A groundbreaking study explores the potential of Generative AI, specifically GPT-4, to take on the role of sell-side financial analysts. By examining how GPT-4 processes corporate earnings press releases and financial statements to forecast earnings, researchers uncover surprising insights into its strengths, weaknesses, and the overall implications for the future of financial analysis. The study reveals that while GPT-4 possesses impressive language processing capabilities, its earnings forecasts are significantly less accurate than those of human analysts. This disparity stems from GPT-4's distinct approach to processing information. Its textual analysis follows a consistent, human-like pattern, prioritizing easily digestible and informative sentences. However, its quantitative analysis reveals limitations tied to the availability of domain-specific data, resulting in inconsistencies and a frequent misalignment with the metrics favored by human analysts. Interestingly, GPT-4’s performance tends to decline when analyzing information released after its knowledge cut-off date, underscoring the importance of continuous learning and access to up-to-the-minute data in financial forecasting. While AI offers powerful tools for data analysis, this study emphasizes the enduring value of human expertise, particularly in navigating the complexities of the financial world. It suggests that rather than replacing analysts, AI might be most effective as a collaborative tool, augmenting their capabilities and providing a new lens for financial analysis. This research opens up exciting avenues for further exploration, pushing us to consider how we can best integrate AI into the financial landscape to enhance accuracy, efficiency, and understanding.