Knowledge Management FAQ

Have a specific question about knowledge management?

This FAQ answers many of the practical questions we hear from executives, technology leaders, and organizations exploring knowledge management—from governance and information architecture to AI, taxonomy, metadata, and getting started.

New to knowledge management? Start with our Executive Guide to Knowledge Management for a broader introduction before diving into these questions.

Editor's Note: This article was originally published in 2016 and is periodically reviewed and updated to reflect current practices, emerging technologies, and new developments in knowledge management. Last substantially updated: July 9, 2026.

Section 1: Knowledge Management Fundamentals

These questions provide a foundation for understanding knowledge management as a discipline. If you're looking for practical implementation guidance, you'll find that in the sections that follow.

What Is Knowledge Management (KM)?

Knowledge management (KM) is the discipline of helping organizations create, organize, share, govern, and apply knowledge so people can make better decisions and work more effectively.

Organizational knowledge includes far more than documents. It encompasses policies and procedures, project history, research, institutional memory, lessons learned, subject matter expertise, and the context behind important decisions. Effective knowledge management helps ensure that people can find, trust, and apply that knowledge when they need it.

Modern knowledge management isn't simply about building a repository or implementing a new technology platform. It's about designing the organizational practices, governance, and supporting technology that make knowledge easier to create, maintain, discover, and reuse over time.

Looking for a broader introduction? Read our Executive Guide to Knowledge Management for a deeper exploration of what knowledge management is, why it matters more than ever, and how organizations can build it as a long-term organizational capability.

Why Does Knowledge Management Matter?

Every organization depends on knowledge. The question isn't whether that knowledge exists—it's whether people can actually find it, trust it, and use it effectively.

As organizations grow, knowledge naturally becomes more distributed across people, teams, and technology platforms. Without an intentional approach to managing it, organizations often spend increasing amounts of time searching for information, recreating work, onboarding new employees, and relying on a handful of individuals who have become the unofficial keepers of institutional knowledge.

Knowledge management helps organizations improve decision-making, preserve organizational memory, reduce duplicated effort, support collaboration, and create a stronger foundation for AI and future growth.

For many organizations, knowledge management becomes increasingly important as they mature. The informal practices that worked well for a small team often become difficult to sustain as the organization grows and becomes more complex.

Related reading: What is Knowledge Management?

Is Knowledge Management the Same as Documentation?

No. Documentation is an important part of knowledge management, but it represents only one piece of a much larger picture.

Most organizations already have documentation. The challenge is that people often struggle to determine where information lives, which version is current, who maintains it, or whether it can be trusted. Creating more documents doesn't necessarily solve those problems.

Knowledge management also includes governance, ownership, information organization, search, shared practices, and the day-to-day habits that help knowledge remain useful over time. It recognizes that valuable organizational knowledge exists not only in documents, but also in conversations, expertise, project history, and the reasoning behind important decisions.

Good documentation supports knowledge management. It doesn't replace it.

For a deeper discussion of this common misconception, see Over-Documentation Isn't Knowledge Management.

What Problems Does Knowledge Management Solve?

Organizations rarely seek out knowledge management because they're interested in the discipline itself. More often, they're trying to solve practical business challenges.

Knowledge management can help organizations address issues such as:

• Staff spending too much time searching for information.
• Teams recreating work that already exists elsewhere.
• Multiple versions of the same document creating confusion.
• Critical knowledge leaving when employees retire or change roles.
• Long onboarding periods for new staff.
• Inconsistent decision-making across departments.
• Difficulty preparing organizational knowledge for AI and automation.
• Information becoming increasingly fragmented across multiple systems.

These challenges are often symptoms of organizational growth rather than signs that something is fundamentally wrong. As organizations become more complex, they benefit from moving beyond informal knowledge-sharing practices toward more intentional approaches that support collaboration, continuity, and informed decision-making.

Section 2: Strategy & Organizational Maturity

These questions explore how organizations approach knowledge management strategically, including ownership, success measures, organizational growth, and how to get started.

Who Owns Knowledge Management?

A common questions we hear is, "Who should own knowledge management?"

The answer depends on the organization.

Knowledge management is inherently cross-functional. It touches technology, operations, human resources, communications, records management, information governance, learning and development, and executive leadership. Because of that, there isn't a single department that's always the right home.

