KM and IT Find Collaboration Productive

IT plays a role in providing a port of entry for customer service solutions and for integrating them with the various repositories that form the knowledgebase. After that point, most KM solutions can be configured and managed by subject matter experts. But the infrastructure on which they are built, whether SaaS or on-prem, must provide the capacity and speed required to deliver their potential.

KMWorld 100 Companies That Matter in Knowledge Management 2026

Companies on this list are wonderful examples of how their products expand the power of KM in changing knowledge environments. They stand out in the KM field, and we applaud their accomplishments. As always, the list is meant to generate interest and to spark discussion. Let us know what you think, and alert us to anything we might have missed.

Securing Your Internal Knowledge Amidst Shadow AI

The pervasiveness of advanced ML models, as well as their effectiveness for increasing productivity, has multiplied the difficulty in securing internal knowledge. Organizations cannot afford to forsake the staples of data access governance,which include data discovery, data classification, access control policy authoring and implementation, monitoringand auditing for regulatory compliance, data privacy, and data security.

Impact of AI on KM Strategy: A Two-Way Street

AI's impact on KM strategy is omnipresent and includes recognizing its potential, particularly for enhancing existing knowledgebases and automating existing processes, while acknowledging the critical role of accurate, clean data to which organizations have access. Consider it a two-way street when setting organizational strategies.

You Don’t Need 47 Agents

The most powerful multistep execution isn't a chain of specialized agents. It's a single model with enough context to plan, execute, and recover—informed by everything it's learned from every prior execution.

Agentic AI and the Evolution of Finance: How Smarter Systems Are Powering Usage-Based Models and Enterprise Growth

Agentic AI marks a shift from passively recording business activity to actively driving it. Those who embrace this shift early will do more than automate tasks—they'll build a trusted, intelligent infrastructure that accelerates not only efficiency but also agility, strategy, and scale.

Conversational AI interfaces and human-AI collaboration to transform legal knowledge management in 2026

This next year will see the knowledge management function take a direction that focuses on a more advanced and mature way of leveraging AI.

Leaders predict AI to continue permeating all aspects of KM in 2026

AI continues to be the topic du jour for various aspects of knowledge management, and 2026 looks to be no exception as leaders in the industry look ahead

Humans in Loops, Flows, and Dialogues

I think we are entering—possibly are already in—the era of humans in the dialogue with AI, discovering our values, getting more specific about them, and altering their applications based on the specifics of our world and situation. If the old KM was about building, organizing, sharing, and leveraging knowledge, the new KM might also be about mastering the dialogue: using AI not just to retrieve our answers, but to help us finally articulate the right questions.

A Call to Arms for Information Professionals

The AI world is advancing at a breathtaking pace with staggering sums of money, but it's built on unstable and illusory foundations. Our role is not to stand on the sidelines shouting warnings. It is to quietly, strategically, and indispensably become the people they cannot do without—the ones who ensure the entire system can actually function.

Will AI Ever Play in Peoria? The Enterprise Reality Check

The tech industry has a long history of overpromising and underdelivering, but AI has taken this to new heights. We're bombarded daily with headlines about AI writing novels, diagnosing diseases, and even replacing entire job functions. Yet, when you peel back the layers, you find a landscape littered with half-baked implementations, inflated claims, and solutions that work only in the most controlled environments.

Inefficient at the speed of light

While process mining started years ago as a mainly data-driven exercise, its stated goal is to be knowledge-driven. Given KM's multidisciplinary scope, we can play a major role in achieving that goal. Any process, no matter how simple, has the potential to reach across an entire business ecosystem, including all stakeholders. This seems like a perfect match for collaborative workflow, AI/ML, knowledge graphs, human sensemaking, and many of the other arrows in our KM quiver.

2026 KMWorld Guide to KM Trends, Products, and Services

Information Rich: Unifying Fragmented Data With Agentic Workflows in 2026

The CIO Strategic Playbook for AI in 2026

100 Companies that Matter in Knowledge Management 2026