Unlocking the Power of Generative AI through Unstructured Data

The Missing Piece of Generative AI: Unlocking Insights from Unstructured Data

Generative AI is taking the world by storm, but it relies heavily on unstructured data - the text, images, documents and other information that makes up 90% of enterprise data. Companies need to focus on surfacing and utilizing this untapped resource in order to fully capitalize on generative AI.

Unstructured data sources like old documents, presentations, IoT sensor streams and more contain a treasure trove of insights that can be harnessed by generative AI. Language models can interrogate these sources, understand them and provide new perspectives. But enterprises continue to struggle with extracting value from these vast stores of unstructured data.

A unified data platform that brings together analytics and AI capabilities is crucial for preparing unstructured data for generative AI. This allows efficient storage, management and analysis of the variety of data types that AI systems need. According to a survey from MIT, 70% of tech leaders see a unified data environment as essential for their AI goals.

However, fragmented IT systems, proprietary file types and lost documents create roadblocks. Mergers and acquisitions have scattered important R&D and plant design documents, for example. New techniques are needed to open up and learn from these locked away sources.

Involving stakeholders across the business is key to overcoming these hurdles and ensuring adoption of AI. While IT leaders enable the technology, line of business executives must take ownership to identify critical data sources, integrate them into workflows and champion change.

The generative AI revolution hinges on access to data. Companies that push forward now to capture unstructured data will find themselves in a prime position to capitalize on the new wave of AI-driven insight. The time is now to unlock the missing piece.