AI is changing QA.
How do we make it work?
A practical look at how enterprise AI can help Development Support teams scale testing, reporting, operational intelligence, and quality, while keeping human expertise at the center.
Inside, you'll find:
- How AI can help Development Support Services scale beyond manual workflows
- Amber's maturity model, from AI-assisted QA to intelligent testing
- Practical applications across QA, reporting, operations, customer support, and localization
- Two detailed use cases for AI-assisted test case generation and report generation
- The infrastructure, governance, security, and human oversight required for responsible adoption
- A phased roadmap for building scalable, AI-enabled delivery operations
Modern game development asks QA and support teams to validate more content, more platforms, more configurations, and more player experiences in less time. As product complexity and operational data grow, traditional workflows can lead to higher costs, slower feedback loops, fragmented reporting, and delayed insight.
This whitepaper explores how Amber is operationalizing AI across Development Support Services, from test case generation and automated reporting to telemetry analysis, customer support, localization, and testing infrastructure. The approach is built around responsible augmentation, not replacement: AI accelerates repetitive and cognitive work, while experienced professionals remain in control of validation, prioritization, and client-facing decisions