In many organizations, knowledge management begins within IT, operations, or a business unit that recognizes the need for better information sharing. As the organization matures, however, successful knowledge management almost always becomes a shared organizational capability rather than the responsibility of a single individual or department.

Regardless of where it formally resides, executive sponsorship is critical. Knowledge management isn't simply a technology initiative or documentation project—it's an organizational capability that requires leadership support, clear ownership, and ongoing attention.

Learn more: Knowledge Management Consulting

Does Every Organization Need Knowledge Management?

Every organization manages knowledge in some way, whether intentionally or not.

For a small organization with only a handful of employees, informal knowledge sharing may work quite well. People can easily ask questions, decisions are made collaboratively, and information is often easy to find because everyone knows who created it.

As organizations grow, however, those informal practices become more difficult to sustain. Teams become larger, work becomes more specialized, technology platforms multiply, and institutional knowledge becomes increasingly distributed across people and systems.

Not every organization needs a formal knowledge management program. Nearly every organization, however, benefits from thinking intentionally about how knowledge is created, organized, shared, maintained, and governed.

The goal isn't to add unnecessary process. It's to ensure that organizational knowledge continues to support the mission as the organization evolves.

How Does Knowledge Management Change as Organizations Grow?

Every organization manages knowledge, whether intentionally or not. What changes over time isn't the need for knowledge management—it's the level of structure required to support the organization.

Small organizations often rely on informal conversations and shared context. People know who to ask, decisions happen quickly, and knowledge flows naturally.

As organizations grow, those informal practices become harder to sustain. Teams become more specialized, work spans departments, technology platforms multiply, and institutional knowledge becomes more distributed. Organizations often discover they need clearer governance, more consistent information organization, and better ways to preserve knowledge over time.

The goal isn't to add unnecessary process. It's to ensure that knowledge continues to support the organization's mission as it grows and evolves.

Learn more: How Knowledge Management Evolves as Teams Grow

How Do You Know If You Have a Knowledge Management Problem?

Organizations rarely decide to invest in knowledge management because someone identifies a "KM problem." More often, they recognize a collection of operational challenges that all point back to the way knowledge is managed.

Some common indicators include:

• Staff spend significant time searching for information.
• The same questions are asked repeatedly.
• Teams recreate work that already exists.
• Important knowledge lives with a small number of people.
• New employees take longer than expected to become productive.
• Different departments organize information in different ways.
• AI tools produce inconsistent or unreliable results because the underlying information isn't well organized.

These challenges don't necessarily mean something is broken. In many cases, they're signs that the organization has reached a level of complexity where informal knowledge-sharing practices are no longer enough.

Learn more: How Do You Know You Have a Knowledge Management Problem? (Originally published in 2013)

How Do You Measure Knowledge Management Success?

Knowledge management doesn't have a single success metric.

Instead, organizations should look for improvements in how knowledge supports everyday work.

Some useful indicators include:

• New employees become productive more quickly.
• Staff spend less time searching for information.
• Teams reuse existing knowledge instead of recreating work.
• Important decisions are easier to understand because their context has been captured.
• Institutional knowledge is preserved during staff transitions.
• AI tools produce more accurate and consistent results because they have access to better-organized information.

Ultimately, successful knowledge management is reflected in organizational outcomes rather than the number of documents produced or the amount of information stored. The question isn't "How much knowledge do we have?" It's "How effectively are we using what we know?"

What Can Leaders Do to Support Knowledge Management?

Leadership has an enormous influence on whether knowledge management succeeds.

Organizations are far more likely to develop strong knowledge-sharing habits when leaders model those behaviors themselves. That includes documenting important decisions, sharing lessons learned, encouraging collaboration across teams, recognizing people who contribute organizational knowledge, and treating knowledge as a strategic asset rather than an afterthought.

Knowledge management is rarely successful when it's viewed as someone else's responsibility. Leaders help establish the culture, expectations, and priorities that make knowledge sharing a normal part of everyday work.

Learn more: Leading By Example: Seven Knowledge Management Practices.

How Much Does Knowledge Management Consulting Cost?

Knowledge management consulting varies considerably depending on the organization's size, goals, and current level of maturity.

Some organizations begin with a focused current-state assessment that identifies strengths, challenges, and practical recommendations. Others engage in longer-term strategy development, governance design, information architecture, technology advisory services, or ongoing executive consulting.

Because every organization starts from a different place, we typically scope engagements based on business objectives rather than a predefined package of services.

