Since its very first appearance the concept of crowdsourcing has undergone major variations, coming to include highly heterogeneous phenomena such as Google’s data mining, exchanges on sharing economy platforms (e.g. Airbnb or eBay), contents production within creative communities online (e.g. Wikipedia) and much more. If one assumes a very broad perspective, it is eventually possible to extend the category of crowdsourcing to cover whatsoever phenomena involving the participation of the crowd online, as in fact has been done. On the contrary, I will argue that crowdsourcing – and in particular its microwork branch – represents the specific practice of extending outsourcing processes to a large, low-cost, scalable and flexible workforce, in order to generate greater added value for a supply chain. To develop this analysis, I will especially focus on the case of Amazon Mechanical Turk, and on how the operations carried out on this platform are primarily intended to manage the huge flow of information which spans across a supply chain. The practice of subcontracting to the crowd tasks previously carried out by employees or third-party suppliers highlights how crowdsourcing involves a reshaping of the supply chain, further extending it to a large network of individuals. Through crowdsourcing processes, companies are either able to replace or train AI, integrating human computation skills in algorithmic structures through simple, and oftentimes tedious, microtasks. In this context, processes of gamification are capable to put further downward pressure on already small piece-wages, as long as crowdworkers are rather willing to earn an even lower economic compensation, if it’s associated to challenging tasks; thus, to make a task more enjoyable through gamification could be an effective way to further reduce a supply chain’s expenditures in crowdsourcing, pushing forward labor exploitation practices structurally embedded in this phenomenon.