ITSM Knowledge Management: Implementation Best Practices

Effective ITSM knowledge management is necessary for delivering consistent, high-quality IT services. Knowledge is often called the most valuable asset for IT teams, but its true value comes from how well it is captured, shared, and kept up to date. ITIL 4 defines the purpose of knowledge management as enabling the efficient and convenient use of information and knowledge across the organization.

When done right, ITSM knowledge management reduces ticket volumes, accelerates resolution times, and improves overall service quality. It also helps organizations align IT operations with business goals, increase employee satisfaction, and create smoother, more reliable processes. This article explores the best practices for ITSM knowledge management and how they can transform support teams into a more proactive and user-focused function.

Summary of ITSM knowledge management best practices

Here is a summary of ITSM knowledge management best practices to be covered: 

Define a clear and actionable ITSM knowledge management strategy

Turning knowledge into lasting value starts with a clear plan. The plan should clearly outline how service knowledge fits your organization, from key systems to daily processes. Once you see where and how this knowledge is used, you can decide how to collect it, store it, and share it. The approach essentially helps teams work faster, deliver better services, and keep employees happy.

Metrics

A significant aspect of the knowledge management practice is making sure the right knowledge is available to the right people at the right time. This applies not only to IT teams who deliver services but also to those teams who consume such services and rely on quick, accurate answers to do their jobs effectively.

To track whether the knowledge management practice is effective, organizations need clear objectives and measurable outcomes. COBIT 2019 highlights a few measurable metrics, such as:

• Percentage of IT staff having the right knowledge as per the required competence level

• Number of new IT knowledge articles accessed within 90 days

• Percentage of IT staff who have attended knowledge-sharing sessions

• Average user-assessed usefulness score for knowledge resources

• Percentage of resolved cases aided by knowledge resources

That said, the scope shouldn’t stop with IT. Employees across the business also benefit when knowledge is easy to find and apply. For instance, accessing the knowledge base to find policies, process guidance, and answers without having to raise a ticket. 

The following metrics can offer valuable insights:

• Self-service adoption rate (how often employees use knowledge portals instead of raising tickets)

• Search success rate (how often employees find what they need on the first attempt)

• Reduction in repeat queries on the same topics

• Employee satisfaction with the accessibility and clarity of knowledge resources

Culture

According to the ITIL 4 practice guides, knowledge management culture varies between organizations and is a source of competitive advantage. Foster a culture of knowledge sharing by building an open atmosphere that encourages learning within and across teams, increasing the organization’s ability to absorb and apply knowledge. Stakeholders in the IT ecosystem play a key role in putting the knowledge management strategy into action. It is important to identify their requirements at every stage of the IT service lifecycle and ensure appropriate buy-in for all initiatives. 

Resources

Finally, your organization’s leadership should support the knowledge management strategy by ensuring that resources are allocated to support initiatives. This includes staff training and awareness, as well as investment in tools and technologies. Organizations that are most successful in implementing ITSM knowledge management develop both people and technology-oriented aspects, and this requires financial resources to be committed to relevant strategic initiatives.

Establish a formal process for ITSM knowledge management

A formal approach to ITSM knowledge management helps identify, integrate, and harness critical knowledge assets necessary to enhance IT service delivery. The organization or team responsible for delivering IT services to end users should implement formal processes to capture, analyze, present, and review ITSM knowledge across the service lifecycle. 

ITIL 4 describes this as your knowledge management practice’s Environment Establishment process, where all stakeholders understand the nature of ITSM knowledge and are willing to create, utilize, and share it. The main activities in this process include:

Knowledge Management Environment Establishment process (Source: ITIL 4)

1. The ITSM knowledge manager, in collaboration with the designated IT team leads, reviews and analyzes organizational information, knowledge flows, and stakeholder feedback to assess the current culture of knowledge use and sharing.

2. This knowledge team reviews external factors that impact the current knowledge system and explores emerging practices in data, information, and knowledge management.

3. Based on the previous steps, the team determines how the knowledge management approach should best support the organizational strategy and identifies areas for improvement.

4. The ITSM knowledge manager logs the improvements and works with the team to implement them.

5. The team develops relevant guidance and training materials, sharing them with stakeholders during planned training and awareness sessions. Information about adoption and satisfaction is incorporated into these materials.

