How Enterprises Can Safely Use Unstructured Data With LLMs

Generative AI adoption is no longer a choice—it’s a necessity for every major organization looking to survive and thrive in a competitive global economy. Recent research from Gartner shows that GenAI is now the

The use of unstructured data in GenAI introduces new types of governance, privacy and security risks that these traditional data management tools aren’t equipped to handle. To safely leverage GenAI, organizations require a radically different approach to governing unstructured data.‘The Acolyte’ Episode 6 Recap And Review: These Short Episodes Were A Big MistakeTo ensure safe usage of GenAI, organizations must have a full view of their unstructured data’s context.

Mapping provides an end-to-end view of data flow similar to the data lineage of structured data. It assists in monitoring the feeding of GenAI models and identifies contributing sources. It also verifies the integrity of responses from these models.GenAI models use massive volumes of unstructured data. Automating the labeling or tagging of files can help to ensure that only relevant data is used in GenAI projects, safeguarding against unintentional use or exposure of sensitive information.

Focusing on the freshness of data, deduplication to remove repeated occurrences, relevance to the topic and reliability of sources helps prevent unintended data from being used for GenAI projects.GenAI assistants, bots and agents are vulnerable to malicious use and attacks. Businesses should look to the appropriate tools to automatically detect, classify and redact sensitive information on the fly, block toxic content and enforce compliance with topic and tone guidelines.

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