Vivrato report: 97% of studio leaders in EU and North America use AI

Vivrato, a consultancy, has published an AI adoption report covering studios in Europe and North America. It is based on 101 interviews with studio leaders, conducted between April and September 2026. According to GamesIndustry.biz, 97% of those leaders have used AI in some form during development, and 94% have used it in at least one of nine production stages.

The interviews covered six types of AI: generative AI, rules-based automation, fine-tuned or custom-trained models, classical machine learning, retrieval-augmented systems and agentic systems. Vivrato said a studio's view of generative AI is not treated as its view of AI overall. Founder and CEO Adam Boyes said public discussion tends to default to generative AI, while studios use a wider range of techniques, such as machine learning for predicting player churn and rules-based automation in testing.

By stage, code and engineering (engine, tools, gameplay code) is highest at 86%. General productivity tasks such as documentation, email, meetings and planning follow at 83%, and concept and pre-production at 79%. Design and prototyping sits at 68%, and art, assets and animation at 60%. More than half of studios use AI for QA and testing, and for narrative and world building. Analytics and player data, and LiveOps and monetisation, have the lowest adoption rates.

Depth of integration is shallow. Over half of respondents rate AI integration across the full production pipeline at three or lower out of ten. European studios, including the UK, report an average self-rated depth of 4.2 out of 10, against 3.5 in North America. European studios use AI more than North American ones in code and engineering, design and prototyping, art, assets and animation, and analytics and player data.

The figures are self-reported by studio leaders and come from a single consultancy's sample, so treat them as a baseline rather than a measure of how deeply AI is built into any given pipeline. The source does not break down results by studio size or by AI type within each stage.