Almost daily, I have conversations with content leaders struggling to solve complex challenges in their organizations. They’re trying to help employees find critical information scattered across multiple systems, scale content creation without ballooning costs, measure the business impact of their content investments, and ensure consistency across thousands of content assets.
AI is completely disrupting how organizations need to think about their content, whether it is customer-facing or internal. The data reveals just how profound—and significant–this disruption has become
Our customers often face complex content problems that hinder their efficiency, scalability, and customer satisfaction. These challenges cost the enterprise money, time, and risk.
I was recently playing 20 Questions with my good friend John when it occurred to me that it has a lot in common with taxonomy—and, by extension, a solid content strategy.
Did you know that one of the best things you can do for your customers is to create less content?I know what you’re thinking. “Why is Content Rules, a company that has been creating excellent content for our customers for over 30 years, telling me to create less content?”
Recently, I have been doing a bunch of research on Retrieval Augmented Generation (RAG). RAG uses a combination of generative-based and retrieval-based artificial intelligence to produce results. Essentially, it combines what it finds with what it creates and gives you an answer to a query.
Content automation is the practice of using systems to perform repetitive tasks to create content; such as formatting, data retrieval, and document assembly. Content automation in the pharmaceutical industry is often implemented for the following reasons: