How (and when) to update your KM strategy

Ensuring that KM endeavors support different access points, systems, and user preferences is a prime consideration for updating KM strategies. Vendors may also supply newfound capabilities (which an organization previously hadn't had access to) that warrant updating a KM strategy to avail organizations of new possibilities.

Cloud technology: A synergistic environment for KM and generative AI

Cloud technology may have become a commodity to some extent, but it is not a simple commodity. The technology that allows cloud computing to be dynamic and agile is composed of many interrelated components, which means that when one thing goes wrong, the problem can cascade. Despite the fact that nearly every organization is using the cloud, about one-third report that their cloud implementations have failed completely, and about one-fourth report that their migration has not met the intended schedule.

Personalization to support customer engagement and boost revenue

Over time, consumers have become accustomed to personalized results when they search for products and services. They are demanding that the brands they deal with have a deep understanding of their individual needs.

Using Generative AI for real-world KM solutions

The overarching utility derived from GenAI capabilities relies on organizations' proficiency to reduce redundancy to minimize inaccuracies, monitor outputs, and trace responses to the underlying data sources from which their responses are produced.

Navigating the risks and challenges of AI (quickly): Create an AI governance program

A strong AI governance program is essential to ensuring compliance and reducing risk. An equally important benefit is that by developing the governance program at the same time the AI application is being developed, issues can be identified early, thus avoiding system redesign or rework on the tail end.

What you should know about cross-border data transfer laws

Multinational companies are generally aware of data transfer laws, but smaller ones just embarking on looking beyond country borders may not be.

Microsoft’s Copilot: A force multiplier for KM

Generative AI (GenAI) applications will increasingly transform organizations' IT platforms. Companies of any size that opt to create robust apps on their own, however, are in for a protracted, complex, and expensive experience.There's a better way: Buy into what I call a GenAI ecosystem from a vendor in whose tech you are already invested. These ecosystems are comprised of the sum of services customers mostly need to build and launch robust apps.

KM and AI: Experts look at what lies ahead for 2024

AI and dreams of its potential rocked this past year as companies moved quickly to embed and offer their own version of chat assistants, predictive and generative AI, and more

The third place of knowledge management

The third place I alluded to goes far beyond mechanistic KM or curated knowledge and takes us into the actual world of tacit knowledge. Here, knowledge comes from and often remains as personal experience, impressions, and intuition; it's undocumented and often hidden and elusive.

Pushing the boundaries of knowledge curation

Knowledge democratization occurs in two directions, seemingly engaged in an endless tug of war: acquisition and dissemination.

Should we go back to paper-based KM?

The sheer volume of largely useless data we have accumulated across the years severely limits the ability of AI to work well, and it comes at a heavy environmental and financial cost.

The flip side of generative AI: Extractive AI

Extractive AI takes a more comprehensive and transparent approach to machine intelligence.

2024 KMWorld Guide to KM Trends, Products, and Services

Unlocking the Power of Knowledge Management for Enterprise AI with Anzo and Knowledge Guru

100 Companies that Matter in Knowledge Management 2024

A Blueprint for Transforming Paper-Intensive Processes