Financial analysis and reporting are being transformed by AI agents that can gather data, interpret business performance, generate insights, and produce decision-ready reports with far less manual effort. But building reliable agents for finance requires more than connecting a language model to a spreadsheet: you need strong data controls, clear analytical workflows, traceable reasoning, and safeguards against unsupported conclusions. In this practical course, you will learn how to design AI agents for financial analysis and reporting from the ground up. You will map finance workflows into agent tasks, connect agents to structured financial data, perform trend and variance analysis, and create prompts that produce consistent, reviewable outputs. You will also explore how agents can assemble management reports, explain key performance indicators, cite their sources, and surface risks or anomalies without overstating what the data proves. The course is designed for financial analysts, FP&A professionals, accountants, reporting specialists, business managers, and technical practitioners who want to apply AI agents to real finance workflows. Basic familiarity with financial statements, spreadsheets, or business reporting is helpful, but advanced AI or software engineering experience is not required. By the end of the course, you will have a clear framework for building and evaluating a finance-focused AI agent, along with a practical reporting workflow that balances automation, accuracy, transparency, and human review. Start building more efficient and trustworthy financial analysis processes today.