AI development is the process of building, training, testing, and improving artificial intelligence systems. It includes choosing data, designing models, evaluating accuracy, and tuning performance so the system behaves reliably for its intended task.
In cyber security, AI development matters because the data used to train or validate a system can become a risk. Sensitive records may be copied into model pipelines, exposed in logs, or leaked through weak access controls. Defenders use careful data handling, synthetic data, and validation to reduce that exposure while still supporting analytics and automation. Attackers also target AI development environments by poisoning training data, stealing models, or abusing poorly secured tools. Strong governance, least-privilege access, and secure testing help keep AI useful without turning it into another attack surface.