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Enterprise Application Integration
Enterprise application integration (EAI) is being used as a knowledge management strategy, tying together critical bits of information gathered from various systems throughout the enterprise. All of the information far-flung across the enterprise and the need to communicate with outside firms make enterprise application integration tools all the more valuable to managing knowledge effectively.

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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: Openstream.ai

The Eva™ platform powers a growing portfolio of Operational AI solutions, from Collaborative Agentic AI systems for high-stakes knowledge work to AI Virtual Agents, AI Voice Agents, and Digital Humans for customer and employee engagement across voice, vision, gesture, and text.

AI 100 Trailblazer: Altuent builds reliable AI outputs starting with better human-centric knowledge foundations

As organisations accelerate the adoption of tools such as Microsoft Copilot and AI agents, a consistent challenge is emerging: AI outputs are only as trustworthy as the knowledge they are built on. In many organisations, content is fragmented, inconsistent, and lacking the structure and context required to generate reliable answers. Altuent addresses this by focusing on the foundations of knowledge.

AI 100 Trailblazer: Enterprise Knowledge collaborates with clients at every stage of an AI program

Thought leadership and the proven methodologies and expertise within are what makes us successful in collaborating with our clients at every stage of an AI program, from initial strategy and business case development to design, piloting, and enterprise AI builds.

ViewPoints

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.

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.

Columns

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.

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.

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.

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.

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 Application Integration Companies and Suppliers
Enterprise Application Integration Directory