In our experience, organizations often discover that the cost of improving knowledge management is significantly less than the ongoing cost of duplicated work, lost institutional knowledge, inefficient onboarding, and time spent searching for information.

Learn more: Knowledge Management Consulting

How Long Does a Knowledge Management Initiative Take?

Knowledge management is best viewed as an ongoing organizational capability rather than a project with a fixed end date.

That doesn't mean organizations need years before they see results.

Many organizations identify meaningful improvements through an assessment and roadmap within a matter of weeks. Governance can often be strengthened incrementally. Search, information organization, and documentation practices can improve over time without requiring a complete redesign of existing systems.

The most successful organizations typically take a phased approach. They focus first on the areas that create the greatest operational value, then continue building knowledge management capabilities as the organization evolves.

Progress matters more than perfection. A practical, sustainable approach almost always produces better long-term results than attempting to solve every knowledge management challenge at once.

Where Should We Start?

If your organization is just beginning to think about knowledge management, resist the temptation to start with technology.

Instead, begin by understanding where people experience friction today. Where is time being lost? Which knowledge is most difficult to replace? Which information do people trust—and which do they avoid? Which business processes depend heavily on a handful of individuals?

Those conversations often reveal opportunities to improve knowledge management without requiring large technology investments or major organizational change.

Most successful initiatives begin with understanding how knowledge currently flows through the organization and then making targeted improvements over time.

Learn more: Knowledge Management Consulting and What Is Knowledge Management?

With the growing interest in AI, many organizations are asking how knowledge management and artificial intelligence fit together. The next section explores some of the most common questions we hear.

Section 3: AI & Knowledge Management

Artificial intelligence has renewed interest in knowledge management, but many organizations are still figuring out how the two fit together. These are some of the most common questions we hear from leaders preparing for AI.

Historically, executives often understood that better knowledge management would be useful, but it competed with dozens of other priorities. AI changes that calculation. Suddenly, improving the quality, organization, and governance of knowledge isn't just about helping employees find information—it's about enabling an entirely new way of working.

Can AI Replace Knowledge Management?

No.

AI can help people find, summarize, and interact with organizational knowledge, but it doesn't replace the work of creating, organizing, governing, and maintaining that knowledge.

In fact, AI often highlights the importance of knowledge management. If organizational knowledge is incomplete, outdated, inconsistent, or difficult to trust, AI will often surface those weaknesses much faster than people did in the past.

Knowledge management provides the foundation. AI provides new ways to access and use that knowledge.

Organizations that invest in both tend to see much better results than organizations hoping AI will solve long-standing organizational knowledge challenges on its own.

Learn more: AI Doesn't Fix Knowledge Gaps. It Exposes Them

Why Is Knowledge Management Important for AI?

Every AI system depends on the quality of the information it can access.

Whether you're implementing Microsoft 365 Copilot, ChatGPT Enterprise, Claude for Enterprise, Google Gemini, or another AI platform, the quality of the responses is heavily influenced by the quality of the organization's knowledge.

Organizations that have clear ownership, thoughtful governance, consistent information organization, and reliable sources of truth are generally much better positioned to adopt AI successfully.

Knowledge management helps organizations answer questions such as:

• Which information should AI have access to?
• Which content is authoritative?
• Who owns that information?
• Is it current?
• Is it appropriate to use for decision-making?

Those aren't AI questions.

They're knowledge management questions.

Learn more: Architecting for AI: Why the Future of AI Starts with the Decisions You're Making Today

Can AI Organize Our Documents for Us?

AI can certainly help classify content, generate summaries, suggest metadata, identify duplicate documents, and improve search.

Those capabilities are valuable, but they don't eliminate the need for human judgment.

Organizations still need to decide:

• how information should be organized
• who owns it
• how long it should be retained
• what should be considered authoritative
• what AI should and shouldn't have access to

AI can accelerate parts of the work. It doesn't replace the organizational decisions that make knowledge management effective.

Should AI Have Access to Everything?

Usually not.

One of the biggest misconceptions about enterprise AI is that it should simply be connected to every document and every system.

In reality, organizations should take a more thoughtful approach.

Before expanding AI's access, it's worth understanding:

• where sensitive information lives
• whether permissions reflect current business needs
• whether content is accurate and current
• whether duplicate or outdated information should be cleaned up
• whether governance policies are in place

Preparing organizational knowledge for AI is often just as important as selecting the AI platform itself.

