Crystal Dynamics explains use of generative AI in development of Tomb Raider: Legacy of Atlantis

Crystal Dynamics uses generative AI for early-stage concepting in Tomb Raider: Legacy of Atlantis. The studio confirmed all final game assets remain human-crafted.

Categorized in: AI News IT and Development
Published on: Jun 14, 2026
Crystal Dynamics explains use of generative AI in development of Tomb Raider: Legacy of Atlantis

Crystal Dynamics confirmed on June 12, 2026, that it is using generative AI during the development of Tomb Raider: Legacy of Atlantis. The studio uses the technology to accelerate early-stage concepting, though it insists all final game assets remain human-crafted.

Early-stage visualization

Jeff Adams, experience director on the title, explained the workflow to Game Informer. He described artificial intelligence as a tool to help the development team find the right answers more quickly.

"Let me give you an example of what that looks like," Adams said. "So, say in early level development, we have an idea for an object, but we're not sure whether or not we want to take the dev time to build it. We can use a generative AI tool to help us visualise that object in the world."

If the concept works, the studio moves it to its traditional pipeline. Adams noted that the team will then concept and build the asset, ensuring all finished content in the final game remains human-crafted.

Limits on public disclosure

When reporters pressed for further details on how this integration works in practice, a Crystal Dynamics representative intervened to end the conversation. This boundary highlights the ongoing sensitivity around AI adoption in commercial software development.

Why this matters for IT and development professionals

This workflow demonstrates a practical implementation of Generative AI and LLM as a pre-production prototyping tool rather than a replacement for core engineering or art pipelines. For development teams, early-stage visualization can reduce wasted compute and man-hours on discarded concepts.

However, maintaining strict handoffs between AI-generated concepts and human-crafted final assets requires clear pipeline governance. Professionals building similar workflows in AI for IT & Development must define exactly where automated tooling ends and human verification begins.


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