Content related to Data Governance for Retrieval-Augmented Generation (RAG)
Enterprise Semantic Layer for Firm-Wide Risk Management at a Financial Services Firm
One of the top global leaders in automotive manufacturing faced significant challenges in managing and accessing critical knowledge across its diverse teams. The company engaged Enterprise Knowledge (EK) to conduct a Knowledge Management (KM) Strategy and solution implementation project plan after the failure of multiple KM initiatives. The engagement’s long-term goal is to establish a shared Knowledge Management System (KMS) to streamline access to crucial information, better leverage experts’ institutional knowledge and experience, and decrease new employees’ time to proficiency. Continue reading
Steps to Improve AI Outcomes with Context Engineering
When it comes to successfully implementing AI solutions, a common refrain in most implementations is that your results are only as good as your inputs. To avoid this pitfall, we have seen both data and content teams ask “are my … Continue reading
Shifting to an AI-First Operating Model
Enterprise capital investments in artificial intelligence continue to outpace measurable operational returns because technology alone does not generate enterprise value. Organizations are spending heavily on new technology, but enterprise-wide productivity remains flat. Research from the Federal Reserve Bank of St. … Continue reading
Your AI Can Reach Everything and Understand Nothing
Connectivity is solved. Understanding and precision are not. Why retrieval systems need a semantic foundation. I met up with a colleague at a conference recently. She was newer to the world of semantics and mostly excited by what she was … Continue reading
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
KM Strategy for AI Readiness
Enterprise Artificial Intelligence (AI) readiness depends on the maturity of its underlying knowledge management (KM) ecosystem, not algorithmic power. Without structured, semantically enriched data, advanced models fail due to misalignment, data fragmentation, and hallucinations. Executive leaders face immense pressure … Continue reading
Knowledge Cast – Lucy Hall, KM Expert in the Financial Services Industry
Enterprise Knowledge CEO Zach Wahl speaks with Lucy Hall, a knowledge management (KM) expert in the financial services industry. With 25+ years in the space, Lucy is experienced in driving enterprise-scale change and delivering measurable business outcomes in projects spanning … Continue reading
Beyond Static Permissions: Why Agentic AI Needs Intent-Based Access Control
From Static Boundaries to Dynamic Intent AI agents don’t just need permission to access resources. They need constraints on how they use that access. Intent-Based Access Control (IBAC) is an emerging authorization model that enforces the principle of least privilege … Continue reading
The New Role of Knowledge Management and its Professionals
The world of Knowledge Management is changing rapidly. For those that can seize the moment and embrace the change, this presents an incredible opportunity. For those that instead react with fear or resistance, they will quickly find themselves in obsolescence. … Continue reading
Knowledge Cast – Jonathan Gordon-Till, Global Knowledge Management Lead of R&D at Mondelēz International
Enterprise Knowledge CEO Zach Wahl speaks with Jonathan Gordon-Till, Global Knowledge Management Lead of R&D at Mondelēz International. Jonathan has spent almost 4 decades in the KM profession, witnessing acquisitions, demergers, and the emergence of new information technologies through roles … Continue reading