Generative AI

Generative AI describes models that produce text, images, code or other content from instructions and context. Output is probabilistic and can be plausible but wrong, incomplete or derived from unsuitable data. A model does not automatically know internal policy or verify facts. Before business use, organisations should define purpose, permitted data, human review, rights, retention, security, suppliers and response to errors. Sensitive information should not be submitted without an appropriate basis and controls. Connecting a model to tools can amplify impact because an answer may trigger actions. Validation uses representative cases, measures quality, risk and cost and retains proportionate traceability. Automating generation does not transfer accountability; significant decisions need supervision, criteria and a fallback when the service or output is unreliable.