How AI Revolutionizes Your ITSM Knowledge Management

IT service desks can be overwhelmed with repetitive requests, inefficient knowledge retrieval, and outdated documentation. Thankfully, artificial intelligence (AI)-driven knowledge management can help make your IT service management (ITSM) knowledge more accessible, accurate, and actionable. This article explains how AI-powered solutions revolutionize ITSM knowledge management, starting with the limitations of traditional knowledge management before covering how specific AI-enabled capabilities can help.

The issues with traditional ITSM knowledge management

Organizations have long struggled with their ITSM knowledge management capabilities. For example, people-related issues – whether this is people not wanting to share what they know (because “knowledge is power”) or that the focus on the “real work” prevents the creation of new or updated knowledge articles. Or process-related issues such as knowledge content aging quickly and rarely being reviewed. Or technical issues such as poor search functionality, meaning users struggle to find what they need. Plus, the (time and money) cost of maintaining your ITSM knowledge management “ecosystem” might seem excessive if usage is minimal.

The first three examples are all “causes” rather than “effects,” though. Instead, the effect is likely seen as low usage and engagement by end-users and service desk agents. They might avoid your knowledge management system because it’s not easy to use, because of the quality and relevance of the contents, or another reason. However, it’s likely to be the combination of issues, with the status quo unlikely to change without a reinvention of your ITSM knowledge management capabilities.

Thankfully, AI can help. And across various ITSM knowledge management areas, some of which are detailed below.

AI-powered ITSM knowledge management – automated content generation

Generative AI (GenAI) can automatically draft new knowledge base articles from various sources, including:

• Resolved tickets, including agent notes and resolution steps
• Chat transcripts
• Existing knowledge base content
• “Tribal knowledge” stored in siloed internal IT docs or wikis
• Known error and workaround documentation
• Root-cause analysis insights from problem management and monitoring tools
• Third-party guidance, such as vendor product documentation.

The AI can also format its suggested content to align with internal knowledge templates. However, the term “suggested content” is important here – at least initially, the initial drafts should be reviewed by subject matter experts (SMEs) to ensure their accuracy and suitability.

This AI capability makes knowledge article creation much easier and quicker, with SMEs no longer needing to create knowledge articles from scratch on top of what they likely consider “their day job.” Consequently, resolution knowledge related to the most common and recent IT issues can be quickly documented and made available to help others with similar needs.

AI-powered search

Traditional ITSM knowledge management relied on keyword-based search. Even with the addition of alternative search terms, it was hit and miss, especially for end-users, given the likelihood that they don’t use IT terminology.

AI-powered search replaces keyword matching with natural language search capabilities that understand the context and user intent. It opens up access to knowledge articles by:

• Interpreting end-user questions that use everyday language
• Surfacing the most relevant knowledge articles based on meaning, not just keywords
• Learning from previous search success and failure to improve future search accuracy.

ITSM knowledge management success can be considered a little “chicken and egg,” in that the more existing knowledge is successfully leveraged, the more likely people are to use your knowledge management capabilities (as well as be inclined to create new knowledge articles).

AI-powered ITSM knowledge management – contextual recommendations (for IT staff)

As with search, IT staff recommendations also used keyword matching. So, an agent might be shown ten “relevant” articles while working on a ticket, but this would be based on keyword volumes and not necessarily article relevancy. It helped, but perhaps not as much as it could.

Thanks to AI-powered recommendation capabilities, that work in a similar way to the aforementioned AI-powered search, service desk agents can now receive various “pushed” content in real-time, including:

• Suggestions of relevant knowledge articles
• Details of the resolution steps used in similar tickets
• Related known issues or recent change alerts.

Importantly, users will expect and demand quality responses from corporate ITSM knowledge management capabilities – because with the consumerism of AI currently in play, users’ expectations are equally high for any internal use cases of AI.

These real-time, context-aware recommendations speed up IT support resolutions (and reduce costs), improve quality and consistency, and deliver better end-user experiences.

AI-powered ITSM knowledge management – virtual agents and conversational chatbots (for end-users)

This is similar to the IT staff capability above, but this time, it facilitates self-help (and much more effectively than traditional IT self-service portals).

Conversational AI chatbots can be made available via various IT support channels, including the portal, as a standalone capability, a mobile app, or within corporate collaboration services such as Microsoft Teams or Slack.

While IT support staff might view an AI-powered chatbot capability as benefitting them by preventing easy-to-solve issues and requests from hitting the IT service desk as tickets, the real value is for end-users. With chatbots providing them with a consumer-like service and support capability that allows them to quickly get the IT assistance they need. Plus, the help is available 24/7, not just when the corporate IT service desk is open. This includes:

• Instant answers to common IT questions
• Easy-to-follow troubleshooting steps
• Backend automations for simple tasks, such as password resets and software provisioning.

As with the earlier capabilities, a key differentiator is that the AI better understands what the end-user needs than traditional ITSM knowledge management and chatbot search capabilities, meaning that the responses and actions are more likely to provide the required assistance.

AI-driven knowledge updates

Knowledge article curation and management is a time-consuming manual task for IT service desks. Even with pre-defined article review alerts, it still might be an IT support task that gets deferred and potentially never rises to the top of to-do lists.

Thankfully, AI can help. It can continuously review the use and performance of knowledge articles:

• Identifying knowledge article gaps, based on the tickets still hitting the IT service desk, and providing draft articles to fill them
• Flagging knowledge articles with low end-user engagement or negative feedback (for human review and improvement)
• Recommending updates that improve knowledge article clarity or accuracy
• Archiving or consolidating redundant knowledge articles.

There’s so much potential to improve ITSM knowledge management using AI. What would you add to this view of how AI revolutionizes things? Please let me know in the comments.