The Future of Content Management and Artificial Intelligence

The Future of Content Management and Artificial Intelligence

How Intelligent Content Services Will Change Enterprise Content Management

In January 2017, Gartner published a blog titled “The Death of ECM and the Birth of Content Services,” which introduced the concept of content services as a better classification for enterprise content management (ECM). The reason being, content services implies a more strategic approach to content management, rather than one platform to rule the enterprise.

Basically, instead of trying to buy one massive ECM system and plug it into every back office system, you can focus your energy on specific problems, and find solutions for them. If managing contracts is the problem, find a really good contract management solution and deploy it. If HR onboarding is the problem, deploy a really good HR content platform.

The recent surge in mainstream machine learning efforts has had a wide-reaching impact on all facets of technology and business. Anyone who is ignoring Artificial Intelligence (AI) will be left behind, content services (or ECM) included.

So, what Happens When We Add Intelligence to Content Services?

Before we dig deeper, let’s talk about what I mean by “intelligence.” In this context, intelligence is when technology makes decisions that traditionally, were made by humans. This can be as complex as applying machine learning algorithms or artificial intelligence, or it can be as simple as process automation using well-defined criteria.

Blog Image_The Future of Content Management and Artificial Intelligence

One of the biggest frustrations we see with content management products on the market today is the difficulty of organizing and indexing (or tagging) documents and content. What if we could automate this using the aforementioned “intelligence?”

Using a few common machine learning techniques, AI can identify and extract meaning from the content of documents.

  • It can identify the people, places or companies discussed in a document.
  • It can begin to group like-documents together based on their content, using a process called, ‘text clustering’ (many news aggregation services, like Google News, use this approach to group related articles into topics and categories).

When we can automatically tell you what your documents are as they’re loaded into a content services platform, you get a massive productivity boost, cut down on errors and omissions and increase user adoption.  

Using some more advanced text analysis techniques, we can extract values from documents and assess their meaning in the larger context. For example, it’s fairly trivial to identify and extract dollar amounts from a contract. Applying contextual analysis, it’s possible to identify the meaning of this dollar amount – perhaps it’s the sale price of a property or the total principal of loan agreement. When this can be done automatically, we can dramatically speed up contract review processes by highlighting the important values in the contract.

Taking this even further, how can we reduce risk in contracts, and make routine audits far less painful? By analyzing all of your past contracts, and knowing which were problematic from a compliance or audit perspective, we can flag new documents that appear to fit patterns identified in the past.

Applying some process automation, these risky contracts can be routed through more thorough review processes. Auditors are beginning to apply machine learning to the audit process to improve their efficiency and accuracy, and businesses should embrace these new technologies as well.

Production and Workflow Improve when AI and Content Services are in Play

Artificial Intelligence has the potential to change the way we do business in many areas. When content services and ECM embrace AI and machine learning, the possibilities are endless. By automating frustrating and menial tasks, we will see dramatic productivity boosts at all levels of the organization.

The future of content services will be intelligent content platforms that blend machine learning and data analytics with more traditional content management approaches.

Click here to check out WorkLight from RhinoDox, the first intelligent content analytics platform that sits on top of your current technology investments, and adapts to your business needs, not the other way around.


Travis Whelan is the Principal Engineer at RhinoDox. He has been in the software industry for more than 15 years, and in the ECM industry for more than 10. When he’s not a busy Rhino, Travis is pretending he’s in the Chopped kitchen serving up creative meals to his family and friends. It’s unknown whether or not any of them have actually enjoyed his cooking.

 

Katy Tolsky
katy.tolsky@rhinodox.com