JPMorgan Chase is implementing internal dashboards to monitor and rank engineers based on their adoption of artificial intelligence tools. The initiative, championed by CEO Jamie Dimon, mandates that developers within the bank's 65,000-person Global Technology division demonstrate meaningful improvements in both the volume and quality of code generated using AI assistants like GitHub Copilot and Anthropic's Claude. To verify compliance, the bank has constructed internal tracking systems that display individual usage metrics to thousands of peers, effectively creating a competitive environment where engineers must prove they are utilizing these tools to remain relevant. Recent reports and screenshots reviewed by Business Insider reveal dashboards that categorize employees into groups such as non-users, light users, and heavy users. One system identified approximately 24,000 active AI users out of nearly 70,000 provisioned accounts as of late March. A separate dashboard tracks daily engagement with specific coding tools, applying a formula that assigns higher scores for proactive actions, such as initiating a prompt, and lower scores for passive acceptance of AI-generated code. These daily interactions are aggregated into quarterly scores that compare each engineer against the median usage rate within their line of business. The transparency of these metrics has sparked anxiety among the workforce. Engineers have described situations where colleagues were flagged as underperformers for low AI usage, with one manager explicitly warning an employee that they appeared as a non-user and needed to begin using the tools immediately. Some staff members report feeling pressured to maintain high engagement levels to avoid being perceived as inefficient, with one developer noting that the tools have seemingly increased rather than decreased workload expectations. Concerns have also been raised regarding the bank's history of monitoring employee behavior, including office attendance and communication app usage, particularly in an environment where layoffs are anticipated. A JPMorgan spokesperson stated that the data collected is not used for individual performance management reviews. Instead, the bank claims the tracking is designed to measure the effectiveness of its AI investments and to provide targeted training and support. The spokesperson emphasized that the full potential of these tools is realized only when people, processes, and technology align. However, industry experts note that such granular tracking of individual employee activity is uncommon in the financial sector. Sameer Gupta of EY observed that while companies often track AI adoption at a team level to identify roadblocks, monitoring individuals directly can make employees uncomfortable, similar to tracking total hours spent on video conferencing. This push by JPMorgan reflects a broader trend across the technology and finance sectors, where companies like Meta and Google are also setting aggressive goals for AI-assisted code and allowing managers to mandate the use of AI agents. As firms strive to justify billions of dollars in technology budgets, the pressure to demonstrate tangible returns from AI is intensifying. For engineers, this shift has created a complex dynamic where the very tools intended to increase efficiency are now being used as metrics for performance evaluation, leading to debates about productivity, privacy, and the evolving nature of professional identity in the age of artificial intelligence.