Democratize knowledge sharing

Embedding ITSM knowledge management best practices into everyday work essentially means making it easy for everyone to share what they know. The knowledge team should put together simple guidelines and FAQs so IT practitioners understand how to add value to the knowledge base.

While doing so, it is worth noting that knowledge sharing isn’t just for team leads, which means every staff member has something worth contributing. A knowledge base resource could be an article, a step-by-step guide, or lessons learned from solving an issue. If it’s useful to someone else in the service lifecycle, it must be in the shared knowledge library.

Training should also be part of IT onboarding. From day one, new hires should be aware of where to find the right information and how to share their own. In the long run, this creates a culture where knowledge flows freely and helps everyone deliver better services.

Review AI-generated content

Thanks to generative AI, drafting and updating knowledge is now faster, smarter, and more consistent than ever. Instead of starting from a blank page, tools like Freddy AI Copilot can instantly draft knowledge articles from resolved tickets, suggest updates to outdated content, and reformat solutions into easy‑to‑use FAQs. 

To accelerate knowledge article creation, AI tools can:

• Automatically generate a draft from resolved incidents or service requests, capturing the issue and resolution steps.

• Suggest relevant solutions or pre‑populates article templates using insights from past tickets.

• Rephrase content for clarity, organizes it into sections (like symptoms, cause, and resolution), and makes it easier to read.

• Flags outdated knowledge and produces updated drafts to ensure accuracy.

• Repurpose content into FAQs, chatbot responses, and other formats for use across multiple support channels.

Of course, these AI‑created drafts are not meant to bypass people. While AI tools can speed up the authoring process, it is recommended to implement a process for validation, review, and reinforcement learning. As one of the common challenges with large language models is hallucination (the generation of incorrect information with high confidence), the ITSM knowledge management process should ensure that a human reviews the AI-generated knowledge article before it is published in the knowledge base, especially where it involves critical knowledge about IT systems’ operations.

Assign roles and responsibilities for ITSM knowledge management

Knowledge is not limited to a few individuals, but a knowledge manager plays a key role in guiding and shaping the culture to ensure the organization maximizes the value of knowledge assets across the IT service lifecycle.

Depending on the size and setup of the organization, this role might be assigned to a dedicated person to oversee the ITSM knowledge management process. This role is typically responsible for:

• Creating awareness of the knowledge management process

• Review and approve the quality of knowledge articles

• Coordinating knowledge culture and capabilities-building initiatives

• Oversee the activities of the knowledge team

• Track metrics and drive continuous improvements in knowledge management

This knowledge manager role does not operate in isolation; instead, it is strengthened by the support of a cross-functional IT knowledge team. They are subject matter experts in their domains and work together to implement the IT knowledge management strategy and processes. 

Part of the team’s responsibility is to make knowledge management a consistent practice across every business unit of an enterprise, so no matter where knowledge is generated, it becomes a shared organizational asset. This includes reviewing and sharing any knowledge generated, whether by people or AI, within their areas of expertise. They also gather feedback from knowledge base users and pass it to the knowledge manager, who analyzes and tracks it as part of continual improvement initiatives.

Leverage technology for enhanced ITSM knowledge acquisition and sharing

The ITSM knowledge management practice is heavily dependent on technology and automation for effectiveness. Imagine a scenario where a team of system administrators is troubleshooting an infrastructure outage and must sift through volumes of documentation and emails to determine the cause and subsequently restore services. Restoring service would be a significant undertaking, and it would likely not be well-received by management and users. 

Now, if there were an ITSM system with a well-documented knowledge base, the team could quickly access architectures, configuration scripts, and troubleshooting manuals that could speed up the resolution actions.

It is best practice to deploy ITSM systems that integrate knowledge articles within standard ITSM process workflows. For example, when querying an IT service within a service catalog, the system can display links to knowledge articles related to requests for accessing and using the service. Another example is knowledge articles referenced during the creation of a change request that guide the installation and configuration of dependent system components.

Intelligent search tools

When agents or employees repeatedly search for something but find no results (or poor results), it signals a gap in the knowledge base. Likewise, if search often returns duplicate or conflicting articles, it points to the need for consolidation. As part of your knowledge management practice, implement intelligent search capabilities that not only retrieve information but also learns from usage. In practice, that means better article recommendations, smart links to similar issues, and clues about where the knowledge base needs updating.