How Does Microsoft 365 Copilot Fit into Knowledge Management?

Microsoft 365 Copilot doesn't create organizational knowledge. It helps people interact with the knowledge that already exists across Microsoft 365.

That means Copilot's usefulness depends heavily on how information is managed within SharePoint, Teams, OneDrive, Outlook, and other Microsoft 365 services.

Organizations with well-organized information, clear governance, and appropriate permissions often see stronger results because Copilot has access to more trustworthy knowledge.

Organizations with inconsistent information frequently discover that Copilot reflects those inconsistencies rather than resolving them.

For many organizations, preparing for Copilot is really a knowledge management initiative.

Should We Clean Up Our Knowledge Before Implementing AI?

One of the biggest changes we've seen over the past few years is that AI has fundamentally changed the return on investment for knowledge management. Organizations are discovering that improving their knowledge ecosystem doesn't just help people—it also enables better AI.

Perfection isn't necessary—but preparation is valuable. Organizations don't need to reorganize every document before exploring AI. In fact, waiting until everything is "perfect" often delays meaningful progress.

Instead, we typically recommend identifying high-value knowledge first. Focus on the information that supports critical decisions, important business processes, customer service, research, or other mission-critical work.

Improving governance, clarifying ownership, reducing obvious duplication, and identifying authoritative sources can significantly improve AI outcomes without requiring a complete redesign of existing systems.

Knowledge management and AI readiness are best approached as complementary efforts that evolve together over time.

What's the Biggest Mistake Organizations Make When Preparing for AI?

Many organizations assume that AI readiness is primarily a technology project.

In practice, the biggest challenges are usually organizational.

Questions about ownership, governance, information quality, institutional knowledge, and organizational habits often have a much greater impact on AI success than the choice of AI platform itself.

Organizations that begin by understanding their knowledge ecosystem are generally better prepared to make thoughtful decisions about AI adoption, governance, and long-term strategy.

Technology matter, but the quality of the underlying knowledge matters even more.

Section 4: Information Architecture & Organization

Good knowledge management depends on more than technology. Information architecture, taxonomy, metadata, and related concepts help organizations organize knowledge so it's easier to find, understand, and maintain over time.

What Is Information Architecture?

Information architecture (IA) is the practice of organizing information so people can easily find, understand, and use it.

Think of it as designing the structure of an organization's knowledge rather than simply deciding where documents should be stored.

A good information architecture considers questions such as:

• How should information be organized?
• How should people navigate it?
• What terminology should the organization use?
• How should related information connect to one another?
• How will people find what they need months or years from now?

Information architecture is one of the foundational disciplines that supports effective knowledge management. When it's done well, people spend less time searching for information and more time using it.

What Is a Taxonomy?

A taxonomy is a structured way of organizing and categorizing information.

Most organizations already use taxonomies, whether they realize it or not. Department names, project categories, document types, product lines, and subject classifications are all examples of taxonomies.

A well-designed taxonomy creates consistency. It helps people organize information in similar ways, improves search, and makes it easier to browse large collections of content.

Taxonomies should reflect how an organization actually works—not simply how technology happens to organize files.

What Is Metadata?

Metadata is often described as "data about data," but a more practical way to think about it is simply information that describes other information.

Examples include:

• Author
• Department
• Project
• Document type
• Client
• Date created
• Approval status
• Confidentiality level

Good metadata makes information easier to search, filter, organize, and manage over time. It also supports governance by helping organizations understand what information they have and how it should be handled.

Metadata is most valuable when it's simple, consistent, and aligned with the organization's actual work.

Related reading:

• Meaningful Metadata for Discoverability and Findability, Part 1 (originally published in 2015)
• Meaningful Metadata for Discoverability and Findability, Part 2 (originally published in 2015)

What's the Difference Between Taxonomy and Metadata?

Taxonomy and metadata work together, but they serve different purposes.

A taxonomy defines the categories an organization uses to organize information.

Metadata describes an individual piece of information using those categories.

For example, a taxonomy might define standard document types such as Policy, Procedure, Research Report, and Meeting Notes.

Metadata identifies that a specific document is a Research Report, belongs to the Operations department, relates to Project Phoenix, and was approved in March 2026.

Together, taxonomy and metadata improve consistency, search, reporting, governance, and AI readiness.

