Shelf Blog
Get weekly updates on best practices, trends, and news surrounding knowledge management, AI and customer service innovation.
The volume of retail support inquiries is often unpredictable. Just consider the most common triggers: Black Friday, the post-holiday return season, sudden viral demand for a specific product, and many more. It is precisely at such moments that AI tools most often provide outdated responses...
Customer support is the arena where agentic AI either shines publicly or fails spectacularly. If your AI makes a mistake, the cost of that mistake is higher than anywhere else in the business. That is precisely why agentic AI for customer service is being discussed today as a high-stakes solution....
Customer service is where customers expect to receive a clear answer to any question they ask. Just one incorrect AI response to a customer can turn into a major public scandal. A simple screenshot on social media, a complaint in reviews, an escalation to second-line support, and your reputation...
Almost every corporation today has more knowledge than it can manage. And AI is marketed to these corporations as the solution to this problem, regardless of the current state of that knowledge. Indeed, AI knowledge management sounds like a ready-made answer: just connect AI to your knowledge...
Knowledge management strategy used to be a plan for organizing documents. Now it’s a plan for whether your AI will work at all. The very same elements of the strategy that make knowledge accessible to employees (governance, consolidation, quality) are exactly what AI agents need to provide...
Knowledge management best practices used to be about helping employees find the right document. But times are changing, and now the stakes are much higher: will your AI provide the correct answer or a definitively wrong one? The very same practices that make knowledge useful to people (governance,...
Virtually every organization has a data governance policy. But far fewer companies actually manage that data by the time an AI agent retrieves it. This gap seems insignificant until you run into “broken” AI projects. The model is fine, the pipeline works, but the data feeding it is unmanaged,...
When enterprises entrust AI agents with real-world capabilities and decisions (such as responding to customers or processing claims), an urgent question arises: How can we trust what the agent does? AI governance is the answer. It is a framework of policies, controls, and oversight that ensures AI...
An AI knowledge base does more than just store articles. It’s a system that understands what’s written in those articles. Whereas agents used to have to enter keyword searches, an AI-powered knowledge base now finds the right content on its own, answers questions in natural language, and provides...
The right knowledge base software for customer support does two things at once: it helps support agents respond faster while also powering the self-service tools and AI that customers increasingly use before calling support. But in 2026, more attention is being paid to the second task because that...
Not every knowledge management system serves the same purpose. And that makes perfect sense, since some are designed to store documents, while others are designed to help customers find answers on their own. Lumping them all under the single term “knowledge management system” obscures the...
We’re convinced that absolutely every large company has a massive amount of data, but when it’s actually needed, no one can find it. CRM systems store customer history, ERP systems store financial transactions, document systems store contracts and regulations, and email contains agreements that...