Noz Urbina, Consultant and Founder, Urbina Consulting, and Founder, OmnichannelX & TruthCollapse.com, considers the missing word from most AI implementation plans—meaning—in his keynote speech at KMWorld Europe and Taxonomy Boot Camp London on Wednesday 15 April. A few years ago, I moderated a KMWorld webinar where Noz spoke and I’m greatly looking forward to his most recent thoughts. According to Noz, AI runs on patterns, while KM runs on shared understanding. The two are not the same. Feed AI all the documents you can lay your hands on and it will still have difficulties discerning differences between open and resolved issues, current and out of date policies, trusted sources and wiki pages no one cares about. So it guesses, sometimes correctly, sometimes not.
In most organisations, meaning is buried in unstructured formats, legacy silos, and inconsistent tagging. Even in traditional databases true data understanding or flexibility is limited by rigid, incomplete structures. Is there a secret sauce to roust AI from its guessing game fixations? I’m guessing Noz will champion the notion that structuring information to reflect how people actually think and work is key. When the "shape" of information matches the way people think and work, everything flows better: engineers resolve issues faster, support teams get clearer insights, and AI systems behave in ways that feel explainable rather than opaque.
Join us to hear his insights into the practice of KM at KMWorld Europe and Taxonomy Boot Camp London next week.