Enterprise generative AI adoption is accelerating rapidly, bringing significant security risks. Organizations must prioritize security, bias mitigation, and human oversight for sustainable AI deployment. New safeguards are needed throughout the AI implementation lifecycle, from data ingestion to monitoring. Responsible AI requires trusted data sources, framework guardrails, and ongoing testing. Embedding trust into the AI lifecycle ensures innovation while protecting people and reputation.