Proving the Value of Knowledge Management

This point cannot be underscored enough and typifies the evolution of the value of KM from qualitative to quantitative terms. According to Vaidyanathan, this transition signals a shift from classic tagging-based “extraction, or even analytics in one mode, to relationship and context between data and content in all modes and sources. This makes KM even more valuable because it now has the power to answer more complex business questions, in real time, as well as help AI-based systems reason and make decisions.”

The use of digital agents, copilots, and AI assistants exemplifies this shift and the simplification of skills requirements needed to access KM systems. When agents are employed with RAGbased systems that are grounded by KM, anyone can avail themselves of these benefits—regardless of his or her technical aptitude. With this agent-based approach, “I can drive more efficiency,” Schuerman revealed. “I can drive more effectiveness. I can get better answers to people at the time they’re needed. So, what does potentially change is the speed and the skills required to get there.”

Final Thoughts

KM is still an enterprise necessity, particularly in the era of the widespread use of language models. As such, its value is proven every time data is prepared for those models and, for the savvy organization, each time those models base their answers on verifiable enterprise knowledge. As Vaidyanathan noted, the other growing use case for demonstrating KM’s value pertains to access controls, data governance, and regulatory compliance. The metadata tags based on KM taxonomies are invaluable in this respect.

Additionally, as almost all the people interviewed for this piece indicated, it’s actually getting easier to prove KM’s value as it changes from being characterized in qualitative terms to quantifiable ones. As such, the value of KM, and of its traditional representations, will likely continue to endure for some time—even with GenAI. “I think you need both because you need that foundation in terms of knowledge that exists today that’s structured, that’s easily understood when you need to find something,” Phelps summed up. “AI tends to help individuals get to an answer faster, but you still need to apply it in the right context. You still need that conceptual framework to be able to relate it to something.”

That’s just what KM provides.