How Content Cognition will Drive Information Management Innovation 

Content cognition is transforming enterprise information management, saving teams hundreds of hours on manual tasks, and enabling staff to focus on higher-level responsibilities.

Recently, we commissioned IBRS to produce a report examining the perspectives, strategies, and experiences of senior information and technology specialists regarding the potential of content cognition in information management solutions.  

For your clarity, IBRS summarises content cognition as the ability of AI in data management to automatically inspect documents at scale and extract specific data, such as contract value, the existence of private or sensitive information, dates and so on.  

According to the report, ‘Content Cognition to the Rescue‘, a number of organisations and enterprise information management professionals still don’t believe content cognition, and AI in general, will improve how they’re managing business information. But it also shows that the majority have changed their perspective.  

In fact, the IBRS report shows that the majority of organisations are already factoring content cognition into their future information management strategies (71% stated it was likely or very likely) indicating a major shift in how organisations approach data management and analytics.  

This isn’t a surprising change, considering the overwhelm of information hyperinflation and organisations’ inability to meet compliance requirements, or even identify their legal and contractual risks.  

The goal of content cognition is to identify high-risk data, minimise exposure, and safeguard critical information, while offering broader value to organisations.

Organisations don’t always know where all of their data is, or what’s in their data, or the context and value of that data.  

Content cognition services can help solve this challenge by:

• Extracting critical data from complex documents
• Identifying document type, context, and organisational value
• Driving business data analytics and strategic decision making
• Enhancing compliance and governance processes  

This level of detail also allows organisations to map out their data analytics and management risks, apply data sensitivity labelling, and apply governance and information lifecycle rules with great accuracy – enabling greater automated information management at scale.  

In addition, content cognition creates a rich metadata layer which is critical for AI in data management initiatives. It enables organisations to curate highly accurate and cleansed data to fuel content generation. This means you can receive sophisticated outcomes based on highly accurate data – this is the kind of value that content cognition can provide.  

But we’ve only just begun to explore all of the uses of content cognition and AI in information management.

According to the IBRS report, organisations are currently focused on solving their ability to manage hyperinflation and data protection, but as AI continues to automate routine tasks and processes, we’ll see a freeing of the human workforce. 

This might mean a boost in productivity and innovation, faster data analysis, and a significantly speedier design and implementation process.  

But some organisations are looking beyond those more immediate benefits to consider possibilities in financial impact analysis, personalised customer experiences, and better customer service. Once organisations are able to effectively use AI for enterprise data management, they’ll be able to unlock the full potential of the technology for an impact on the entire business.  

With heavy augmentation of the tasks performed by information management teams, what will future information management teams do?

Most information managers I’ve spoken with spend a lot of time maintaining EDRM solutions and even more time ensuring staff follow the rules. This is not a great use of their expertise and time.  

With the introduction of AI-driven information management services, that role will shift to a more strategic, quality focus.  

Information management teams will move into a more consultative role as business partners, identifying all of the potential for exacting and leveraging their organisational data. They’ll be able to link previously disconnected information assets, have access to real-time analytics, and minimise the effort put into remaining compliant by automating routine tasks and applying best practices.  

Most technology revolutions are about automating the mundane or the manual, and AI is making it possible to extend the realm of opportunity. 

For more information on how AI will drive the next wave of information management innovation, download the full IBRS Report below or head to our dedicated IBRS Report Hub.