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Why AI-Powered Search is a Game-Changer for Knowledge Management

Emily DiLeo June 18, 2024

Generative AI, large language models (LLMs), and machine learning (ML) have enabled huge leaps in knowledge management functionality - this has a direct, positive impact on your business.

This article is a deep dive into one of these capabilities: intelligent search. I will explain how it works and why it plays a crucial role in a modern business model, from my perspective as a librarian, archivist and knowledge management specialist.

The problem of findability

As a knowledge management specialist in UX, I help companies make their customer research findable, accessible and shareable. One pain point that I have seen over and over is a lack of findability - people have difficulty simply locating past research.

What kind of research have we done on this product feature?

Did another team do this research already?

The person would then spend their time searching in various tools, databases and folders. This is a very frequent struggle for researchers, designers, and product managers - and just one example of how often we perform search-and-find in our workday.

From keyword search to intelligent search

Now, let’s understand how the search experience has made great leaps forward with LLMs and AI. The 1990s and early 2000s was all about keyword-based searching. A keyword search works by utilizing an index of information, not unlike the index you might find in the back of a book. The process works like this:

1

As the name implies, keyword searching is heavily reliant on the keyword that is used. So if the user submits an inaccurate keyword, they won’t find what they are looking for. And if the user doesn’t know exactly what they’re looking for, it is unlikely that they’ll discover relevant research that they didn’t know about.

Intelligent search is completely different. This search uses a model (developed by Google in 2017) that searches for meaning rather than the simple presence of a keyword. Let’s call this feature “semantic functionality” (semantic = meaning).

2 (1)

Semantic functionality is really the game-changer here. It means that the system can interpret a query by searching for meaning - synonyms, related terms, context, even colloquial terms. No stone is left unturned!

Not only is intelligent search a must-have for any tool that relies on search functionality, it opens the door to additional AI-based features that have the potential to change the experience of search.

AI assistant as a “personal librarian”

No one understands (and feels) the frustrations of a poorly functioning search better than librarians.

Many of you have experience with library catalogs, in public or academic settings. They have made great improvements in recent years, but were generally very difficult to use. Librarians like myself would teach entire classes on searching the catalog, because unless you knew how the catalog worked, it was impossible to fully leverage it for search and discovery. I would also conduct “research interviews”, in which I would ask the user to tell me about what they were looking for. I would then suggest keywords or adjacent subject areas to explore.

AI-powered features of an intelligent search provide complete answers to search questions, with summaries and a list of citations. The “smart assistant” within a search even suggests search questions, based on past behavior of the user. In essence, AI is acting as a “personal librarian”.

The user experience of intelligent search

Intelligent search and AI-powered assistants elevate the user experience of search in the following ways:

  • Engagement: users are more likely to engage with a platform that includes these features. Rather than struggling to find what they’re looking for, their questions are answered by a helpful guide.

  • Discoverability is greatly enhanced. Because search functionality is greatly improved, users are exposed to a wider variety of relevant content when they search. This is essential for sound decision making, in that the decision-maker is taking various and multiple information sources into account.

It should be noted here that these advanced features require an excellent user interface, so as not to overwhelm the user. In addition, information about security and transparency should be easily accessible, so that users know how and where their Personal Identifiable Information (PII) will be used and stored.

The business implications of intelligent search

There are a wealth of statistics out there that prove the ROI of knowledge management, and intelligent search figures prominently into them.

  • Employees spend 1-2 hours per day looking for information, and according to a study of 1000 American employees by Panopto, over 60% of them have trouble finding what they are looking for. With accuracy and speed, intelligent search can solve this problem.

  • Because intelligent search makes information more discoverable, better decisions can be made using a wider array of information.

  • By making the compilation and synthesis of information much quicker, room is made for strategy and innovation (what humans do best!).

  • Intelligent search can democratize research and analysis, by increasing access to information across the organization.

  • Intelligent search facilitates knowledge sharing, which is crucial to business success.

If you aren’t leveraging intelligent search in your business, you should be! Choose tooling that has an excellent user interface, a well-built AI assistant, and transparent security features. You’ll be well-positioned to increase efficiency and employee satisfaction.