From AI Policy to Operational Governance
Many organizations now have an AI policy, and it is important not to stop there! As far fewer organizations can … Read More
AI Beyond the Hype: Five Leadership Lessons from Season 1 of the RHEMINISCING Podcast
“AI is powerful, but power without purpose, governance, and human judgment is not progress.” — Dr. Anthony J. Rhem
This … Read More
Why Assessing AI Algorithms Is No Longer Optional
Artificial intelligence is moving fast, but responsible organizations cannot afford to move carelessly. AI is no longer confined to experimental … Read More
The Importance of an AI Center of Excellence
An Artificial Intelligence Center of Excellence (AI CoE) is critical for organizations seeking to move beyond isolated experimentation and toward … Read More
2025 Year in Review: From AI Tools to Agentic Systems
Looking back in 2025, my blog content on the Knowledge Management Depot, I believe represents a cohesive, forward‑leaning body of … Read More
Leveraging AI-Driven Data and Knowledge for Competitive Advantage in a Digital Economy
It was a pleasure to attend the 20th International Conference on Knowledge Management (ICKM) as part of the combined GFIC-CIKI-ICKM… Read More
In print:
Essential Topics in Artificial Intelligence AI evolved from expert systems to today’s machine learning and generative models; covers ethics, LLMs, AGI, and NLP basics.
Essential Topics in Information Architecture Information Architecture (IA) details important areas of interest in the principles and practice of implementing information architecture.
Knowledge Management in Law Firms is a collection of insights on managing knowledge in a law firm, from Knowledge Management professionals around the globe. KM in Law Firms is produced in association with the International Bar Association.
Knowledge Management Matters brings together the expertise of the world's thought leaders of KM, who share tips, tactics, and techniques.
Knowledge Management in Practice gives detailed information on applying knowledge management (KM) practices, procedures and techniques to solve real world problems.
UML for Developing Knowledge Management Systems provides knowledge engineers the framework in which to identify types of knowledge and where this knowledge exists in an organization.
It also shows ways in which to use a standard recognized notation to capture, or model, knowledge to be used in a knowledge management system (KMS).
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