Top Five Ways to Harness the Power of AI Co-Pilot

Scott Abel, Content Strategy Evangelist from Heretto, said that the examples in today's talk come from Heretto's customers. He said that everyone is using AI, but typically not in the most effective way, especially for technical writers. 

AI-powered copilots are built in to the tools we use. When they are inside the tool, they are designed (usually) to understand our content rules. They can act directly on our documentation, but are not writers and cannot replace us. They are like an extra set of hands or eyes. 

AI isn't going to take you job, but if you don't know how to use AI tools, the next person who comes along and who does know them is going to.  

Copilots live inside out tools, and the best ones are trained on the work you do. It's context aware; it doesn't just have the ability to spit out a few words. It also works within the structure of the documentation because it feeds on patterns. 

One way an AI copilot can help is to analyze and improve content, such as ensuring style guide rules are followed, analyzing a topic and making changes, finding and removing or replacing terms, polishing text from non-native speakers, slitting long sentences, and changing voice and tone.  It can even rewrite titles based on the content. 

Another way is for restructuring content. If your unstructured content has some semblance of structure, if there is some predictability, AI is really good in coding that. It can also change content structure, and do it quickly. 

A third way is performing table gymnastics. For example, converting tables to lists or lists to tables or adding, moving, or removing rows or columns.  

A fourth way is enriching content with semantics and metadata, such as wrapping content in DITA elements, adding attributes to DITA elements, specifying element properties, and adding metadata like keywords based on the content of topics. 

A fifth way is guiding people who are new to XML, such as building a specific structure in DITA, answering questions about DITA, and providing understanding of concepts. 

Other practical uses include generating content from tickets, finding tone inconsistencies and quality issues, spotting opportunities for reuse across product information sets,  and identify content appropriate for specific experience levels.