As Gerald Holton said, “we are now uniquely privileged to sit side by side with the giants on whose shoulders we stand.” Knowledge management is an emerging field of study with widespread interest both inside and outside the academe. In order to get a sense of the direction the field is taking as it evolves, I conducted a thematic analysis of online discussions to identify trends and gaps, and identified several areas where knowledge management professionals can contribute.

Identifying a diverse range of sources

Though I tried to find a diverse range of organizations to draw from, almost everything I found was focused on for-profit corporations. I looked for conversations across the web including Substack newsletters, youtube channels, KM-specific news sites and blogs, discussion forums, consulting practices, and conferences. In the end, I identified 41 potential discussions through a variety of keyword searches using whole-internet search engines like Google as well as platform-specific searches. I then refined that list down to 24 that had specific things to say about knowledge management trends, themes, and processes as opposed to discussing knowledge management as a whole.

Thematic analysis

Once I had my corpus, I evaluated each one for topics, themes, and keywords. Once the coding step was complete, I did a thematic analysis to try to form logical groups of related terms. The results are as follows.

Feedback loops

The topic of continuous learning and refinement of knowledge took many forms in the discussions. Some talked about feedback loops and iterative processes that incorporated outcomes back into the knowledge management process as new knowledge to be captured, both for positive results (best practices for success) and negative (lessons learned from failure). Others described the transformation of existing knowledge as it was applied to new use cases.

Employee churn

Most of the articles did their best to present this aspect of knowledge management in a positive light. Some expressed it with terms like reskill or upskill, using knowledge to make employees more valuable or to retrain them to work in other areas of the organization as needs change. This was usually framed as a passive process, where an employee was given new responsibilities and expected to use the knowledge base to fill gaps in their understanding, rather than using the knowledge base as source material for active training programs. Little attention was paid to tacit knowledge during those discussions. 

The remaining articles discussed in a distressed tone the tragedy of knowledge leaving an organization when employees seek other opportunities or retire. In these cases, optimizing the extraction of knowledge from workers, including converting tacit knowledge to explicit form, was the primary focus. One discussion in this group was more frank, addressing the corporate value proposition of replacing expensive experienced workers with lower paid inexperienced ones, and counting on the organization’s knowledge base to make up the difference.

Knowledge management impact evaluation

This was the area that seemed to have the most diversity of viewpoints in the discussions. Some were focused on identifying key metrics that indicated use of the knowledge management systems and processes, like number of newly created documents or number of accesses broken down by team. Others were focused on the transformative process, tracking how captured information was refined and given new presentations over time, showing the age of data cross referenced with its continued usefulness. Several focused specifically on measuring return on investment for knowledge management programs within organizations, proposing different ways of tracking both the expense of the program and its financial benefits. These last mostly focused on discussing frameworks of evaluation, leaving up to individual organizations to work out the details of how to accomplish them. None of them discussed how to identify areas of the organization’s operations where knowledge management could be better utilized, nor how to identify gaps in the knowledge being processed by such systems.

Tacit vs explicit/knowledge fairs/peer mentoring

For those that acknowledged the existence of tacit knowledge, the focus was mostly on how to convert it to an explicit representation. Those explicit representations were then the basis of sharing knowledge across the organization, for example by having regular “knowledge fairs” where groups within the organization could present recent findings to other groups. Of those that chose to address tacit information in its existing form, there were discussions about peer mentoring programs, apprenticeships, ride alongs, and other ways of passing along or developing tacit knowledge.

Primacy of culture/Program implementation

I’ve grouped these together because of how much they seemed to overlap. Every discussion I encountered about the importance of organizational culture to the success of a knowledge management program was embedded within a discussion of how to successfully initiate and maintain such a program. The most common points raised were related to the importance of leadership, both from the top of the org chart and by “knowledge leaders” throughout the organization, and the importance of weaving knowledge management into the values and practices and fabric of the whole organization. From there, implementation discussions were primarily focused with employee engagement and buy-in, integration into workflows, and impact evaluation as discussed earlier. And of course, many of the discussions were published by the makers of knowledge management tools, who were eager to explain how their technology could address every concern they had raised.

Hierarchical organization

Many of the implementation guides included suggestions around this area. There were several discussions around specific hierarchical structures for different company departments such as human resources and customer service, and there was also discussion about organization-wide knowledge hierarchies, taxonomies, and even templates for different types of knowledge. Most of the suggestions centered around access control and knowledge sharing throughout the organization. Interestingly, I didn’t find any discussion of non-hierarchical approaches; given Dalkir’s discussion of the stages of knowledge management’s evolution as a field, I find it odd that so many of these purported experts would still be clinging so tightly to a concept from the first stage.

