Two distinct types of AI users are emerging, creating a significant divide in how organizations leverage AI technology. The first group consists of "power users," often non-technical individuals who fully embrace advanced AI tools like Claude Code and Python. These users, particularly in finance, are unlocking substantial productivity gains by moving away from limiting software like Excel. For instance, a non-technical executive managed to convert a complex 30-sheet Excel financial model into Python using Claude Code, transforming their workflow and enabling more sophisticated analytics. In contrast, the second group primarily interacts with basic AI tools like ChatGPT or Microsoft Copilot, which often fall short of expectations. Microsoft's Copilot, while widely used in enterprises due to its bundling with Office 365, is described as an inadequate imitation of more robust tools, leading to frustration among users. Many enterprises restrict access to these tools, limiting employees' ability to explore more effective AI solutions. This creates a risk, as decision-makers may dismiss AI's potential based on poor experiences with inadequate software. The challenges faced by enterprises extend beyond software limitations. Strict IT policies, legacy systems, and siloed engineering departments hinder innovation. These companies often lack the infrastructure to implement advanced AI solutions safely. Smaller firms, in contrast, can move quickly and adopt modern tools with better APIs, resulting in greater productivity. The article highlights that real advancements come from employees experimenting with AI in their workflows rather than top-down initiatives. Organizations with internal APIs will have a significant advantage, allowing for more integration and meaningful automation. The gap between those harnessing AI effectively and those stuck with outdated tools is widening rapidly.