Many organizations are rushing to adopt Artificial Intelligence. Internal copilots are being piloted. Search experiences are being reimagined. Customer support teams are testing AI assistants. Executives are asking when productivity gains will appear. Yet a large number of these initiatives run into the same problem. The AI is ready. The content is not. This is … Read more
For years, many organizations viewed Knowledge Management as a support function. Important, yes, but often underestimated. KM teams were asked to maintain repositories, improve intranets, organize content, support lessons learned programs, and encourage knowledge sharing across the business. That model is changing fast. The rise of Artificial Intelligence is forcing organizations to rethink how knowledge … Read more
Most knowledge managers didn’t get into this field to become AI experts. They got into it because they care about how organizations learn, how expertise flows, and how knowledge gets preserved and used rather than lost. Now, barely a conversation about KM strategy goes by without large language models entering the room, sometimes as a … Read more
Knowledge capture has been the stubborn problem at the center of knowledge management for decades. Organizations invest heavily in frameworks, workshops, and KM platforms, and then watch critical knowledge disappear when a senior engineer retires, a project team disbands, or an expert moves on. The process of getting knowledge out of people’s heads and into … Read more
Global enterprises face a distinctive implementation challenge that defeats standard project management methodologies. When knowledge management systems must span continents, cultures, regulatory regimes, and technological generations simultaneously, the complexity exceeds what sequential, centralized deployment approaches can address. The failure modes are familiar: headquarters-mandated platforms that encounter resistance in regional offices, elegant architectures that collapse under … Read more