KM’s biggest problem:
While the garbage in, garbage out rule will always be a challenge for anyone trying to build a KM solution, the biggest challenge KM faces is ensuring people can find the knowledge they seek. Artificial Intelligence (AI) has the potential for solving this problem.
Auto-categorization of content:
Keywords are not enough. To quickly find things, they must be categorized. Grocery stores are a great example of this: they don’t stock things on shelves in alphabetical order; they group or categorize them for easy access.
In the world of KM, a piece of content must be linked to the terms that people are likely to use when searching for it. The problem is that this is a tiresome process when done manually—it also requires insight into how people will likely search for information.
Artificial intelligence can make this process almost painless. AI can be used to suggest which terms to associate the content with. Over time, AI suggestions can improve as it learns from its human supervisor. It can also learn when it has incorrectly used terms by observing the behaviours of searchers and adapting its suggestions.
Increasing consumption of content:
Unfortunately, many KM applications do not categorize their content at all, or if they do, it’s not done sufficiently or properly. As a result, users often find them to be all but useless. Thus starts the downward spiral of the KM application. People complain, thus discouraging others from using it. Lack of use results in lack of funding. Eventually nobody wants to be associated with the KM application. It then dies of loneliness.
“Eventually nobody wants to be associated with the KM application. It then dies of loneliness.”
AI powered auto-categorization, however, can help improve the user experience—without requiring an army of people to build, maintain and expand its usage. As people get better results from using the system, they’ll share their successes with others. As more people perceive the KM system as having value, it will attract more content and more users—and the KM ecosystem thrives.
An interesting recent article by Donna Fluss got me thinking about how the growing interest in AI could help make KM an exciting term and concept once again. Perhaps instead of asking people to “search the KM application”, we’ll find they get excited about the opportunity to “ask our AI”.
Do you have experience using AI in your organization? Please let us know in the Comments section—we’d love to hear about it!
Creating new knowledge is not simple or intuitive, but for knowledge managers it is worth perfecting because the potential benefits are significant.
KM Methodologies are policies, rules, techniques, procedures that prescribe how knowledge work is to be performed and offer ways to do it successfully.
KM incentive and reward programs encourage compliance with goals, improve performance against metrics, and increase participation in KM initiatives.
KM goals and measurements include targets included in employee performance plans and metrics to track performance against those goals and other operational indicators.