The arrival of the gig economy has led to an unprecedented explosion of person-to-person task outsourcing: driving, food pickup, and shopping can all be done by someone other than the consumer. Such outsourcing potentially creates new challenges for gig workers: knowing the most efficient route, determining the entrance to the customer's home, or knowing where to find the product they are shopping for. To better understand the extent to which technological innovations can help mitigate these challenges, we conducted field experiments on a grocery shopping platform that uses an AI-enabled guidance system to help shoppers find products on store shelves. We find that, as one would expect, such technology helps by reducing the number of refunds (due to the item being hard-to-find, e.g. located at a pop-up display, etc.) and that less experienced shoppers tend to use this guidance the most. However, counter-intuitively, we also find that the usage of more complex routing algorithms is not free: it takes a longer time to consult AI guidance and picking times increase as a result. Overall, we find that AI improves the effectiveness of gig workers by helping less experienced workers achieve order outcomes that are more comparable to those of more experienced workers, thus increasing both customer satisfaction and revenue per order. However, there are boundary conditions for technology adoption and overuse of technology can even lead to lower productivity. Our main results can be summarized as follows: