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.

Knowledge Automation: The End of Manual Knowledge Management - eGain

Enterprise AI deployments are only as good as the knowledge that feeds them. Knowledge Managers relying on manual KM processes will find themselves unable to keep pace with the demands of AI-powered customer engagement. Knowledge Automation provides the solution—a continuously optimized, trusted knowledge layer powering both human agents and AI.

AI is only as powerful as the knowledge behind it - Upland RightAnswers

AI must operate within clear guardrails, supported by human oversight and defined governance processes. When knowledge is reviewed, versioned, and owned, AI becomes a trusted accelerator rather than a potential risk. Organizations that embrace human-in-the-loop governance are better positioned to innovate confidently while maintaining control.

Readers' Choice Awards 2025 - Franz: Agentic AI with AllegroGraph’s Neuro-Symbolic Knowledge Graphs

To achieve true autonomy, AI systems must integrate both neural networks (for learning and pattern recognition) and symbolic AI (for structured knowledge and reasoning). This fusion, known as Neuro-Symbolic AI, is essential for bridging the gap between data-driven insights and human-like decision-making.

Readers' Choice Awards 2025 - Stravito: From Insight to Action— How Stravito Is Powering Faster, Smarter Consumer Decisions

By blending AI with human expertise, Stravito is evolving from simplifying searching for knowledge to shaping smarter, consumer-led strategies.

2025 KM Leaders Circle: Enterprise Knowledge, LLC. - Harnessing assorted data, content, and other knowledge assets in an AI-ready format

Enterprise Knowledge helps organizations harness their assorted data, content, and other knowledge assets in an AI-ready format, building the necessary organizational models and mechanisms to support enterprise-level alignment.

2025 KM Leaders Circle: Evalueserve - Transforming Knowledge Management Through AI and Expertise

Our customized solutions fuse human expertise and AI to modernize taxonomies, scale rapid access to organizational knowledge, and re-engineer KM processes to drive measurable value.

The Next Generation of Knowledge Management

One of the emergent applications of RAG is to improve the data curation, metadata descriptions, and even contents ofthe enterprise knowledge housed within vector stores.

LLMs for the Rest of Us

LLMs are rapidly becoming pervasive across a wide range of use cases, both for individuals and SMBs. The underlying technology is complex, but using them is just a matter of writing your first prompt. With some practice and the right model, you can end up with a powerful tool that enhances your productivity in numerous ways.

2025 KM Leaders Circle: Graphifi - Harness the power of knowledge graphs and AI

With Graphifi, you can manage data intelligently, integrate seamlessly, and accelerate AI innovation, all based on standards to enhance interoperability.

2025 KM Leaders Circle: Bridge the Gap Between Siloed Data and AI Value with Graphwise

The Graphwise platform enables powerful semantic search by leveraging knowledge graphs to understand data's meaning and relationships, delivering more precise results.

2025 KM Leaders Circle: KMS Lighthouse - Transforming static data into dynamic, actionable insights

Empowering enterprises to automate knowledge delivery, reduce operational costs, and elevate customer experiences.

2025 KM Leaders Circle: Lucidworks - Empowering Smarter CX Through Agentic AI

By combining the power of agentic and generative AI with a deep understanding of user intent, Lucidworks helps enterprises create more intuitive, efficient, and impactful digital experiences.

2025 KM Leaders Circle: metaphacts - Do what you do—better, with knowledge graphs & AI

metaphacts transforms data into consumable, contextual and actionable knowledge that drives intelligent business decision-making and trustworthy and explainable insights.

Enjoy Better Business Intelligence, Faster - LexisNexis

Nexis+ AI delivers access to quality results, leveraging a global data library that includes genAI-enabled news and corporate data from thousands of globally-recognized sources, including The Associated Press, Dun & Bradstreet, Gannett, and many more.

Transform enterprise data into a strategic, AI-ready asset - EncompaaS

Designed for unstructured content, EncompaaS discovers, classifies, and enriches information across Microsoft 365, legacy ECM systems, and file shares—without migration. It automates governance, applies retention and sensitivity policies, and enriches metadata to improve GenAI outcomes.

Making Search Conversational to Improve Knowledge Access

With vector search engines, users can authenticate the accuracy of language models by referencing the sources responses are based on.