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Responsible usage of generative AI with unstructured data

by Richard Freeman, Business Portfolio Manager, Enterprise Workflow Solutions

Summary

Explore six responsible security considerations for using generative AI and unstructured data.

Read time: 6 minutes

The way generative AI (GenAI) mines and adds context to data plays an important role as organizations consider managing critical security risks surrounding data quality, accuracy, integrity, and credibility — also known as data veracity. These risks extend to personal data privacy, intellectual property, corporate integrity, and public liability.

Generative models have become increasingly popular in artificial intelligence due to their ability to create content, including text, images, video, and music. As businesses begin to utilize GenAI to unlock creativity, innovation and productivity, it is crucial to prioritize security, particularly when it comes to unstructured data. By recognizing and understanding the risks, business leaders can make informed decisions and achieve better outcomes.

Learn more about how to protect and secure your unstructured data

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  1. 1[1] Gartner, Information Technology Glossary, Dark Data, https://www.gartner.com/en/information-technology/glossary/dark-data, as of February 26, 2024.