Read more about metadata and taxonomies:

• Meaningful Metadata for Discoverability and Findability, Part 1 (originally published in 2015)
• Meaningful Metadata for Discoverability and Findability, Part 2 (originally published in 2015)

What Are Controlled Vocabularies?

A controlled vocabulary is an agreed-upon set of terms that an organization uses consistently.

For example, one team might refer to "Human Resources," another to "HR," and another to "People Operations." A controlled vocabulary establishes a preferred term so information is categorized consistently.

Controlled vocabularies reduce ambiguity, improve search, and make reporting more reliable.

They're particularly valuable in larger organizations where different departments naturally develop different terminology over time.

What Is a Knowledge Map?

A knowledge map helps organizations understand where important knowledge exists and how it flows throughout the organization.

Unlike a document inventory, a knowledge map doesn't necessarily list every file. Instead, it identifies:

• critical knowledge areas
• subject matter experts
• important business processes
• key information sources
• dependencies between teams
• potential knowledge risks

Knowledge maps are particularly useful when organizations are preparing for AI, planning for succession, or trying to reduce reliance on a small number of individuals.

What Is a Knowledge Graph?

A knowledge graph is a way of representing relationships between people, information, concepts, systems, and other organizational knowledge.

Rather than storing information in isolated folders or documents, a knowledge graph focuses on the connections between different pieces of knowledge.

Modern AI systems increasingly use knowledge graphs to improve search, recommendations, and reasoning because they help provide context that traditional file structures often lack.

Most organizations don't need to build a formal enterprise knowledge graph immediately, but understanding how information relates across the organization is becoming increasingly valuable.

Do We Need All of These Things?

Not necessarily.

Many organizations hear terms like taxonomy, metadata, information architecture, and knowledge graphs and assume they need a complex information management program before they can improve knowledge management.

In practice, the goal isn't to implement every concept. It's to apply the right level of structure for the organization's size, complexity, and needs.

A small nonprofit and a global pharmaceutical company won't need the same information architecture or governance model. Good knowledge management isn't about maximizing complexity—it's about creating enough structure that people can reliably find, trust, and use organizational knowledge.

Section 5: Knowledge Sharing, Organizational Learning, and Knowledge Retention

Knowledge management isn't only about organizing information. It's also about helping knowledge move throughout an organization. These questions explore how organizations capture, share, and build on what they know.

What Is Knowledge Sharing?

Knowledge sharing is the process of making knowledge available to other people so they can use it in their own work.

That can happen formally through documentation, training, Communities of Practice, or mentoring. It also happens informally through conversations, collaboration, coaching, and day-to-day work.

Effective knowledge sharing isn't about encouraging people to document everything they know. It's about creating an environment where valuable knowledge can move efficiently across teams, projects, and organizational boundaries.

Knowledge management provides the structure that supports knowledge sharing. The two are closely related, but they're not exactly the same thing.

Why Don't People Share Knowledge?

Most people don't intentionally withhold knowledge.

More often, knowledge sharing breaks down because people are busy, don't know what's valuable to others, or don't have easy ways to capture and share what they've learned.

Sometimes organizational incentives unintentionally discourage sharing. People may worry about losing influence, assume someone else already documented the information, or simply not realize how important their experience has become over time.

The solution is rarely asking people to write more documentation. Organizations are generally more successful when knowledge sharing becomes part of everyday work rather than an additional task people are expected to complete after everything else.

Most organizations don't lose knowledge because people refuse to share it.

They lose it because no one realized how valuable it had become until it was gone.

What's the Difference Between Tacit and Explicit Knowledge?

One of the foundational concepts in knowledge management is the distinction between tacit knowledge and explicit knowledge.

Explicit knowledge has been documented in some form. Policies, procedures, reports, research, manuals, meeting notes, and databases are all examples.

Tacit knowledge exists in people's experience, judgment, intuition, and practical know-how. It's often much harder to document because it develops through doing the work rather than simply reading about it.

Strong knowledge management recognizes the value of both. While not every piece of tacit knowledge can or should be documented, organizations benefit from finding practical ways to share expertise before it disappears through turnover or organizational change.

What Is Institutional Knowledge?

Institutional knowledge refers to the collective understanding an organization develops over time.

It includes historical context, lessons learned, relationships, decision-making practices, technical expertise, organizational culture, and the countless details that help people understand not just what to do, but why things are done that way.

Institutional knowledge often accumulates gradually and quietly. It also disappears more easily than many organizations realize.

