AI-enabled Technology and Gig Workforce: The Role of Experience, Skill Level, and Task Complexity

Abstract

While there is widespread excitement about AI-enabled technologies and how they will change the nature of white-collar work, it is less obvious how these innovations can change blue-collar work, which tends to be largely manual, poorly digitized, and relatively low-paid. In this paper, we examine the influence of AI-enabled technology (specifically, the machine-learning algorithm that enables efficient product location and pickup) on the gig workforce by analyzing its effects on worker performance and work patterns. We focus on understanding how various factors -such as worker experience, skill level, task complexity, and workload - impact human-AI collaboration in this context. Using data from a large-scale randomized field experiment on the Instacart platform, we assess how AI tools designed to optimize item-picking processes affect service quality and efficiency as well as the work patterns of the gig workforce.

Our findings reveal that AI technology provides significant performance enhancements by improving work efficiency and quality by 3.83% and 3.29%, respectively, particularly among more experienced workers. In fact, AI technology does not diminish the value of experience but rather complements it in our context. Conversely, we also find that AI can substitute for workers' skill levels, especially in helping lower-skilled workers bridge the gap with their more skilled colleagues. However, lower-skilled workers need experience to benefit from technology fully. Moreover, the extent to which AI complements experience is influenced by task complexity, with AI playing a more significant role in complex tasks and when workers experience a high workload. Our comprehensive analysis also indicates that AI technology leads to a 3.16% increase in the volume of work on the platform. In addition, it improves the flexibility of workers, allowing them to handle tasks across multiple stores. To this end, the AI leads to a 38.5% relative increase in the likelihood of shoppers working across multiple stores. Notably, the study underscores that human experience remains vital in shaping the work patterns of the gig workforce when influenced by AI technology. These insights emphasize the need for companies to balance technological and human factors, such as skills and experience, to optimize AI's benefits for blue-collar workers, ensuring that new tools complement rather than replace valuable human experience.

Keywords: AI, online retail, field experiment, technology, gig workers, stockouts, wayfinding, experience, skill level, task complexity