Back to Basics: What is Knowledge Management?
As we move deeper into the era of artificial intelligence, it is important to not just tie knowledge management to the development of AI, but to resist knowledge management principles to establish a foundation for where the conversations between AI teams and KM practitioners need to take place. This post offers an simple answer to the question, What is Knowledge Management?
(cover image by OpenAI from a prompt by the author.)
Knowledge Creation
Knowledge creation starts with environments that encourage inquiry and experimentation. It’s not always about invention—it’s often about synthesis. When people are empowered to reflect, collaborate, and think critically about what they know and what they need to know, new knowledge emerges. Organizations that prioritize knowledge creation design workflows that accommodate serendipity and learning—not just execution. This is where strategy and insight first come into play, long before documentation or tooling.
Knowledge Capture
Capturing knowledge requires intentional design. Not everything people know is captured by default—especially when knowledge lives in experiences, practices, or intuition. Effective capture strategies bridge the gap between tacit and explicit knowledge. That might mean documenting lessons learned, recording decisions, or building structured ways to reflect on projects. Without capture, knowledge evaporates with turnover and time.
Knowledge Sharing
Sharing knowledge is a social act, not just a technical one. Systems alone won’t make it happen. It depends on culture, trust, and the belief that what you know is valuable to others. Good KM programs build incentives and norms around contribution. They create physical and digital spaces for sharing—places where expertise meets need. And they help people move from hoarding to helping, especially in hierarchical or siloed environments.
Knowledge Utilization
Utilization is where knowledge earns its keep. It’s not enough to store it—it has to inform action. Utilization happens when knowledge is easy to find, relevant, and trustworthy. It also requires alignment with workflows and decisions. If people can’t apply knowledge in context, they won’t use it. The best KM efforts integrate knowledge access where the work happens, reducing friction and increasing confidence in use.
Knowledge Retention
Retention is about reducing loss—especially in the face of churn, retirement, or restructuring. It starts by identifying what knowledge is critical and at risk. Then it moves to mitigation: mentoring, cross-training, storytelling, and archiving. Retention strategies shouldn’t be backloaded at the point of exit—they need to be woven into daily practices so knowledge is continually transferred and preserved.
Knowledge Evaluation
Evaluation keeps knowledge from going stale. It challenges assumptions, refreshes content, and ensures that what’s documented still aligns with current reality. Evaluation also provides feedback loops—helping knowledge creators understand what’s useful and what’s not. Without evaluation, KM becomes a digital landfill. With it, knowledge stays sharp, relevant, and adaptive.
Technology and Tools
Tools matter, but only when they serve people and processes. KM technology should support search, curation, contribution, and governance. That includes everything from content management systems to AI assistants. But too many tools without integration—or without clear purpose—undermine KM. Successful programs invest in usable, interoperable systems with clear roles in the knowledge lifecycle.
Leadership Pulling the Levers of Culture
Culture and leadership anchor everything else. Leadership sets the tone by modeling knowledge behaviors—sharing openly, asking questions, learning visibly. Culture determines whether people feel safe and valued when they share what they know or admit what they don’t. Without leadership support and a knowledge-positive culture, KM strategies won’t scale. This is where change either gains traction or dies quietly, however,,,,
…as I write in Management by Design, I try to avoid working with clients on “culture.” I suggest, rather, looking at the levers of culture, such as policy, practice, technology and space. Talking about creating a knowledge-sharing culture is much less effective than leaders encouraging sharing behavior by interacting with the repositories rather than say, answering side chats or e-mails that don’t contribute to community knowledge that reinforce behaviors that silo knowledge. Cultures are crafted, not idealized or willed into existence.
At the recent APQC conference, where I shared this slide during my AI and knowledge management talk, one speaker invoked Peter Drucker’s adage that “Culture eats strategy for breakfast.” That is true—unless strategy and culture are inseparable. Strategy is the story an organization tells itself about how what it will do to meet its objectives, overcome obstacles and navigate change.
Effective strategies are not directives—they’re enacted stories. When actions align with incentives, job descriptions, and performance indicators, strategy becomes reality. People don’t adopt a strategy; they become characters in it.
Strategy is a short set of timely actions, not an inviolable plan with an expiration date, a wish list, or a set of principles. Those who attempt to convince people to follow a strategy will fail. Strategy is an enacted story built into job descriptions and incentives, performance indicators and product mixes. People follow because they are part of the story. The setting won’t be a fantasy about the future but a co-created reality.
AI is the latest technology to rise to the level that organizations want a strategy for it and to embue their strategy with it. Those who focus on AI’s role in helping them achieve their strategic objectives will ultimately reinvent their organizations to leverage AI effectively. Those who simply attempt to find homes for AI within the business will not optimize for its possibilities. If you can’t answer the question about the role AI or knowledge management plays in your organization’s story, then you’re doing culture change wrong.
So, What is Knowledge Management?
What is knowledge management? It’s the connective tissue between how people learn, decide, act, and adapt. When done well, KM helps align the levers of culture to empower strategy. It helps focus technology on outcomes and imbue knowledge with purpose. It makes the organization smarter by design, not just by chance. As AI accelerates the pace and scale of what’s possible, organizations need to ensure that knowledge doesn’t just move faster—it moves in the right direction, grounded in shared understanding and strategic intent.
For more serious insights on AI, click here. For more serious insights on KM, click here.
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