Preserving institutional knowledge doesn't mean documenting every conversation. It means identifying the knowledge that's most critical to the organization's mission and creating sustainable ways to retain it over time.

How Do You Preserve Institutional Knowledge?

Institutional knowledge is rarely lost all at once. More often, it disappears gradually as people change roles, retire, or leave the organization.

The most effective organizations don't wait until someone gives notice to think about knowledge capture. Instead, they build practices that preserve important knowledge as work happens.

That may include documenting key decisions and their rationale, capturing lessons learned, encouraging cross-training, creating Communities of Practice, and identifying areas where too much knowledge depends on a single individual.

The goal isn't to document everything. It's to preserve the knowledge that's most important to the organization's mission.

Learn more: Don't Let Knowledge Walk Out the Door: 5 Knowledge Retention Tips

What is Knowledge Retention?

Knowledge retention is the practice of ensuring that important organizational knowledge remains available even as people change roles, retire, or leave the organization.

It's one component of a broader knowledge management strategy.

Organizations often think of knowledge retention only during offboarding. In reality, the most successful organizations build knowledge retention into everyday work by documenting decisions, encouraging collaboration, mentoring newer staff, and making knowledge easier to share across teams.

Knowledge retention is less about preserving the past than it is about ensuring the organization can continue learning and adapting over time.

How Do You Capture Institutional Knowledge?

There's no single technique that works for every organization.

Different types of knowledge require different approaches.

Examples include:

• documenting important decisions and why they were made
• recording lessons learned throughout projects
• interviewing subject matter experts
• creating reusable templates and playbooks
• mentoring and cross-training
• Communities of Practice
• knowledge maps
• collaborative documentation

One of the most effective approaches is making knowledge capture part of everyday work rather than treating it as a separate effort. Small, consistent habits generally produce better long-term results than occasional documentation sprints.

Learn more: 5 Ways to Incorporate Knowledge Capture into Everyday Operations

What's the Difference Between Knowledge Capture and Knowledge Transfer?

Knowledge capture focuses on preserving knowledge so it remains available in the future. That may include documenting decisions, recording lessons learned, creating playbooks, or building knowledge repositories.

Knowledge transfer focuses on helping knowledge move from one person or team to another. Mentoring, cross-training, Communities of Practice, and collaborative project work are all examples of knowledge transfer.

Most organizations need both. Capturing knowledge without helping people apply it limits its value. Relying entirely on person-to-person knowledge transfer, however, creates risk when people leave or organizational priorities change.

Strong knowledge management intentionally supports both capture and transfer.

Learn more: Knowledge Capture and Knowledge Transfer

What's the Biggest Risk to Organizational Knowledge?

One of the biggest risks is the single point of knowledge.

This happens when one individual becomes the only person who understands a critical process, customer relationship, technical system, or organizational decision.

Single points of knowledge often develop gradually and unintentionally. They usually reflect experience and dedication rather than poor planning.

Over time, however, they create organizational risk.

Knowledge management helps organizations identify these dependencies and create practical ways to distribute knowledge before it becomes a crisis.

Small organizations can face some of the greatest knowledge risks because so much important information lives with just a few individuals. Everyone "just knows" how things work – until someone goes on leave, changes roles, or leaves the organization.

Small organizations usually don't need elaborate knowledge management programs, but they benefit tremendously from identifying critical knowledge, documenting important decisions, encouraging cross-training, and building habits that preserve institutional knowledge as the organization grows.

Learn more: The Most Overlooked Risk in Small Organizations? What You Don't Know.

How Do You Reduce Knowledge Loss During Employee Turnover?

The best time to think about knowledge transfer is long before someone resigns.

Organizations that consistently preserve knowledge tend to:

• identify critical knowledge areas
• encourage cross-training
• document significant decisions
• capture lessons learned
• build mentoring relationships
• create shared ownership for important processes
• review knowledge risks periodically

Exit interviews can be valuable, but they shouldn't be the organization's primary knowledge retention strategy.

How Do You Preserve Knowledge When Someone Leaves?

Organizations often think about knowledge capture during offboarding, but by that point much of the opportunity has already passed.

Knowledge retention works best when it's part of normal operations rather than a last-minute activity.

