Organizations must find, classify, and validate their unstructured data (such as contracts, emails, PDFs, and documents) before using it for AI, as this foundational work establishes the meaning and trust necessary for AI models to understand business operations effectively.
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What to do with unstructured data in your business
Added:We have exciting new research here at Bark. We're finding that 2/3 of organizations say most of their unstructured data is unusable for AI.
This blocks context and can lead to agentic AI failure.
To make that data usable, we're finding that AI adopters need to find it, classify it, and trust it.
>> [music] >> Here's why that's so important. AI doesn't just run on code and compute, it runs on context. And the richest context in your organization is not necessarily in your relational databases. Rather, it's in your contracts, your emails, your PDFs, your internal documents, and images. That context contains the proprietary knowledge that nobody else has. That's your competitive edge, and most companies can't even get to it.
My colleague Merve Aydogan and I measured this problem with Bark's new survey of 225 data and AI adopters.
[music] We found that AI adopters are just starting to discover and harness their rich unstructured data objects for agentic innovation. The two most critical data preparation tasks are classification and validation, which establish meaning and trust before anything else. Without that foundation, downstream work like formatting, indexing, and labeling can't even begin.
And without that foundation, your gen AI models and agents will fail to understand how your business truly operates. This can lead to human bottlenecks as your AI business teams need to babysit their agentic applications. If you read our full report, you can see where you stand and hear our recommendations to get on the right maturity path. Look forward to hearing from you.
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