Content related to Leveraging KM as the Foundation for Artificial Intelligence
How to Make Tacit Knowledge Accessible for the Enterprise
Much of what an organization’s employees know isn’t written down. Tacit knowledge refers to exactly that: “highly internalized knowledge that is difficult to articulate, record, and disseminate.” It manifests as a deep, institutional understanding of the daily operations, unwritten processes, … Continue reading
Knowledge Cast – Melanie Adams of MSD
Enterprise Knowledge CEO Zach Wahl speaks with Melanie Adams, Global Talent Development & Training Operations Lead, Digital Manufacturing Operations, at MSD. With a deep background in science, leading analytical testing teams, and ensuring quality in regulated pharma environments, Melanie blends … Continue reading
What is the Difference Between a Semantic Layer and a Context Layer? When to Use a Knowledge Graph vs. a Context Graph
Before AI became part of everyday conversations, most enterprise knowledge and data projects had a somewhat straightforward goal: to create a “single source of truth.” In theory, this meant that everyone in the company could look at the same search … Continue reading
Leveraging a Semantic Layer for Research Curation and Conversational Experiences
The Challenge A global philanthropic organization focused on health programs struggled to fully leverage knowledge from semi-structured and unstructured documents. Specifically, within a health-related funding program, researchers lacked access to key qualitative data from end-user surveys and transcripts. Consequently, they … Continue reading
Knowledge Cast – TJ Hsu of Amgen
Enterprise Knowledge CEO Zach Wahl speaks with TJ Hsu, Director of R&D Knowledge Management at Amgen. With over a decade of experience in artificial intelligence and knowledge services, TJ currently leads a team dedicated to enhancing Amgen’s research, development, and … Continue reading
Understanding the New Knowledge, Data, and AI Ecosystem: Trends in Enterprise AI Architecture
The way we consume, create, and engineer information has changed dramatically, with the last several years demonstrating a marked transformation due to Artificial Intelligence (AI). According to a recent report, Generative AI adoption has reached a tipping point, with nearly … Continue reading
Optimizing Historical Knowledge Retrieval: Extracting Knowledge by Making Connections
The Challenge From POC to Production A Federally Funded Research and Development Center (FFRDC) faced significant challenges with low-quality or incomplete metadata for managing and cataloging scientific reports, hindering researchers’ ability to parse repositories and efficiently discover relevant content. As … Continue reading
What Are Explainable AI Knowledge Portals and Why Do You Need Them?
Knowledge Portals first came into prominence in the early 2000s. These initial portals were a collection of static links to information on everything from HR systems to company policies and communications. It was a single location to access the systems … Continue reading
Top Knowledge Management Trends – 2026
Since 2019, I’ve been authoring an annual KM Trends article. This article tends to be one of the most important and challenging that Enterprise Knowledge produces each year, and rightly should be listed as a coauthorship with many of my … Continue reading
The Role of Product Taxonomies in the Age of AI
Product Taxonomies are Your Intellectual Property; Why they Deserve More than AI Slop “Good design is invisible,” a principle that applies as much to digital taxonomy design as it does to the design of physical objects and spaces. At their … Continue reading