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  • Tim Jordan

5 Big Knowledge Management Challenges (and How AI Can Help Solve Them)

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Every support manager knows that a knowledge base is an essential tool for providing self-service support and for keeping team members trained and up to speed.

But managing a knowledge base can be time-consuming at best and completely overwhelming at worst — especially if you’re tasked with a complete revamp.

Fortunately, the vast improvements we’ve seen in AI recently means there are plenty of ways that AI can help you manage your knowledge base. Let’s look at some of the common challenges of knowledge management and how you can overcome them to make your knowledge base successful for the long haul.

Challenge 1: Knowledge silos

One of the biggest challenges in knowledge management is getting accurate information from key stakeholders.

You’ll come across this challenge when you’re creating your first knowledge base, revamping your existing knowledge base, or as you’re working to keep your knowledge base updated.

As companies evolve faster, there’s an even greater risk that institutional knowledge and key information about products and processes gets stale. Outdated knowledge is unhelpful — or worse, frustrating — for your customers, so it's a problem every support team needs to figure out how to handle.

The solution: build a knowledge-sharing culture

The only way to solve this challenge is to foster a culture of knowledge-sharing and communication.

This is admittedly easier said than done.

The easiest way to get this started is to start yourself. Share knowledge with other departments that may be useful to them. And then start asking for information in return. Join product roadmap meetings and engineering standups. Don’t assume information will get shared — go chase it down.

Be kind, inquisitive, and collaborative, and over time you’ll see those silos start to break down.

As you figure out where information lives and how to obtain it, you’ll be able to build automated processes and systems that make it easier to surface product changes and updates in the future.

In addition to this, make sure your team members feel heard when they bring up gaps in knowledge and ideas for knowledge base updates. Make it easy for them to bring updates to leadership or make updates to articles themselves.

How AI can help

AI-powered tools can help break down barriers between departments through unified search.

For example, your support team may use Zendesk for their knowledge base while your product team may use Confluence or Notion. A unified search using AI would allow you to search those locations as if they were in the same tool and serve up the information you need.

Tools like Current leverage AI to identify changes across all of your connected tools, then use generative AI to summarize those changes and communicate them in one feed for your whole company.

Challenge 2: Knowledge base searchability

There are two sides to the challenge of knowledge base searchability — internal search and SEO.

In some knowledge base tools, search won’t always give you the answer you’re looking for. It makes finding the right answers difficult, even if they’re there. It’s annoying for both customers and internal users.

SEO optimization is fast becoming a necessity for online customer-facing knowledge bases. The vast majority of customers (92%) use search engines to find information online. This means they not only expect the same level of optimization from brand-specific knowledge bases like yours, but they also expect to have your knowledge base results show up in their search engine results.

Poor searchability within a knowledge base results in finding answers too slowly. This leads directly to increased frustration for customers, higher support ticket volume, and difficult support interactions because the customer is already upset.

The solution: optimizing your articles for search engines

This solution is pretty simple. Optimize your help center articles for search and you’ll see better searchability both within your knowledge base platform and on search engines like Google.

You can also come up with a standardized tag or organization system so your customers have a “hub” to view similar articles with the same labels. Within Zendesk, this involves creating categories and sections that are intuitive and easy to follow.

How AI can help

There are two main ways AI can help with searchability. The first is through Natural Language Processing, or NLP. You can implement NLP algorithms to understand the context and semantics of what your customers are searching for to serve up better results over time. If you’re using a modern knowledge base tool, chances are the search feature already includes some kind of NLP.

The second way is through predictive search suggestions. You can have AI-driven predictive search suggestions appear as your customer types in the search field to deliver results faster. This looks very similar to how Google gives search suggestions based on the mounds of data they have.

Lastly, you can use generative AI — like ChatGPT — to optimize your help center content. A simple prompt can be something like this: I’m going to share a help center article below. This article is intended to help customers [do X]. Can you please share suggestions to optimize the content of this article for search engines?

Challenge 3: Hard-to-read content

We’ve all been there. You click on a blog post with a compelling title, get to the post, and then you have to click away because it’s a messy, poorly formatted mess.

This same thing happens to knowledge bases all the time.

As a customer, one of the worst things you can find is a help article that doesn’t help you in any way. Poor formatting increases the effort it takes to find a solution — and every support team wants to minimize customer effort.

Regardless of the cause, hard-to-read content will prevent your customers and internal teams from getting the help they need.

The solution: prioritize readability

Write your knowledge base articles in a way that is conversational, clear, and concise. Use language your customers would use in titles, tags, keywords, and in the body of the article.

For formatting, make your content digestible by keeping paragraphs short with frequent line breaks.

