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Why Embodied Knowledge Matters and Why AI Doesn't Understand

A machine-learning large language model doesn't have tacit knowledge. It consists of potential knowledge.

KMWorld Guide to KM Trends, Products, and Services
The KMWorld Guide to KM Trends, Products, and Services assists IT and business decision makers as they continue to navigate the major technologies and trends shaping digital transformation today.


QUOTE OF THE WEEK


The trouble with the world is that the stupid are cocksure and the intelligent are full of doubt.

 

- Bertrand Russell


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Knowledge Management Case Studies

UiPath and Talkdesk collaborate to transform customer experience journeys

Model Context Protocol-based agentic integration allows for faster, more accurate access and usage of data and information to reduce errors and elevate productivity

Pangaea Data partners with AstraZeneca to advance precision healthcare

This collaboration aims to transform patient identification and clinical decision-making worldwide

Storyblok and Netlify unite to advance content deployment speeds, reduce costs, and increase security

The partnership will enable brands to instantly deploy content in Storyblok worldwide using Netlify in a move designed to help companies adapt to the impact of AI on marketing

OpenText and Fiserv collaborate on resilient information management solution for financial services

New solutions reduce manual effort, strengthen governance, and improve customer experiences

Knowledge Management Opinions & Analysis

Is Your Agentic AI Built on Sand or Bedrock?

Data and knowledge do not, anymore, exist as separate components. They are rapidly merging into a single architecture. As KM'ers, we can no longer leave data management solely up to the admins. Rather, we need to work closely with them on creating data architectures that are contextually and semantically rich enough to be reliably actionable for use by autonomous and semi-autonomous agents.

Why Embodied Knowledge Matters and Why AI Doesn't Understand

A machine-learning large language model doesn't have tacit knowledge. It consists of potential knowledge.

Forget AI Magic, Embrace the Knowledge Graph

The advances in AI and information management are not our enemies; they are our most powerful allies. When wielded by skilled KM professionals, these technologies work. When deployed without our input, they fail miserably, delivering incorrect, misleading, or plain nonsensical results.

The Productivity Paradox: Why Your AI Investment Won’t Pay Off Without KM

There should be one clear group of winners emerging from the coming disillusionment: knowledge and information managers. The AI reckoning will force a long-overdue epiphany upon executive leadership: The value of technology is not inherent; it is contingent on the quality of the information fuel you feed it.

Knowledge Management White Papers

The Trend-Setting Products in Knowledge Management 2025

2025 KMWorld Guide to KM Trends, Products, and Services

100 Companies that Matter in Knowledge Management 2025

From Clutter to Clarity- Why only 2-5% of your Content Matters for KM

Knowledge Management Research

STATE OF AI 2025: MID-YEAR REPORT - Lack of Trusted Content Emerges as Achilles Heel - Survey

State of Play on LLM and RAG: Preparing Your Knowledge Organization for Generative AI

Sponsored by: Graphwise

Toward Greater Visibility in Today's Knowledge World: 2024 Survey on Information Sharing and Transparency

Sponsored by: ProcedureFlow

eGain - The state of Knowledge Management in 2023: Untapped Potential for Business Value - Survey