Assessments that test understanding via reproducing facts with minimal application and reflection are more easily performed by AI. It is important to consider whether testing recall and understanding is important, or whether this can be tested through demonstrating higher level skills, such as application (in order to apply students will have to understand). 

Examine students’ past behaviours. Cohorts and their approaches to learning and assessment will differ, however, if plagiarism has been an issue before it might also be the case now that AI tools are so easily available. 

Look into feedback from past cohorts. Do students report on being overwhelmed with the amount of work they have to do? High assessment load can lead to pressure that might force students to adopt coping strategies to deal with the workload. This means being strategic and undesirable use of AI to produce assignments could be a part of that strategy.  

A lot of assessments happening at the same time might further contribute to students feeling overwhelmed with high workload and therefore force students to use AI strategically in inappropriate ways. 

Guiding academic integrity and quality of assessment is important but considering AI use in terms of its place within the industry is also important when deciding on how to approach AI use. If you predict AI will be an important part of students’ working lives it is important to teach them how to make best use of the tools they will be working with in the future.