To be most effective, a knowledge article’s search should span across all the places where knowledge lives. That means having consolidated structured records (like tickets, CMDB entries, and system logs) and unstructured content (like documents, videos, meeting transcripts, and vendor contracts) into a single, consistent interface where everything can be tagged, related, and shared. Once consolidated, knowledge can be organized with tags and relationships, then shared across the team. That way, agents spend less time searching for answers, and everyone else has the details they need for projects, routine tasks, or one‑off requests.

These repositories are most valuable in day‑to‑day ITSM work, where they allow agents to resolve incidents and requests more quickly by surfacing the right knowledge at the right time. When integrated with learning management systems (LMS), these repositories can become an even more powerful resource for ongoing professional development and access to relevant knowledge directly within their training workflows.

We cannot discuss technology in ITSM knowledge management without mentioning the impact of AI on content generation and analysis through large language models. Modern ITSM teams can use LLMs to improve knowledge reuse, such as suggesting relevant knowledge base articles in Slack or MS Teams, so employees get immediate answers and avoid raising unnecessary tickets. AI can also support ITSM analytics by scanning records for patterns and anomalies, giving teams early visibility into recurring issues or emerging risks. By the end of the cycle, AI complements knowledge management by both extending the reach of existing knowledge and strengthening the insight IT teams can draw from their data.

Freddy AI Agent suggesting solution articles

Monitor, measure, and improve ITSM knowledge practices

Your knowledge management practice must ensure that only the right information reaches the right people at the right time. To know if that’s happening, consider measuring how knowledge is being created, shared, and reused. Instead of manually collecting numbers about knowledge usage, you can pull the data that’s already generated inside the ITSM system itself.

Most ITSM platforms already capture this activity inside their own modules, which makes them a natural source of reporting. For example:

• The incident module records when an agent links a knowledge article to resolve a ticket — data you can report as “% of incidents resolved with knowledge.”

• The request module tracks when a user’s request is resolved via a self‑service article — giving you metrics like “requests deflected through self‑service.”

• The knowledge module logs how many articles are created, updated, viewed, or rated — often considered essential metrics such as “article freshness” or “usefulness score.”

Combined with user feedback, this data also shows which practices work well, where gaps exist, and whether there is a scope for your knowledge base to evolve.

Though these metrics only matter if they help IT teams perform better in practice. Remember that the goal is to improve immediate, operational key performance indicators (KPIs) that IT managers and team leads mostly care about. Examples:

• If knowledge articles are updated frequently → agents can resolve tickets faster.

• If knowledge quality is high → fewer mistakes, less rework, and more first‑contact resolutions.

• If knowledge repositories are effective → agents spend less time searching, so productivity improves.

Once these operational improvements are in place, they naturally support broader business benefits (like better employee experience, fewer outages, or lower IT costs). But the link is step‑by‑step: metrics → team KPIs → business outcomes.

 The following illustration indicates success scores and percentages for representation purposes only. Actual outcomes and improvements can vary based on specific organizational contexts, implementation strategies, and individual use cases.

Knowledge management metrics & value flow

Knowledge management metrics & value flow

Deploying an AI‑driven knowledge database makes these connections even stronger. It supports the shift‑left approach by giving users and first‑line support agents quick access to the knowledge they need. As a result, fewer issues are escalated to higher‑tier IT support or external vendors.

Knowledge teams should then review metrics on a regular basis, alongside user feedback and industry trends. This helps them spot opportunities to improve information, processes, tools, and even team culture. 

Continuous improvement driven by metrics, analytics, and stakeholder feedback

This should also involve identifying trending employee issues (through analytics and AI) to build support articles around those topics, which can help deflect tickets, improve employee experience, and reduce agent workload. The knowledge manager should then consolidate and drive the implementation of these improvements in line with changes to the IT environment and business needs. 

Conclusion

Most IT teams collect knowledge, but only a few manage it well. Knowledge management needs executive attention. It should be funded, given ownership, and supported by the right tools and culture.

When that happens, the benefits are many: faster ticket resolution, fewer escalations, and smoother changes. The best practices discussed in this article are straightforward. Consider pairing the recommendations with analytics and AI to spot trends early and deflect recurring issues. Above all, make continuous improvement part of the culture.

If you’d like to see how these practices work in action, try the Freshservice demo and explore how modern, AI‑driven knowledge management can strengthen every part of your IT service operation.