Question Answering (QA) is the automated task of providing an answer to a question posed in human language. Whether through search engines or speech controlled home assistants it has become a tightly integrated part of many peoples' daily routine at work or home. In recent years, these methods have improved greatly for commonly spoken languages. This can almost wholly be attributed to advances in sequence modeling using deep neural networks, an increase in computing power, and the creation of large data sets suitable for training. In this talk, development of such QA methods are presented for Icelandic. The methods applied are a statistical approach based on term frequency, a current standard practices approach using a neural language model for Icelandic and a modern variant using pre-encoded phrase lookup.