From Risk to Readiness: Anatomy of an AI-Ready Knowledge Asset
The hidden risk in your AI investment isn’t the technology; it’s the content. The core issue is that humans and AI systems process information differently: humans infer context and build on an ever-expanding web of knowledge; AI systems require explicit … Continue reading
Knowledge Cast – Bridging Knowledge, Data, and AI by Zach Wahl, Joe Hilger, and Lulit Tesfaye
In this special episode of Knowledge Cast, Zach, Joe, and Lulit pass the mic to Senzing‘s Paco Nathan, who interviews them about their new book Bridging Knowledge, Data, and AI: Harnessing the Semantic Layer Framework to Drive Intelligence. Paco guides … 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
3 Common Pain Points in Transitioning from Semantic Strategy to Implementation and How to Avoid Them
At EK, we work with many organizations that are looking to connect, standardize, and enrich knowledge assets (both structured data and unstructured content) for their enterprise through the implementation of a Semantic Layer. While traditionally, Semantic Layer implementation was in … Continue reading
Where AI is Failing Organizations Without a Semantic Layer: Lessons From the Trenches (with Case Studies)
It has been over three years since OpenAI, an artificial intelligence research company, introduced ChatGPT in November 2022. While artificial intelligence has existed for decades prior, this release and development of Generative AI (GenAI), large language models (LLMs), and their … Continue reading
The Role of Unified Entitlements in Getting Your Content AI Ready
AI has become the place to find answers to nearly any question. I have used the public LLMs like ChatGPT, Anthropic, and Gemini to create trip itineraries, research topics for a book I am writing, and plan social gatherings. I … Continue reading
How Taxonomies and Ontologies Enable Explainable AI
Taxonomy and ontology models are essential to unlocking the value of knowledge assets. They provide the structure needed to connect fragmented information across an organization, enabling explainable AI. As part of a broader Knowledge Intelligence (KI) strategy, these models help … Continue reading
How to Leverage LLMs for Auto-tagging & Content Enrichment
When working with organizations on key data and knowledge management initiatives, we’ve often noticed that a roadblock is the lack of quality (relevant, meaningful, or up-to-date) existing content an organization has. Stakeholders may be excited to get started with advanced … Continue reading
Defining Governance and Operating Models for AI Readiness of Knowledge Assets
Artificial intelligence (AI) solutions continue to capture both the attention and the budgets of many organizations. As we have previously explained, a critical factor to the success of your organization’s AI initiatives is the readiness of your content, data, and … Continue reading
Semantic Layer Strategy: The Core Components You Need for Successfully Implementing a Semantic Layer
Today’s organizations are flooded with opportunities to apply AI and advanced data experiences, but many struggle with where to focus first. Leaders are asking questions like: “Which AI use cases will bring the most value? How can we connect siloed … Continue reading