Putting the ‘human’ in ‘human-in-the-loop’ at KM & AI Summit 2025

Kim Glover, Director, Communications Change Management, TechnipFMC, will lead two sessions at this year's KM & AI Summit—'Cooking With KM: Knowledge Sharing & Building Skills,'"and "Storytelling for Collaboration & Change"—exploring how "human-in-the-loop" concepts reflect and affirm the broader purpose of AI, technology, and KM itself.

GenAI for Customer Service: Pitfalls and Prescriptions for Success - eGain

Successful customer service automation with GenAI requires a strong foundation of integrated knowledge management. Investing in a modern knowledge hub to power GenAI projects will help you meet aggressive operational cost reduction and CX goals.

Leading Services to Bridge the Gap Between Your Knowledge, Information, Content, and Data—Delivering Knowledge Intelligence - Enterprise Knowledge

Whether you're starting with strategy development or ready to implement AI solutions, our expertise spans from tacit knowledge capture to the design and development of enterprise-level AI, ensuring your organization achieves its KI goals.

Enhancing Organizational Experiences: The Power of Knowledge Management Systems and LLMs - KMS Lighthouse

Looking forward to 2025 and beyond, the synergy between KMS and LLMs will drive significant advancements in organizational experiences. By leveraging the strengths of both technologies, organizations can expect enhanced efficiency, better decision-making, and more innovative solutions to complex problems.

Bridging the Knowledge Gap in Manufacturing: Securing Institutional Expertise for the Future

The manufacturing sector is at a crossroads. While investments in new technologies and infrastructure are essential, they must also be utilized to preserve and share institutional knowledge. By adopting a comprehensive KM strategy that includes centralized data management, digital innovation, and a culture of knowledge sharing, manufacturers can safeguard their expertise and secure long-term success.

Navigating the IT Landscape: Balancing Hybrid Cloud and Cloud Repatriation to Stay in Control of Your Infrastructure

To secure their data, certain industries have strict regulations regarding data storage, requiring data to be kept in specific geographic locations or under stringent security measures. This is yet another reason for organizations nowadays to switch back to on-prem resources.

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.

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.

The Long- and Short-Term Impacts of AI Technologies

A much less-known but arguably more critical tech law is Amara's Law, which states that we tend to overestimate the short-term impact of new technology while underestimating its long-term effects.

The rise and potential fall of the citizen developer

The citizen developer movement was heralded as a revolution. Like most revolutions, things have sometimes gone differently than planned. The logic is sound, empowering those who know the business best to build the tools and systems needed to do their job. Ah, if only things were that simple …

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 flip side of generative AI: Extractive AI

Extractive AI takes a more comprehensive and transparent approach to machine intelligence.

100 Companies that Matter in Knowledge Management 2025

From Clutter to Clarity- Why only 2-5% of your Content Matters for KM

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