The rise of artificial intelligence (AI) has opened the door for employing it to manage enterprise information better. However, how can enterprises go beyond using AI from extracting value and insight from the mass of content and data that already exists? According to David Jones, vice president of product marketing at Nuxeo, there are four ways by which AI can turn enterprise content into a true information asset.
Enterprises can utilize AI for using metadata effectively. For instance, enterprises can use a content solution platform (CSP) to pass content through an AI enrichment engine. This will enable users to append additional metadata attributes to each one of the files currently stored. By virtue of allowing users append additional metadata more context, intelligence, and insight is injected into the information management ecosystem.
AI can, in addition, be used by enterprises for enabling fast and accurate identification of content. For example, an AI-driven engine can be used to classify content stored within legacy systems much more easily. In fact, even fundamental AI tools can identify the difference between a contract and a resume. In addition, advanced engines can be employed to expand this principle to design AI models based on content specific to an enterprise. Consequently, the classification created will be much more detailed than the generic classification developed by employing a manual approach.
Furthermore, AI can be used to process humongous content and thereby mitigate the challenge of managing records or even simply applying retention policies. By using AI-classification of content with a CSP, it is possible at a massive scale to determine “what is not a record” quickly and easily. Subsequently, AI can be used on the remaining content to identify the type of content in more detail and match it to the retention rules. Furthermore, AI can be leveraged to make recommendations to the relevant staff members.
However, the most powerful value proposition of AI is enabling enterprises to deploy machine-learning models and train them to use on specific data sets. This takes AI in information management to the next level and turns content into a true information asset. When an enterprise works with its own data to train AI models, it means the AI engine can provide accurate data about a document or an asset. In addition, the AI engine applies metadata completely tailored to the needs and nuances of their business.
The metadata attributes help a user find and retrieve content. However, automated entity extraction offers much more — by delivering more attributes, with greater accuracy, and at a faster pace. This drives applications such as automated image and content capture; the automated launch of workflows and related business processes; even associating new content or assets with pending tasks or work assignments.
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