With 91% of people willing to use a knowledge base (KM) to solve their issues, it’s easy to see why so many companies have started focusing on this area. The good news is that Artificial intelligence (AI) has been touted as a revolutionary technology for KM. Here are six ways AI will shape knowledge management in the future.
1. Enhance Knowledge Discovery and Collection
The first and most important impact of AI is that it can help you discover and collect information for your knowledge base.
AI platforms have the ability to analyze big data sets and identify the resources being used most frequently.
This means that you can deploy AI to monitor the materials your team uses the most and create suggestions for you to fill in your knowledge base.
2. Result in More Impactful Applications of Big Data
Besides collecting information, AI is also a great tool for KM because it helps you analyze patterns and figure out which steps you need to take next.
For instance, AI has helped large companies like Repsol reduce nonproductive time by 50% across key sites.
Likewise, AI can help you identify the areas of your knowledge base that see the most usage and determine how to improve these resources.
3. Identify the Best Features with More Ease
Do you need to have a search function? Is your knowledge base categorized correctly? Would it be better to provide written or video resources to your team?
AI is a great way to answer all of the questions above, which in turn can help you determine what functionalities and features your platform should have.
4. Facilitate Advanced Analytics
AI is already used to collect and analyze advanced statistics in other areas, and KM is no exception.
As a matter of fact, AI can help collect more intricate data, analyze it over longer periods, and identify patterns that would be difficult for human users to spot.
This can help unveil crucial information, analyze it from different angles, and create more accurate predictive models.
5. Personalization of Content Delivery
Each team member in your company has a unique search pattern, but it’s possible to accurately predict which resources these users will look for based on their prior behavior.
While this task may be challenging for human users, chatbots can quickly go through the data and help provide personalized content suggestions.
6. Prevent Loss of Data
AI algorithms require a robust infrastructure and extensive databases, so implementing this technology will inherently reduce the chances of experiencing large-scale data loss.
Not only this, but AI KM systems can enforce data handling policies and create backups automatically, which contributes to a stronger data storage mechanism.
Areas of AI with the Most Impact on Knowledge Management
Artificial intelligence technology is an umbrella term that covers a huge collection of algorithm-powered software and hardware. As such, there are distinct areas that will have a much bigger impact on internal and external KM systems.
Here are two areas of AI that will help usher your knowledge management system into a new era.
Advancements in deep learning have resulted in complex algorithms that give artificial intelligence technology the ability to mimic human capabilities. This includes the ability to interpret images or create writing from scratch.
New algorithms that use even bigger data sets are part of the future of AI, so you need to keep a close eye on advancements in this area and how they impact your KM system.
Simply put, a chatbot is a piece of AI software designed to provide answers and help users accomplish different tasks.
Chatbots are important because they humanize AI and allow your team to use this technology in a simple way.
Now, not all chatbots are the same. You need to find (or create) an alternative that understands your business, has the technical requirements you need, and will therefore boost your company’s efficiency.
Challenges of AI in Knowledge Management
While AI can become one of the keys to efficient knowledge management, it’s also important to understand its challenges before implementing this technology.
Artificial intelligence is still in its early stages, so it’s necessary to stay updated with the latest advancements. If not, you run the risk of running your KM system on a dated platform.
Not only this, but other challenges you need to consider are the following:
Unfortunately, there is no set security standard for the implementation of AI.
Not only this but there are many AI models that parse data and extract information in ways we’ve never seen, so it’s important to evaluate how this will impact data security.
Therefore, it’s essential to implement a strict security policy when adopting AI for knowledge management. This should include requirements like:
- Using a virtual private network (VPN): A VPN encrypts your connection and makes it extremely difficult to intercept or access your data.
- Use multi-factor authentication: Multi-factor authentication ensures that only authorized users access your knowledge base.
- Only allow users to access relevant information: You should also set up different access levels for users and only allow stakeholders to access data relevant to them.
A Lack of a Clear Strategy
One of the biggest mistakes that companies make is implementing AI for knowledge management without a clear strategy.
There are countless applications of AI in the KM context. However, implementing this technology the wrong way can create significant issues that are expensive to fix.
For instance, if the AI model used isn’t trained properly, it won’t deliver timely data to users or understand which resources are related to specific scenarios.
As we’ve mentioned before, AI technology is still in its early stages. Therefore, there are limitations that you need to consider before you implement machine learning and other forms of artificial intelligence.
For instance, AI doesn’t have the ability to efficiently identify new issues and create entire articles from scratch.
Instead, you should evaluate the current capacities of AI and only implement this technology in areas where it’s a proven resource.
Difficulties Setting Up the Right Company Culture
One of the biggest challenges you may face has nothing to do with AI technology itself, but how it’s received by your team.
It’s normal for users to show a bit of resistance to change, especially if they believe AI may replace them at some point.
As such, it’s your duty to provide the right training, establish a positive company culture around AI, and ensure that your team is comfortable with this technology.
This will help ensure a better KM system, from the way data is collected from the primary sources to how it’s delivered to your team.
To Wrap Up
Knowledge management has had a huge influence on the success of leading companies for decades, even before the term was coined.
Now, innovative technologies like AI are starting to transform the current state of KM and will undoubtedly shape its future.
As long as you focus on your team and consider the challenges of implementing AI into your KM system, you’ll be able to improve the flow of information in your company and use technologies like machine learning to your advantage.