Give step-by-step instructions with bullet points and numbered lists. Break up the content with screenshots of the steps to take for help.

You can even record a video of what the customer needs to do and place it at the top of your articles for more visual learners.

Then, create a help center style guide so all your articles look the same, no matter who is writing or updating them.

How AI can help

One of the key ways that AI can help make help articles more digestible is by summarizing the content for the customer. You can use AI to automatically provide a quick summary of the steps customers need to take for a how-to, or to summarize the new features of your latest product updates.

Amazon is now taking this approach with customer reviews. They’ve implemented a “Customers say” section that summarizes the content of all the reviews for a product so you don’t have to sift through all the reviews (unless you want to).

Here’s an example of the review summary for an under-the-desk walking pad.

review summary for an under-the-desk walking pad

Generative AI writing tools — like ChatGPT — can really help with this. Once you’ve drafted up a knowledge base article, upload it to ChatGPT and ask it to improve the readability. You can get specific if you’d like — ask it to be humorous, professional, or to write like Ernest Hemingway, if that’s what your brand voice sounds like.

We’re seeing many support helpdesk tools — like Zendesk and Intercom — incorporate features like this that improve the readability or tone of emails your support team sends. It’s a no-brainer to extend this same functionality into your knowledge base.

Challenge 4: Language barriers

Communication breakdowns occur frequently between speakers of the same language. If you’re serving customers across multiple languages, it’s even easier for things to get misunderstood.

For example, suppose your knowledge base is primarily written in English.

For a non-English speaker, it can be hard to decipher what steps need to be taken to solve an issue. This introduces customer friction and the potential for difficult support conversations.

The solution: use AI to translate articles

With the power of AI, it’s easy to translate articles into virtually any language.

Of course this requires knowing your customers’ preferred language(s) as a first step. Once you’ve identified the target languages, make publishing each knowledge base article into those languages a default step in your knowledge management process.

How AI can help

AI can help you get around this challenge easily by translating articles for you. That’s where Swifteq’s Zendesk Help Center Translate app comes in.

Powered by OpenAI’s ChatGPT, the Help Center Translate app can automatically translate your Zendesk Guide articles into virtually any language. It lets you review them before publishing, and allows you to translate them while maintaining the original article’s formatting.

You can even bulk translate multiple articles at once into one or more languages!

Challenge 5: Lack of time

A big challenge in any kind of knowledge management process is a lack of time.

Finding time to create new articles or update existing articles can be extremely difficult with the increased responsibilities that many support teams and leaders take on these days.

Even if your knowledge base is perfect today, you’ll be amazed at how quickly content becomes outdated. Processes change, products are updated, and knowledge gets lost. Every little change requires documentation updates, and this takes time away from whatever else you’re doing.

If your support team is big enough to have a dedicated knowledge manager (or knowledge management team) then this may be less of an issue, but it still won’t go away completely.

The solution: optimize your knowledge management processes

To remedy this challenge, look for efficiencies — both big and small — in your day-to-day processes. This may include finding new tools to use, but it may be as simple as documenting your documentation process or empowering your team members.

Keeping on top of your knowledge base will also help ensure update work doesn’t continue to pile up as well. At a minimum, I’d recommend a quarterly review process for updating knowledge base content.

How AI can help

AI is great at increasing the efficiency of your human team members. It can automate or speed up many of the tasks that make knowledge management time-consuming, such as improving the readability and formatting of new or revised articles (as mentioned above).

You can also use AI to uncover new opportunities (quickly) for your help center. Whether that’s through using a dedicated feedback analytics tool — like Kapiche — or uploading anonymized customer conversations to ChatGPT, AI can quickly analyze why your customers are reaching out. This can help you identify knowledge base content gaps — and you can even use generative AI to draft new help center articles using your support team’s responses in those tickets.

A dedicated help center analytics tool can also save your team time by making it easier to identify areas of your help center that need improvement.

AI can overcome many knowledge management challenges

Your knowledge base is an incredibly powerful tool — but it takes hard work and effort to maintain it and maximize its value.

AI has the potential to help you overcome many of the most common knowledge management challenges. If you aren’t using AI to improve your knowledge base today, it’s a great time to get started.

If your support team uses Zendesk, there’s no easier way to get started on solving many of these challenges than through signing up for a 14-day free trial of Swifteq. We create Zendesk apps that help customer service teams automate and operate more efficiently, without sacrificing the quality of their customer service.


Written by Tim Jordan

Tim is a support manager at and a writer for Supported Content. When he’s not busy leading his team, you’ll find him spending time with his wife and two daughters, usually on some Disney-related activity. He also blogs about personal finance at Atypical Finance.


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