In the rapidly changing landscape of higher education, the debate is on: should teaching and learning tasks be accomplished by humans or machines? It is considered that judging the quality of someone’s work should remain a human task. However, this task may be accomplished with the assistance of machines producing data for critical appraisal by humans. Well before the arrival of ChatGPT, educators were encouraged to use text-matching software (TMS) to provide formative feedback to students to prevent plagiarism. At the time, TMS were exclusively marketed by large corporations in monopoly positions. Now that text-matching applications and plugins are diversifying to detect generative artificial intelligence (GenAI) and becoming more accessible, there is an opportunity for students to use them for self-assessment. This chapter will look at the evolution of TMS, including their recognized strengths and limitations, prior to and after the arrival of ChatGPT. Then, I will discuss the current usage of TMS by undergraduate students, based on a study conducted across over 30 universities in North America and Europe. Finally, I will offer avenues for TMS to serve as self-assessment tools to prevent plagiarism in institutions of higher education.