What is an AI-powered knowledge base?

The technology field has significantly changed in the last few years, causing all sorts of issues for the elderly and slow adopters. Just to stay in the loop, people have to learn about concepts such as artificial intelligence, the Internet of Things, and machine learning. To make matters worse, some of these technologies have a direct impact on our daily work, forcing us to quickly adapt.

One of the terms that aren’t sufficiently explained is knowledge base. In its essence, the phrase refers to full-access libraries accessible via the Internet. They consist of specific information pertaining to concepts, science fields, services, or products. By accessing a knowledge base, a user can learn more about a specific topic or learn how to use something.

Nowadays, many knowledge bases are powered or enriched through the use of artificial intelligence. This technology works autonomously to provide us with the most relevant data about a specific topic. In this article, we will teach you how the two systems interact and how we can benefit from AI-powered knowledge bases.

AI and knowledge bases

Nowadays, when a user is looking for an answer to something, they usually access information through online knowledge bases. These databases have all the information possible on a specific topic, which means you don’t have to visit secondary sources to learn about a certain concept.

Unfortunately, given that the knowledge bases have so much data, people often struggle to get the answers they need. They’re forced to browse hundreds of pages looking for specific information, which is not only arduous but might also lead them to wrong conclusions.

With artificial intelligence, the use of knowledge bases becomes a breeze. When typing a question in a tab, AI will quickly try to “decipher” the meaning behind the keyword and provide the most relevant answer. This can save you a lot of time as you won’t have to go through dozens of documents.

7 Advantages of using an AI-driven knowledge base for customer support

There are virtually no drawbacks to using AI-powered knowledge bases, while there are lots of benefits. In a nutshell, this technology helps you meet customers’ demands while reducing costs and human labor:

1.    Consistent, quality service

No matter how people are using knowledge bases, artificial intelligence ensures that all of them come to the same conclusions. Given that advanced systems are in charge of the process, users will always be given access to the best, most relevant information for a particular query. This is especially important for company teams that use the same data for education.

2.    Faster problem solving

AI-powered knowledge bases are mostly used in customer service. Unlike human customer support, AI doesn’t need much time to provide feedback. These advanced systems can instantly solve all their issues, thus boosting customer satisfaction.

3.    Less training

Companies that have large customer support teams usually struggle with training, as onboarding many people simultaneously often leads to a loss of productive time. By relying on an AI-driven knowledge base, this becomes a thing of the past.

With the right information that is widely accessible to everyone, teams can provide the same quality of support. Furthermore, having access to the same knowledge base ensures that all answers are standardized.

4.    Reliable retrieval

When sharing the data through the same network, you ensure that the top-tier experts in your company can seamlessly integrate new employees. Basically, there is no loss of information from teacher to student.

5.    Diverse data

One of the biggest issues with traditional databases is that the information within them is not suitable for all departments. By combining AI with various tools and systems, you can organize the data so that the same information is presented in different formats to different departments.

6.    Content relevancy

AI has a proactive role when tackling content. It continuously checks the data for accuracy and relevancy, making sure that it’s up-to-date. In other words, if the data within the database ever becomes obsolete, artificial intelligence will either remove it or update it.

7.    Performance tracking

Nowadays, many AI systems and tools come with analytical features. You can monitor the performance of your customer support center through relevant metrics like average response rate, customer satisfaction rate, the number of resolved cases, and so on.

Methods for improving your AI knowledge base

Despite the fact that AI knowledge bases are autonomous systems, there are always methods to make them even more efficient:

  • Use NLP

Adding improvements to Natural Language Processing can make knowledge bases even more efficient. For example, you can scour the most common questions that people ask and use this information to manually update content. Furthermore, NLP technology is vital for introducing chatbots and voice search features.

  • Leverage ML

Machine Learning, or ML, is a subset of artificial intelligence that focuses on predictive analysis. Companies commonly use this technology to improve the performance of various business activities.

In terms of knowledge bases, you can rely on ML to assess performance and find opportunities and gaps you can exploit. Based on that data, you can enrich information within the knowledge base to further improve your customer service. Through analysis, you can also learn more about user needs and behavior and tailor your feedback based on their requirements.

  • Integration

Software integration has become commonplace within the business world. You can mix and mash your AI knowledge base with various analytics tools and CRM to streamline your customer support process across different departments and channels.

  • Continuous improvement

As mentioned previously, many AI systems come with analytical features. Companies can check the performance of their customer support teams and whether an AI-powered knowledge base is suitable for the users. Based on this data, you can introduce improvements over time to further boost satisfaction rates.

Conclusion

While AI-driven knowledge bases are a relatively new concept, it’s vital that you learn more about the topic as soon as possible. Based on everything we’ve seen so far, this technology will become the basis for modern customer support, so you should try your best to gain a headstart.

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