KM & AI Summit 2025 keynote to showcase knowledge management and AI as the backbone for customer service success

Ashu Roy, chairman and CEO of eGain, will share how leading clients are accelerating knowledge creation and curation, along with improving search success rates while driving down costs, during his KM & AI Summit keynote, "AI Knowledge for Customer Service Success"

Breaking down the realities of GenAI implementation at KM & AI Summit 2025

During his KM & AI Summit session, "Enterprises With AI Action: Industry Insights," John Chmaj, senior director, KM strategy, Verint, will explore how the new knowledgebase requires us to rethink how we add, access, and present content in the age of GenAI.

Tips and Techniques to Close Knowledge Gaps

Knowledge gaps are a moving target, and companies must institute continuous improvement procedures to keep up. Numerous avenues exist for detecting knowledge gaps, including employee assessments and technology-derived metrics. Remedies include training and, increasingly, deploying AI solutions to seek out new information. Organizations will need to proactively monitor these gaps and use the available tools to close them in order to stay competitive.

KMWorld Conference Wrap-Up and Look Ahead

Evident in all the tracks and conferences was the trend toward recognizing the foundational value of KM to enterprises large and small, nonprofit and for profit. Without seamless access to knowledge—access that stretches across data silos and transcends formats—enterprises cannot please customers and employees as they would like. AI-based technologies contribute to elevating the value of KM, but they are not the only driving force.

Experts predict AI will continue impacting KM in 2025

AI continues to disrupt the knowledge management space and experts in the field predict that it's a trend that still hasn't reached its full potential, yet. In 2025 there's more room for improvement.

Why ubiquitous AI will mean more, not fewer, white-collar jobs

One thing is clear: The widespread adoption of GenAI will not lead to fewer knowledge jobs, but rather, it will pave the way for their growth and evolution.

Integration impasse: Why organizations can’t wait for data integration before deploying AI

The need for comprehensive data management will always be important, and there are many other benefits of digital transformation, but CIOs don't need to delay GenAI projects until the completion of a giant data centralization effort. By adopting a more flexible approach that incorporates GenAI and next-generation BI tools, businesses can navigate the complexities of modern data ecosystems while driving innovation and maintaining a competitive edge in an AI-driven world.

Democratizing software development with no code/low code

By enabling greater productivity and accelerated software development timelines, no code/low code is on the rise.

252 Million Walas

There are 195 countries in the world. How many more entrepreneurial innovation hotspots are out there, waiting to be tapped and awakened? In our high-tech, virtual world, all of the steps Pakistan has taken can be replicated virtually anywhere, regardless of your country's size, GDP, or location. Imagine the possibilities ...

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.

The third place of knowledge management

The third place I alluded to goes far beyond mechanistic KM or curated knowledge and takes us into the actual world of tacit knowledge. Here, knowledge comes from and often remains as personal experience, impressions, and intuition; it's undocumented and often hidden and elusive.

When is good enough enough?

Our goal should be to improve the quality of knowledge assets and their accuracy and relevance in use. Much of this will come from human expertise and effort, increasingly combined with the power of AI.

Content reuse — the key to scaling businesses intelligently and quickly

Building the AI content pipeline — why structured content is the key to automation and personalization

2025 Content Trends

Assessing Business Value and Impact