An AI sandbox is a controlled, supervised environment for developing, testing, and evaluating AI systems. It can separate experiments from production systems, limit access to data, and help teams record how models and datasets are used. A sandbox is a testing method, not automatic proof that a system is safe or that its data use is justified.
In cybersecurity and privacy work, sandboxes can help assess model behavior while enforcing safeguards such as access controls, retention limits, and documented data flows. Teams should check whether each dataset is necessary for its specific purpose and stage, and whether less exposing alternatives are adequate. Testing results do not by themselves establish real-world reliability: independent validation, including checks on new populations and edge cases, may still be required.