Some practical approaches include:

• documenting important decisions and their rationale
• encouraging cross-training
• identifying single points of knowledge before they become organizational risks
• creating opportunities for mentoring and knowledge transfer
• capturing lessons learned throughout projects rather than only at the end

Organizations don't need to capture everything. They do need to identify which knowledge is most important to preserve and build sustainable habits for keeping it accessible.

What Are Communities of Practice?

A Community of Practice (CoP) is a group of people who regularly share knowledge around a common area of expertise or professional interest.

Communities of Practice are less about formal reporting structures and more about helping people learn from one another. Members exchange ideas, solve problems together, share lessons learned, and build expertise across organizational boundaries.

Many organizations naturally develop informal Communities of Practice. Others intentionally support them through regular meetings, collaboration spaces, mentoring, or shared learning activities.

Communities of Practice remain one of the most effective ways to strengthen knowledge sharing because they focus on people and relationships rather than documents alone.

Is Knowledge Sharing the Same as Knowledge Management?

Not quite.

Knowledge sharing is one of the ways knowledge moves through an organization.

Knowledge management is the broader discipline that supports that movement through governance, information architecture, organizational practices, technology, leadership, and culture.

You can think of knowledge sharing as one important capability within a larger knowledge management strategy.

Organizations with strong knowledge management practices generally make knowledge sharing easier because people know where information belongs, how to find it, and how to contribute without creating unnecessary complexity.

What Should We Document?

This question comes up all the time. The short answer: not everything.

Organizations create new knowledge every day, and attempting to document every conversation, meeting, and decision is neither realistic nor desirable – and honestly, it wreaks havoc when too much documented knowledge is introduced to AI and chatbots.

Instead, focus on documenting knowledge that is:

• difficult to recreate
• critical to the mission
• frequently reused
• important for compliance
• needed for onboarding
• foundational for AI

Good knowledge management is about intentionality rather than volume.

Section 6: Governance & Related Disciplines

Knowledge management intersects with several other disciplines, including information and data governance, records management, and content management. These fields are closely related, but they have different goals and responsibilities.

Table: Overview of Related Disciplines

What's the Difference Between Knowledge Management and Information Governance?

Knowledge management and information governance are complementary disciplines.

Knowledge management focuses on helping people create, share, find, and apply knowledge so they can make better decisions and work more effectively.

Information governance focuses on ensuring that information is managed appropriately throughout its lifecycle. That includes policies related to ownership, security, privacy, compliance, retention, and risk.

A simple way to think about the difference is this:

• Knowledge management asks: How can we make better use of what we know?
• Information governance asks: How should this information be managed responsibly?

Most organizations benefit from both.

What's the Difference Between Knowledge Management and Records Management?

Records management focuses on identifying, protecting, retaining, and disposing of official organizational records in accordance with legal, regulatory, and business requirements.

Knowledge management has a broader scope. It includes many types of organizational knowledge that aren't formal records, including project knowledge, lessons learned, research, institutional memory, and subject matter expertise.

Records management is an important part of an organization's information ecosystem, but it isn't a substitute for knowledge management.

What's the Difference Between Knowledge Management and Data Governance?

Data governance focuses on the quality, consistency, ownership, and appropriate use of structured data.

Knowledge management focuses on helping people use organizational knowledge, much of which exists outside traditional databases.

The two disciplines increasingly overlap, particularly as organizations adopt AI. High-quality data supports better analytics, while well-managed organizational knowledge supports better decisions, collaboration, and AI-assisted work.

Organizations often benefit from coordinating these efforts rather than managing them independently.

What's the Difference Between Knowledge Management and Document Management?

Document management focuses on storing, organizing, versioning, and controlling access to documents.

Knowledge management is broader.

Documents are one important source of organizational knowledge, but they represent only part of what an organization knows. Knowledge also exists in people, conversations, decisions, workflows, research, and institutional experience.

Document management helps organizations manage files.

Knowledge management helps organizations manage knowledge.

What's the Difference Between Knowledge Management and Content Management?

Content management focuses on creating, publishing, organizing, and maintaining content, particularly for websites, intranets, customer communications, and digital experiences.

Knowledge management focuses on helping people find, trust, and apply organizational knowledge wherever it exists.

Many content management systems support knowledge management initiatives, but implementing a CMS does not automatically create a knowledge management program.

What's the Difference Between Knowledge Management and Digital Asset Management (DAM)?

Digital Asset Management (DAM) systems help organizations manage rich media such as images, video, audio, graphics, presentations, and marketing materials.

