The knowledge curation phase, which frequently takes the form of semantic tags, classifications, and other codifications, will remain indispensable to, and likely become automated for, KM strategies. “In 2024, LLMs [large language models] can semantically tag a document at the most granular level in a way that previously was a dream,” Kamien mentioned. According to Nivala, what AI expressions are less accomplished at, and what will remain central to modern KM strategies, is “adding that relationship like, or have this piece of knowledge which, in itself, doesn’t talk about customer or the organization, but rather what it’s related to. We need to be sure that we record that business context.” Kamien added that he thinks KM is “still in the early days of a shift from document-centricity to data-centricity and, ultimately, to meaning-centricity and reasoning-centricity. Data-centricity means you can harness structured and unstructured data and pull out answers to questions in an unstructured document.”
Moving forward
Emergent technologies, strategic elements, temporal drivers, and vendor relationship implications are critical for updating a KM strategy—as is the over all KM landscape as a whole. When to update your KM strategy is dependent on your individual situation. How to update it has more commonalities as technologies, overall organizational goals, and customer expectations evolve and change. What is not in doubt is the fact that, sooner or later, your KM strategy will need to be updated.