Generative AI is becoming part of more daily workflows, but it also introduces risks many teams are still learning to manage. Prompt injection, data leakage and autonomous agent interactions create new threat paths that traditional controls often miss.
Stronger governance, trusted data sources, refined classification and continuous testing help detect bias, drift and unsafe outputs. Human oversight is also important, since autonomous agents can push errors through systems faster than manual review can catch.
To close maturity gaps, organizations should strengthen training, build security into development pipelines, review access controls and prepare for AI-driven incidents with realistic response exercises.
Learn how governance and human review improve GenAI safety:
👉 https://t.co/scP2tzOf8G
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