Generative AI now powers critical workflows, but it demands precise rules around data, infrastructure, and access. Without them, risks multiply—data leakage, unauthorized queries, shadow integrations. The fix is not guesswork. It is disciplined controls applied at every layer.
Data controls begin with classification. Know which datasets feed your AI models. Track their origin, label sensitivity, and apply policies to restrict movement. Enforce masking and filtering before data ever reaches a model. Logging every request is mandatory. Audit trails must connect each query to an identity and purpose.
Infrastructure access is the second layer. Limit AI execution environments to isolated clusters. Require role-based access to GPUs, model weights, and inference APIs. Apply ephemeral credentials that expire quickly. Monitor resource usage against patterns that signal abuse. Close unused ports. Remove default credentials.