The morality of AI and the immense amount of stolen work on which it is trained is both a personal question for each individual, and a much larger question for courts and legislators. The practical question of whether it even works as claimed, though, is an important one for those running businesses, especially those feeling those FOMO pangs keeping them awake at night.<\/p>\n
In an environment where many studios really don\u2019t want to risk their use of AI becoming public knowledge, however, there\u2019s a stark lack of comparative case studies or emerging best practices \u2013 an information blackout in which, I fear, some snake oil salesmen are gleefully setting up shop.<\/p>\n
The problem AI purports to assist with is, after all, a truly existential issue for many studios. Lots of companies are struggling with development cycles that are growing out of control \u2013 an immense problem given that the industry’s business model generally means you don’t make any money until you launch (Early Access models aside). That\u2019s a hell of a tough thing to handle financially if your development cycles are growing past the five-year mark (and in some cases heading towards the decade line).<\/p>\n
Finding any way to wrangle those timeframes back under control is a key focus for a lot of studio heads. It\u2019s only natural for them to be receptive to a technology promising to massively boost productivity across the board for everything a studio does \u2013 code, art, animation, sound, you name it, AI companies claim they can speed it up.<\/p>\n The problem is that while it\u2019s clear that AI can be very useful in limited, narrow use cases, as a tool supervised by a human expert, those cases are a long way from the ideal being sold by the AI companies themselves, of autonomous agent tools delivering gigantic productivity boosts.<\/p>\n Consider the programming side of things. Code is arguably the ideal field for generative AI, since while it\u2019s a very highly skilled and knowledge-driven industry, many of the tasks involved are inherently repetitive. Much of a coder\u2019s time is spent either repeating patterns from their own prior work or seeking out solutions to problems other people have already tackled before them.<\/p>\n It’s not reliable enough to be let loose to do things on its own<\/p>\n It\u2019s unsurprising that generative AI, which is essentially a huge pattern matching system that figures out what\u2019s likely to come next based on what it sees before, has many genuine uses here.<\/p>\n A skilled programmer who’s already expert in their field can absolutely use AI judiciously to speed up their output, essentially treating it as a glorified autocomplete that’s just smart enough to be able to save a lot of repetition and boilerplate typing, as well as generating reasonably good function documentation, among other things.<\/p>\n This is how most skilled developers are using AI today. It’s not reliable enough to be let loose to do things on its own, but it can save time and let you iterate faster (especially in the prototype phase, in which some bugs or inefficiencies aren’t a total showstopper), as long as a skilled coder carefully supervises its output.<\/p>\n That’s clearly a useful thing. But it’s on an entirely different planet from the promises being made by AI companies to try to convince studios to make AI central to their workflows. Agentic AI being given free rein over entire codebases and completing tasks that used to need a human in the loop does not seem like a realistic paradigm for game development (or, honestly, for any kind of development beyond hobbyist projects, which are the only field in which this kind of “vibe coding” has any actual value).<\/p>\n So, while skilled coders might increase their productivity by a moderate amount (how much is debatable; some recent research suggests that while coders feel their output increasing, their measurable productivity gains are actually negative due to the amount of time spent squabbling with the AI’s weirder and less helpful impulses), the actual bottleneck many studios face remains in place \u2013 they still need to hire skilled, experienced coders, who are always expensive and often not easy to find.<\/p>\n The same essentially holds true for artwork and any other field. Generative AI might find some uses in terms of prototyping, and speed up that part of the process, which is where most studios seem to be experimenting with it now \u2013 churning out rough, AI-generated assets for prototypes and placeholders.<\/p>\n
\nSeven years on from the formation of The Initiative, the Perfect Dark reboot was cancelled and the studio closed after the game became stuck in development hell<\/a><\/p>\n