Today’s deep-learning neural networks, which mimic human learning patterns, can be trained on vast data sets to achieve superhuman proficiency at any given task – AlphaGo learned to play Go, and then mastered it. Generative AIs use such neural networks to create new content in response to a textual or visual prompt, or even certain contextual cues.

In this blog we will explore various types of AI tol sets that are applicable to game development. Each game contains thousands of models, textures and other assets, and AI can be harnessed to generate these at scale, and at a fraction of the cost and time that is currently spent developing them. We will also discuss companies that are working on, or offering, AI solutions for key parts of the game asset pipeline.

We will also delve into the use of AI in game testing and playtesting for bugs – AI can potentially automate quality assurance. Games have grown bigger and bigger, and quality assurance has become increasingly challenging. AI can help spare developers the thankless, time-consuming task of playtesting and bug-fixing.

AI is thus both a literal and figurative game changer for developers, and in the following sections we deal with the main contexts in which AI is being used to help streamline how games are made – from the creation of game assets to the testing of games in the development phase.

The Generative Revolution in Game Development According to venture firm Andreessen Horowitz, even small game studios can now finally achieve quality without punitive costs and time, because they can harness generative AI tools to create game content with unprecedented ease.

Generative AI thus holds great promise for gaming because the AAA game industry has a steep barrier to entry – consider the budget, the man-hours, and the crunch behind games like Red Dead Redemption 2 (RDR 2, 2018) and other large-scale games. In fact, RDR 2’s estimated budget of $540 mn comfortably exceeds the most expensive Hollywood film – Pirates of the Caribbean: On Stranger Tides ($379 mn).

To compete with the likes of Rockstar, developers need to find cost-effective tools for the game development pipeline, and even giants like Rockstar or Ubisoft can benefit from such solutions – in fact, Ubisoft is working on both an AI-powered animation system, and an AI bug-fixing tool. Quite a few studios are hence already trying to enhance their workflows with AI, as we will discuss below.

2D Assets and Concept Art AI-powered programs such as MidJourney, Stable Diffusion and Dall-E 2 can generate high-quality image assets, such as concept art and 2D game content from text prompts and they have already found a place in game asset production – a developer has used these AI generators in tandem, with a professional artist, to create concept art within days rather than weeks.

These aren’t enterprise tools – they are available to enthusiasts as well, and Youtube has videos on how to generate concept art or any type of 2D image using such AI generators for free.

Ludo, in turn, is a company which offers an image generation solution geared for studios. Ludo is an AI-powered game ideation and creation platform that is intended to streamline the creative process of game development, and one of the ways it helps game developers is by using Stable Diffusion to generate images during the ideation phase, and even create high-quality 2D artwork and assets further down the pipeline.