Capture best practices

These discussions were sometimes related to automated use of captured knowledge (e.g. as training material for large language models), sometimes about placing knowledge within a hierarchy, sometimes about standardization practices so that knowledge is captured in a consistent form, and sometimes about workflow integration to capture it at specific points in the work process.

Point of use/workflow integration/access control

Knowledge management process steps have to be integrated at every level of an organization, and also at every step of employee workflow. It’s not adequate to simply capture and expose everything. People conducting work and making decisions need to have access to relevant information, and will drown if they have to wade through everything. On the other end of the knowledge pipeline, capturing everything instead of only things likely to be relevant will cause drowning in the analysis and refinement phases. And of course, not everyone should have access to all company knowledge, for example the pricing contract terms for a new client, or the reason for one employee’s medical leave, shouldn’t be available to all employees.

AI

The previous point about access restriction is one of the primary concerns in discussions around AI agents being integrated into knowledge management workflows. Since large language models will incorporate all information to build their models, they can inadvertently reveal sensitive information that should be kept confidential. Another point of use concern is “hallucinations,” an inaccurate term since literally everything an LLM produces is a hallucination, it’s just that some of them happen to be correct. In many cases, LLMs aren’t capable of citing a source for the information they provide to users, and since decision makers often ask AI agents to summarize information they do not have subject area expertise in, they may not be able to recognize incorrect responses, leading to poor decisions based on them. However, these discussions consisted mostly of footnotes in otherwise AI-positive posts. Most of the AI discussion was about the formatting and packaging of captured information to efficiently import it into large language model tools, and the most effective places to leverage those tools in employee workflows.

Everything else

There were several topics identified that weren’t the main focus of an article. These are themes that only a single source discussed, or that didn’t easily fit into an existing group. These included discussions about the benefits of outside consultants as knowledge management coaches, a criticism of the data-information-knowledge-wisdom pyramid, some thoughts on collaborative knowledge capture, the prioritization of certain knowledge in addition to refinement, the challenges of divesting knowledge from the process when it’s been consumed by LLMs, and the capture of semantically meaningful relationships between pieces of knowledge.

What’s missing

These are areas that I expected to find discussions of but was unable to do so. The first is any mention of ethics or professional values, including respectful use of Indigenous knowledges. Second, any discussion of the benefit to the individual knowledge worker beyond a generic mention of “job satisfaction.” Third, commonalities and interactions between the corporate applications of knowledge management and those of non-profits, academics and researchers, and Indigenous groups. Fourth, the environmental impact of knowledge management, processes, and tools (e.g. the increased use of potable water for cooling AI data centers). Fifth, discussion of under what circumstances one should consider not implementing knowledge management within an organization. Sixth, how individuals within an organization can advocate for knowledge management when not in positions of leadership.

A final point, there is a small and isolated community discussing personal knowledge management, ranging from digital gardeners to followers of the Zettelkasten method. While such personal practices are discussed, often in the context of specific tools like Notion or Obsidian, there is an absence of the application of the science of knowledge management at the individual level rather than within an organization. While those two knowledge contexts have significant differences, the lack of overlap and sharing of best practices and so on was surprising to me.

Diversity of perspectives

There’s certainly a lot of diversity in what people are talking about and their views on these topics. However, there was surprisingly little overlap in the discussions I found. Within the 24 sources I reviewed in depth, any given topic or theme was rarely discussed by more than two, and none more than three. The only exception to that was AI, where many of the sources were AI companies and only talked about AI. It seems that most of the people and organizations publishing these documents were doing so from a soapbox instead of a forum, and discussion is likely not the best term to describe them. With everyone focused on their own individual area of interest, there seemed to be very little conversation going on, comparing and contrasting or building on other people’s points of view.

Conversely, there seems to be little diversity in who is doing the talking. It was exceptionally difficult to find contemporary discussions outside of the corporate sector. While plenty is written and published about knowledge management in academic and non-profit applications, it mostly seems to be scholarly in nature, or talking about the knowledge management field as a whole rather than discussing specific topics, themes, or trends. Not surprisingly, Indigenous ways of managing knowledge are almost entirely ignored by corporate, academic, and non-profit sectors, instead occupying their own silo of discussions ostracized from the Western discourse.

Implications

Knowledge management as a field is being discussed on a wide variety of online platforms. There is great variety in the topics being discussed, as we’ve seen. There are also many topics not being discussed, and no shortage of opportunities to contribute to the conversation. Knowledge management professionals have a responsibility to ensure the field evolves in a holistic and ethical way, and addressing the gaps identified would be an excellent place to start. However, the overall discourse seems to be primarily focused on talking, rather than listening. The single largest opportunity for us as knowledge managers is to create constructive dialog, where different people and organizations respond to each other and build on each other’s ideas. This is especially true when bridging the silos between corporate, academic, non-profit, Indigenous, and personal knowledge management sectors.

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