If you removed the AI-suggested feature tomorrow, would players notice because it deepens your game, or would they not miss it because it was safe filler?
3Are your art direction decisions increasingly constrained to styles that Midjourney can generate cleanly, rather than the distinctive visual direction your studio is known for?
4When your design team uses GitHub Copilot for gameplay code, are junior developers learning to evaluate whether the suggestion is clever or just common, or are they accepting it because it compiles?
5Has an AI tool ever suggested a game direction that contradicts your studio's previous player feedback or your known player community values?
6Are you making creative risks the same way you did before AI tools, or are you unconsciously gravitating toward safer options because the AI keeps suggesting proven alternatives?
7When Inworld AI generates dialogue for NPCs, how do you know whether it matches the character voice your writers created or whether it has smoothed the character into a generic, AI-friendly version?
8If your game's aesthetic started converging with three other studios' games this year, is that because you're all solving the same player problems, or because you're all using the same generative tools?
9Does your narrative designer still make the story decisions they believe in, or are they now defending story choices to the team because an AI system recommended them?
10What design decision from the last year would be unrecognisable to players if you replaced it with what the AI originally suggested?
Player Experience and Live Operations
11When an AI system recommends changing monetisation mechanics to improve retention, do you have a way to know whether you're genuinely improving the player experience or manipulating players into spending differently?
12Are you measuring player trust separately from engagement metrics, or do you assume high session time means players actually trust your game?
13If a player community suddenly felt your live ops were becoming impersonal or extractive, could you show them the human decision-maker for that change, or would you have to admit an algorithm changed their game experience?
14When you A/B test new player onboarding flows using AI recommendations, are you comparing them against your original design intent or against what maximises day-one retention?
15Does your live operations team know what percentage of changes to player rewards, difficulty curves, or event structures originated from AI suggestions rather than human design decisions?
16If you stopped using AI to optimise your battle pass structure tomorrow, would your monetisation fall because the new system was actually worse, or because the old system was designed to be more persuasive than profitable?
17Are players saying your game feels more generous or more sticky after you implemented AI-driven personalisation, or are they saying it feels like it knows them too well?
18When you personalise content or difficulty using player behaviour data, can your community manager explain to players why their experience is different without sounding like you're isolating them?
19How many players have left your game specifically because they noticed their difficulty, rewards, or spending pressure changed based on their behaviour patterns?
20If your average session time increased because of AI-driven content recommendations, but your community is smaller and more churn-prone, are you actually winning?
Team Capability and Technical Judgement
21When your programmers use GitHub Copilot, are they building the ability to spot what code is right for your game's architecture, or are they becoming dependent on AI-generated solutions that work but create technical debt?
22Has anyone on your team formally rejected an AI suggestion in the last month, and if so, did they have to explain their reasoning, or did they just override it and move on?
23Are you hiring artists and designers based on their taste and judgement, or based on their ability to prompt Midjourney and Inworld AI effectively?
24When a mid-level designer proposes a feature that contradicts what an AI tool recommended, does your leadership listen because the designer has strong reasoning, or do they have to work twice as hard to be heard?
25If you lost access to your AI tools tomorrow, could your team still ship a game that meets your creative and commercial standards, or have you built dependency into your pipeline?
26Are your junior developers learning to read and understand code, or learning to read and accept code generated by Copilot?
27When you onboard new team members, do you teach them your studio's design philosophy and engineering standards first, or do you teach them the AI tools first?
28Has any team member raised concern that relying on AI for creative suggestions is atrophying their own creative decision-making skills?
29If your lead designer left today, would the next person in that role understand why you made the creative choices you made, or would they only see that an AI recommended them?
30Are you investing in growing your team's ability to make intentional creative and technical decisions, or are you optimising for faster iteration with AI?
Alignment Between Vision and AI Output
31Can you write down your game's core creative vision in one paragraph, and if so, would an AI system trained on your git commits and design documents produce the same vision?
32When Unity AI recommends a change to your game's behaviour, do you understand what metrics it is actually optimising for, or are you trusting that optimisation and engagement are the same thing?
33If you asked five different team members whether a major design decision came from your studio's vision or from an AI recommendation, would they all agree?
34Are you documenting why you accepted or rejected each AI suggestion so you can spot patterns later about whether AI is pushing you toward certain types of games?
35When ChatGPT generates quest text or mission objectives, is someone checking whether the language matches your game's tone, or just whether it is coherent?
36Has your studio ever shipped a feature that you now recognise was there because an AI recommended it, not because players asked for it or your vision required it?
37Are you using AI to speed up execution of your creative vision, or using AI to replace your creative vision because iteration is faster?
38If you compared the games your studio was known for five years ago against what you are shipping now, would a player recognise your design fingerprint, or would they say you now play it safer?
39When an AI tool generates multiple design options, are you selecting the one that best serves your game, or the one that is most polished because the AI generated it?
40Do you have a clear threshold for when an AI recommendation is good enough to ship versus when it needs human revision, or does that threshold shift based on deadline pressure?
How to use these questions
Before you ship an AI-suggested feature, ask yourself whether a player would recognise it as something your studio would make. If the answer is no, it should not ship.
Track every design decision that started as an AI recommendation and ended up in your released game. At the end of the year, ask whether your studio's fingerprint is stronger or weaker.
When you see engagement metrics improve after an AI change, separately measure whether player satisfaction and community health improved with them. One can go up while the other goes down.
Protect one part of your game design process from AI tools completely. Let your team make at least some decisions the old way. You will learn what you are actually losing.
If a junior team member accepts an AI suggestion because they do not yet know your studio's standards well enough to judge it, that is a signal you need better onboarding and mentorship, not better AI.