Reducing Information Overload With AI

An AI knowledge management system provides a central location where employees can ask questions anonymously...

Lack of contextualization

Data is important. But, when organizations only use 32 percent of theirs, and much of it lies within silos, organizations don't get a complete picture of their business and instead experience information overload. 

Your organization's information becomes redundant, outdated, and useless without contextualizing data. With information trapped in silos, data goes unused, and pieces to your organization's puzzle go missing.

Your employees should not be dealing with the effects of information overload. Everyone should have the ability to complete tasks and solve problems on time, focus on and hit business targets, and increase overall productivity. 

New technology has provided (limited) support while creating new problems. It's time for a system that reduces information overload and actively manages and contextualizes the information, enables employees to find answers fast, and allows everyone to access the experts within their organization.

How to prevent information overload with AI

Preventing an overload means actively managing the volume of information produced and kept while verifying the quality, making information within your organization accessible to everyone, and decreasing the time it takes for employees to access information. This can reduce information overload with the support of AI.

Manage and contextualize data

As much as we love data, it's time to stop hoarding it and start managing it. An effective way is with artificial intelligence. AI can recognize when and what information is outdated or redundant. AI repairs data overload by forgetting unnecessary data and recycling useful (quality) information to manage data and prevent an overload. In addition, AI can provide a better picture of your business because, with permission, it can see through silos and access non-sensitive information from your internal tools. Accessing information from more points draws better conclusions at scale, limits the number of sources to search to find information, and creates a centralized location to map your organization's knowledge and the contributing people.

Contextualization helps everyone better understand and use the information available.

Find a system to answer questions effectively

Employees find answers faster when you actively manage organizational data and information overload. However, when answers to questions reside within your organization's knowledge blind spot, everyone wastes too much time searching for the information or people to solve their business problems.

Having a system to answer questions effectively shrinks your organization's knowledge blind spot. An AI knowledge management system provides a central location where employees can ask questions anonymously and creates a repository of questions and answers within your organization. The AI automatically tags related topics and generates a list of previously asked and answered questions when writing a query. If your question doesn't currently exist, you can post your question. Because of the AI-generated tags, the colleagues who are most likely to know the answer are instantaneously notified to answer the questions quickly.

Another benefit to a system like this is that you can ask (anonymously) and answer the redundant questions you receive from colleagues daily. And when the answer is no longer correct or outdated, instead of colleagues coming back to you for an updated solution, you can edit your original response and avoid reanswering hundreds of questions from colleagues. This reduces the number of notifications you receive from colleagues with questions, saves you time from answering unnecessary queries, allows you to focus more on completing the work that matters, and alleviates information overload.


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