AI’s Impact on Data Silos and Knowledge Hubs

The impact of AI on both data silos and knowledge hubs is proving to be powerful in solving some age-old problems, including curtailing the effects of siloed information while increasing the value of knowledge hubs. It can only become more impactful going forward.

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.

Europe Needs to Stop Building Regulatory Moats and Start Building Markets

For Europe to cultivate world-leading AI companies, it needs to build the foundational conditions that have made ecosystems such as Silicon Valley so productive. This also means attracting and retaining talent through easier immigration, greater mobility across borders, and simpler equity compensation structures that make joining an early-stage startup genuinely rewarding. Without people willing and able to take risks on new ventures, there is no growth or innovation.

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.

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.

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.

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.

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