Term extraction is the first step in extracting specialised terminology and creating a terminology database. How the extraction is carried out depends largely on the database and the time and personnel resources available. This is because working manually quickly becomes extremely time-consuming when the source files are extensive. And, at the moment, AI is always called upon if manual tasks need to be supported or automated. But what does term extraction look like? Is it enough to formulate a prompt to extract all the specialised terms from a text? We pitted human, machine and AI against each other in several tests with different texts and prompting strategies. Here we present the results and show the advantages and disadvantages of each of the three options.