Generative AI
AI techniques (e.g., GANs, transformers) that create new content - text, images, or other media - often raising novel governance and IP concerns.
A family of models that learn data distributions and sample new instances. Generative AI powers text-to-image, deepfake, and code-generation tools. Governance must address data provenance (licensing of training data), content moderation (preventing harmful generations), watermarking (to identify machine-generated media), and intellectual-property safeguards to respect third-party rights and avoid misuse.
A marketing agency uses a text-to-image generative model to create product mockups. Governance policies require that training images come from licensed stock photos, generated content is watermarked, and a human review board vets all outputs for brand compliance and potential copyright issues.
“What used to take weeks of manual reviews and policy work is now structured and auditable in Enzai within minutes. It’s the first time AI governance has felt operational, not theoretical.”
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