Knowledge Base - Enterprise Knowledge

Why AI Projects Fail Without a Common Language: The Case for Taxonomy Standards

Emma Chow . Eloragh Espie . May 27, 2026 . Blog

As organizations rush to adopt AI solutions and technologies, the necessary structures to support such solutions are often overlooked. Gartner predicts that by 2026, 63% of organizations will not have the right data management practices for AI. This gap shows … Continue reading

How to Scale a Semantic Layer with Interoperable Ontologies

James Egan . Diana Felder . May 19, 2026 . Blog

A Semantic Layer is the framework for connecting data from multiple sources and formats in both a human- and machine-readable way that enables organizations to understand the meaning of their data, extract contextualized information, and discover new insights. A key … Continue reading

A Practical Guide to a Taxonomy Remodel

Bonnie Griffin . May 18, 2026 . Blog

For anyone who has undertaken any form of home remodel or loves to watch television shows featuring them, the general phases of a home renovation are familiar: visualizing the target state of the remodeled home, carrying out structural work, demolition, … Continue reading

Taxonomies vs. Ontologies for Enabling AI-Readiness

Kathleen Gollner . May 11, 2026 . Blog

AI solutions need to be grounded in an organization’s context. It is difficult to reliably distill context from the entirety of an organization’s knowledge assets, including facts, documents, datasets, and other structured records. Without a specific directive on what matters … Continue reading

Three Case Studies that Showcase Why Every Semantic Layer Needs a Strategy

Madeleine Powell . Rachel Carrier . April 22, 2026 . Blog

As the world of artificial intelligence and advanced data technologies continues to accelerate rapidly, so does the importance of knowledge and information management frameworks to support AI at scale. At Enterprise Knowledge (EK), we regularly see organizations struggling to navigate … Continue reading

Semantic Layer Enablement and Change Management, Part 1: Understanding Change & Measuring Impact for the Semantic Layer

Nina Spoelker . Lynn Miller . April 21, 2026 . Blog

The semantic layer is a framework of standards and tools designed to work and remain behind the scenes. It is the conceptual layer that sits between your organization’s knowledge assets, like content and data, and the people who need to … Continue reading

How to Improve Enterprise AI Adoption: AI Observability & Evaluation

Maryam Nozari . April 16, 2026 . Blog

Part 1: Why Agentic AI Demands a New Kind of Visibility The AI Trust Problem No One Is Talking About Your AI product is live. Latency looks fine. Uptime is green. And yet, somewhere in production, your AI is quietly … Continue reading

Taxonomies in the Age of AI: Evolving Your Strategy

Bonnie Griffin . Justin Grossman . April 15, 2026 . Blog

The Topic Taxonomy: An Outdated Artifact? As knowledge workers continue to navigate constantly evolving priorities in developing effective AI solutions that complement organizational priorities, semantics have maintained their value—but not without shifts that deserve our attention. Broadly speaking, one reliable … Continue reading

From Slides to Structured Data: Preparing Slide Decks for AI Systems

Anna D'Angela . April 10, 2026 . Blog

Slide decks are everywhere in most organizations. They are used to share strategies, summarize decisions, communicate complex ideas, and facilitate decisions. They are packed with information, but they’re also inconsistently formatted and can be difficult for machines to properly “read.” … Continue reading

Expert Analysis: What is Enterprise AI-Ready Content?

Elliott Risch . Emily Crockett . April 8, 2026 . Blog

Scaling Your AI Pilot with the Right Contextual Foundations There’s a rush to build AI solutions: recommendation engines, chatbots, analytics dashboards, and virtual agents. But chasing shiny tools, without understanding the full picture can be risky. The organizations that truly … Continue reading