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.
Our customers often face complex content problems that hinder their efficiency, scalability, and customer satisfaction. These challenges cost the enterprise money, time, and risk.
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?”
The main gist of the article is large AI companies including OpenAI, Google, and Meta are running out of training content for their AI engines. Before we talk about what they did next, let’s think about the implications of this.
In pharmaceutical and biotech regulatory document development, your content strategy – the business plan for how you create, manage, and deliver content – significantly impacts your ability to innovate, comply with regulations, and ultimately, bring new medicines to market.
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: