Meaning ● Data Extractivism, in the context of Small and Medium-sized Businesses (SMBs), denotes the often-unnoticed process by which substantial volumes of operational data are collected and analyzed, predominantly by larger entities or automated systems, potentially creating an imbalance in bargaining power. This data frequently originates from SMB interactions with platforms, SaaS solutions, or integrated automation tools integral to their growth strategies. The core of Data Extractivism within SMB environments lies in understanding that while data aggregation ostensibly facilitates optimized solutions, the resulting asymmetry may hinder an SMB’s strategic autonomy and competitive agility. Understanding the data’s ownership and application is key to mitigating this, especially as SMBs implement diverse automation technologies to improve efficiency. It’s imperative for SMBs to critically evaluate data-sharing agreements and understand how their operational intelligence is utilized to enhance automation and other system implementation. ● The challenge for SMBs is to balance the advantages of data-driven insights with the imperative of protecting their unique competitive advantages. ● Data Extractivism is critical when considering AI implementation within SMB automation, which requires sophisticated business frameworks that address value creation from these data exchanges.