In recent years, the conversation about technology has centered on concepts such as data, artificial intelligence, automation, and intelligent agents.<\/p>\n\n
We’re talking less and less about documents.<\/p>\n\n
And yet, documents remain at the heart of virtually every business process.<\/p>\n\n
Why?<\/p>\n\n
Because data and documents serve different purposes. Understanding that difference is becoming increasingly important for managing information effectively and leveraging all the knowledge that exists within an organization. <\/p>\n\n
A piece of data answers a question. A document explains the story. <\/strong><\/p>\n\n A piece of data may indicate that an invoice amounts to 12,500 euros.<\/p>\n\n But the accompanying document provides answers to many other questions:<\/p>\n\n The data summarizes the information.<\/p>\n\n The documents provide context.<\/p>\n\n And context remains essential for correctly interpreting information, understanding processes, and making better decisions.<\/p>\n\n Artificial intelligence also needs context<\/strong><\/p>\n\n One of the major advances in artificial intelligence is its ability to analyze large volumes of information in a very short amount of time.<\/p>\n\n But even the most advanced models need to understand the context of what they are processing.<\/p>\n\n It’s not enough to simply access a dataset. They also need to know: <\/p>\n\n For this reason, there is increasing talk of connecting artificial intelligence solutions with corporate document repositories.<\/p>\n\n Not to replace them, but to make use of the knowledge they contain and facilitate access to relevant information at any given time.<\/p>\n\n Documents remain the language of organizations<\/strong><\/p>\n\n Contracts.<\/p>\n\n Records.<\/p>\n\n Reports.<\/p>\n\n Blueprints.<\/p>\n\n Procedures.<\/p>\n\n Policies.<\/p>\n\n Correspondence.<\/p>\n\n Although many processes are now fully digital, a large portion of business knowledge continues to be expressed and preserved through documents.<\/p>\n\n And that doesn’t seem likely to change.<\/p>\n\n What is changing, however, is the way we access them.<\/p>\n\n A few years ago, we were looking for documents. Today, we’re starting to look for answers. <\/p>\n\n However, those responses continue to be based on information that, in most cases, is contained in documents.<\/p>\n\n Not all information is structured<\/strong><\/p>\n\n Databases store structured information: names, dates, amounts, statuses, references, or indicators.<\/p>\n\n But much of an organization’s knowledge is not organized in that way.<\/p>\n\n It is spread across reports, contracts, technical specifications, manuals, procedures, emails, minutes, and internal communications.<\/p>\n\n That is precisely where records management continues to play an essential role.<\/p>\n\n Because it does more than just store and organize files.<\/p>\n\n It organizes knowledge, establishes relationships between pieces of information, and enables that knowledge to be retrieved, shared, and used securely.<\/p>\n\n From Document to Knowledge<\/strong><\/p>\n\n Perhaps the most important change is not that documents are disappearing.<\/p>\n\n The thing is, we’re changing the way we interact with them.<\/p>\n\n We used to look for a specific file.<\/p>\n\n Now we hope to ask a question and get an answer right away.<\/p>\n\n But for that to be possible, the information must first be well organized, managed, classified, and linked.<\/p>\n\n Artificial intelligence can speed up access to knowledge. It can analyze documents, locate relevant information, identify relationships, and help answer complex questions. <\/p>\n\n But that knowledge needs a solid foundation on which to build.<\/p>\n\n If the documents are outdated, duplicated, disconnected, or lack a proper structure, the responses obtained may also be incomplete or unreliable.<\/p>\n\n\n
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