Two distinct groups of AI users are emerging, and their differences are significant. The first group, dubbed "power users," embraces advanced AI technologies like Claude Code and MCPs. These users often come from non-technical backgrounds yet leverage AI for various tasks, particularly in finance, where traditional tools like Excel fall short. The second group consists of casual users who primarily interact with ChatGPT or similar platforms. Surprisingly, many people remain in this less effective camp, primarily due to limitations imposed by corporate policies and outdated software. Microsoft's Copilot is highlighted as a major failure in the enterprise space. While it has a substantial market presence, it offers a poor user experience and lacks the capabilities needed for complex tasks. Microsoft employees themselves are turning to Claude Code for internal projects, despite having access to Copilot, indicating its inadequacy. The restrictive nature of enterprise IT policies compounds the problem, preventing users from utilizing more advanced AI tools. Locked-down environments and a lack of internal APIs hinder productivity, leaving many organizations at risk of underperforming in a rapidly evolving AI landscape. Smaller companies enjoy a competitive edge as they often lack the bureaucratic hurdles found in larger enterprises. These nimble organizations are quick to adopt and effectively use AI, allowing employees to be far more productive. Employees in smaller firms can leverage tools like Claude Code to convert complex Excel models into Python scripts, gaining significant analytical power. In contrast, larger firms struggle with outdated systems and limited capabilities, restricting their ability to innovate. The future of work appears to favor small teams that organically develop AI-assisted workflows rather than relying on top-down strategies. Companies with accessible APIs for internal systems will outpace those without, enhancing their ability to integrate AI effectively. The technology landscape is shifting, with legacy enterprise solutions facing pressure from newer, more adaptable products that offer better API functionality. The speed at which smaller teams can leverage AI tools is reshaping the competitive landscape, allowing them to challenge much larger organizations.