KMWorld 100 Companies That Matter in Knowledge Management 2024

We think these companies play a pivotal role in shaping the future and bringing relevancy to how knowledge is harnessed and made useful across diverse sectors. They are committed to driving efficiency and effectiveness through KM to organizations of all types.

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.

Promises and Perils of AI for Enterprise Knowledge Management

This survey reveals both excitement and trepidation around enterprise AI adoption for knowledge management. Long-standing problems around information access, data quality, and speedy acquisition of needed information are the puzzle pieces that AI has the potential to solve.

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

Decoding the data deluge; use ECM to navigate the unstructured content labyrinth

Obtaining contextual knowledge about how users create and interact with unstructured data is an essential business practice to plan for data storms effectively. Enterprises need to understand that it's not enough to know these user activities but also must take remediation action when necessary.

The flip side of generative AI: Extractive AI

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

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 trust problem with GenAI

2023 has been the year of ultra-hyping GenAI, and who is paying for this deluge of marketing? Technology vendors that want us to buy it. Again, it's impressive stuff, but when we shift from selling to buying and ultimately using it, many tough questions need to be asked.

The five ages of data

Perhaps this latest phase in the history of data will bring us to accept inexplicable complexity as a property of the world. We could view this as pure chaos, but thanks to having lived through the past four ages in rapid succession, we might instead recognize that chaos as being rich with endless mysteries we will never uncover completely.

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

eBook: Navigating IM In an Evolving Remote/Hybrid World