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Enterprise Search
Having a comprehensive, highly secure enterprise search capability—one that fills the gap between specialized search systems and Web-focused search tools—can be a key business asset, and is essential to effective knowledge management for corporations and government entities. When enterprise search has a strong emphasis on knowledge management, intellectual property, e-discovery and compliance, it becomes the foundation for comprehensive risk management.

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Features

2026 The KMWorld AI 100: The Impact of AI on KM is Inescapable

While AI holds the promise of radically transforming KM, human oversight takes on intensified responsibilities for ensuring the knowledge provided is accurate, timely, and relevant as well as guarding against violations of privacy and proactively securing sensitive data.Value is the key to adopting any technology, and AI tools are no different. AI-enabled KM provides opportunities for KM to shine and for knowledge managers to prove their value to their organizations.

AI 100 Trailblazer: Access Innovations, Inc. - AI Can’t Find Information That Isn’t Labeled

Access Innovations combines decades of expertise in knowledge organization, taxonomy development, and metadata creation with advanced AI techniques to help organizations prepare their content for the next generation of intelligent applications.

AI 100 Trailblazer: AllegroGraph - Agentic AI Needs Context Graphs Built on Knowledge Graphs

As AI systems evolve from assistants into autonomous collaborators, enterprises will need durable memory, explicit semantics, lineage, governance, and explainability. AllegroGraph and GraphTalker provide the semantic control plane where Knowledge Graphs become Context Graphs for trusted Agentic AI.

AI 100 Trailblazer: Upland RightAnswers - Transforming enterprise knowledge into trusted AI answers

Purpose-built for complex, high-volume environments, RightAnswers empowers teams to resolve issues up to 4x faster with 49% faster search speed, achieve 80% AI-generated search response accuracy, and scale operations without increasing headcount through a proven combination of KCS-aligned workflows and next-generation capabilities including Gen Answers and RightAnswers X. 

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Semantic Layers Bring Answers to Problems KM Is Designed to Solve

With a semantic layer framework, an organization can actually spot where they lack explicit knowledge and information, or where people are asking questions for which explicit answers don't exist.

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.

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

How Semantic AI & Knowledge Graphs Can Turn M365 Environments Into a Smart Knowledge Hub

By eliminating data silos, semantic AI enriches customer data and content and enables greater knowledge discovery across an organization. Due to its diverse capabilities, such as text mining, tagging, semantic search, etc., it can be implemented along the whole data and content lifecycle in order to develop intelligent applications. When integrated with an organization's CMS, semantic AI can help individuals get the information they need sooner.

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Looking to the Past to Co-Create the Future

As more ancient texts become digitized and translated, let's go all-in by using human-augmented AI, combining ancient knowledge artifacts with our modern body of research. And let's not just be confined to one or two disciplines. Infinitely large numbers of breakthrough innovations even more impactful than the examples shared are possible.

The Deterministic Delusion: Why Agentic AI Fails the Rules-Based Reality of KM

The real error of the expert system era was not determinism itself—it was incomplete rules. Today's risk is the opposite: We have agents that are too flexible, running on too little accountability, deployed into environments where variation is not a feature but a liability.

Why Knowledge Management Needs a Quantum Reboot for the Agentic AI Age

By embracing a quantum approach, we can create an organization that is genuinely adaptive and intelligent. Agents, freed from the shackles of classical KM, can roam our knowledge graphs, identifying emergent patterns and unexpected connections that no human ever could. They can see that the support ticket trend and the new feature request in the sales call are actually the same particle, just observed in different contexts.

A Glorious Victory for KM!

That AI has proven itself to be a revolutionary knowledge tool paints a different picture of the world itself. For millennia, we in the West counted as the highest knowledge the bedrock beliefs that ground the certainty of the layers of lesser knowledge that rest upon them. While the success of our culture proves the value of this approach in some critical areas, the rapid advances in knowledge enabled by machine learning based in multidimensional models that are too complex for us to understand remind us of what we've always already known: Our world overwhelms our smidgeon of consciousness.

Knowledge Management Whitepapers

From Fragmented Signal to to Strategic Insight

How Enterprise Information Architecture Solves Businesses’ Biggest Data Challenges

2026 KMWorld Guide to KM Trends, Products, and Services

Information Rich: Unifying Fragmented Data With Agentic Workflows in 2026

Enterprise Search Companies and Suppliers
Enterprise Search Directory