Get more out of your information assets with AI for knowledge management
Jessica Singh Jessica Singh
February 14 5 min

Get more out of your information assets with AI for knowledge management

Knowledge, often in the form of data, is the single most valuable asset a business has today. Yet many organizations are failing to extract value from their information assets -- whether it’s finding a way to capture and share internal expertise or analyzing diverse data points to learn more about what drives customer decision-making. AI provides a novel solution for knowledge management, and it’s helping companies everywhere unlock new value from their data.

What is business knowledge management?

Business knowledge comes in two main forms. The first is customer data. In recent years, companies have raced to accumulate enormous quantities of customer data, building so-called data lakes and applying advanced analytics that will allow them to find out more about their customers.

The second and most often overlooked form is internal information. That’s the knowledge that your employees accumulate and share — in technical reports, meeting notes, and a whole range of intangible information that resides in an individual’s head. It’s also the information that’s most easily lost when employees move on. This information is every bit as valuable as customer data, but is more difficult to quantify, structure and leverage.

The challenge of knowledge management

Customer data and internal information suffer from the same problem. Organizations have a lot of it, be it structured, semi-structured, or unstructured, and more often than not, data is spread around different systems and locations, creating a scenario where insights could be difficult to extract.

Successful organizations understand that constant improvement requires unlocking the potential from their databut sifting through vast amounts of it isn’t easy. Over time, organizations have come up with a wide range of different ways to achieve effective knowledge management. This ranges from software solutions like CRMs and intranets to methodologies like Kaizen and Lean. While there are benefits and drawbacks to each of these, all essentially require end-users or admins to tag and categorize information in a systematic way.

In fact, it’s only with the recent innovations of AI applied to knowledge management that businesses have really begun to seize the value of their business knowledge.

The emergence of AI

Effective knowledge management has been difficult to achieve for many years for two main reasons:

  • Data sources, types, volumes and structures vary across organizations and industries and are complex to map.
  • Technology has long struggled to infer context from information. That means end-users have had to manually tag, categorize or structure the data before any software can effectively interpret it. This process is tedious, time-consuming and takes resources away from more value-adding business tasks.

AI provides a new solution to overcome these challenges, with techniques that infer context and meaning from information and pick up new patterns from unstructured data. With AI that can learn from user behavior, systems continually improve and can evolve together with business targets and constraints.

These are the reasons that AI applied to knowledge management has become increasingly popular in recent years—because it’s almost uniquely equipped to address these difficulties. A range of business departments and functions across industries have realized the value that AI can provide, including manufacturing, research and development, operations, finance, marketing and sales.

Why do you need AI for knowledge management?

We’ve discussed how AI can help with knowledge management. But why is it so important for your business in the first place? Here’s a look at two main reasons.

Seize your knowledge

    A business is made up of the collective knowledge of all the people who have worked there. Much of this knowledge exists in the form of tacit skill sets or is scattered around in stray notebooks, emails and documents. Knowledge and expertise from one employee need to be recorded, quantified, structured and made easily discoverable for every other worker in the organization. With AI, the processes of structuring and discovering this information are made easier than ever.

    Make effective decisions

      The more you know about your customers, the better you can create and target new products and services to them. Many large customers use a CRM system to do this, yet few leverage AI to truly decipher the value of this information. AI and machine learning algorithms are uniquely effective at discovering patterns in data that humans could otherwise spend hours seeking.

      AI applied to knowledge management… in practice

      A wide range of different industries have found ways to put AI for knowledge management into practice. In one particular instance, the marketing department of a startup used AI to better interpret data on the readers of their website content, and the content their competitors were creating. The result? High quality, targeted content.

      In another example, a healthcare specialist improved its internal knowledge management by providing a chatbot that answered employees’ questions during a potentially disruptive office move. It used AI technology that allowed it to understand the context of employees’ questions and relate that back to the relevant information that could answer them.

      Across a whole range of industries, AI is being used to improve knowledge management in exciting ways. And as the technology gets more intelligent and adaptive, the potential for fundamental improvements and new value creation is rapidly growing.