Knowledge management may include digital assets, but it also encompasses many other forms of organizational knowledge.

Organizations with large creative, marketing, research, or communications teams often use both DAM and knowledge management practices together.

How Does Governance Support Knowledge Management?

Governance provides the structure that allows knowledge management to scale.

As organizations grow, governance helps answer practical questions such as:

• Who owns this information?
• Who is responsible for maintaining it?
• Which version is authoritative?
• Who can access it?
• When should it be reviewed or archived?

Good governance doesn't exist to create bureaucracy.

Its purpose is to create confidence that people—and increasingly AI systems—are using knowledge that is trustworthy, current, and appropriate for the task at hand.

Organizations with strong governance generally find that knowledge becomes easier to maintain over time because responsibilities and expectations are clearer.

Do Small Organizations Need Governance?

Usually, yes—but not the same kind of governance as a large enterprise.

Governance should be proportional to an organization's size, complexity, and risk.

A small nonprofit doesn't need dozens of committees or lengthy policy documents. It does benefit from simple, shared expectations about where information belongs, who maintains it, how sensitive information is handled, and which sources should be considered authoritative.

As organizations mature, governance typically evolves alongside them.

The goal isn't to create more process than necessary. It's to establish enough structure that knowledge remains useful, trustworthy, and sustainable as the organization grows.

Section 7: Technology & Knowledge Management

Technology plays an important role in knowledge management, but successful knowledge management begins with people, processes, and governance—not software. These are some of the technology questions we hear most often.

Is SharePoint a Knowledge Management System?

SharePoint is a powerful platform that can support knowledge management, but implementing SharePoint alone doesn't create a knowledge management program.

Organizations are often surprised to discover that the same SharePoint environment can work extremely well for one organization and become frustrating for another. The difference is rarely the technology itself. It's how information is organized, governed, maintained, and used.

When paired with thoughtful information architecture, governance, and organizational practices, SharePoint can become an excellent foundation for knowledge management. Without those elements, it often becomes another place where documents accumulate over time.

Can Microsoft Teams Replace a Knowledge Base?

Not entirely.

Microsoft Teams is designed primarily for collaboration and communication. Conversations, files, and decisions often begin there, but Teams isn't intended to serve as the organization's long-term source of institutional knowledge.

Organizations are generally most successful when they distinguish between collaboration spaces and knowledge repositories. Teams helps people work together today. Knowledge management helps ensure that important knowledge remains available tomorrow.

Do We Need a Knowledge Base?

Maybe—but not every organization needs a dedicated knowledge base.

The more important question is whether people can easily find and trust the information they need.

For some organizations, that may involve a traditional knowledge base. Others may rely on SharePoint, an intranet, a customer support platform, a wiki, or a combination of systems.

Technology decisions should support how the organization works rather than define it.

What's the Best Knowledge Management Software?

There isn't a single "best" knowledge management platform.

The right technology depends on factors such as:

• organizational size
• existing technology investments
• governance requirements
• security needs
• collaboration patterns
• regulatory obligations
• long-term goals

Organizations often achieve better results by improving how they use existing platforms before investing in new ones.

The technology landscape continues to evolve rapidly, particularly with AI. A thoughtful strategy generally delivers more value than chasing the latest platform.

Can We Improve Knowledge Management Without Buying New Software?

Often, yes.

Many organizations already own capable technology through Microsoft 365, Google Workspace, Atlassian, or other enterprise platforms.

The larger opportunity is frequently improving governance, information architecture, ownership, and organizational practices rather than replacing technology.

Organizations are often able to make significant progress by clarifying how existing systems should be used and making it easier for people to find, trust, and contribute knowledge consistently.

How Much Technology Does Good Knowledge Management Require?

Less than many organizations expect.

Technology should reduce friction rather than create it.

The goal isn't to build the most sophisticated knowledge ecosystem possible. It's to create an environment where people can confidently create, find, share, and apply knowledge as part of their everyday work.

Good technology supports good organizational practices. It doesn't replace them.

Continue Exploring

If you're just beginning to explore knowledge management, these resources provide a good place to continue:

• What Is Knowledge Management? (Executive Guide)
• Knowledge Management Consulting
• AI Doesn't Fix Knowledge Gaps. It Exposes Them.
• Over-Documentation Isn't Knowledge Management
• Knowledge Management in 2026
• Architecting for AI: Why the Future of AI Starts with the Decisions You're Making Today