
The era of merely “chatting” with AI is evolving into a more sophisticated partnership where Large Language Models (LLMs) act as highly capable analytical associates. For the financial professional, the challenge has shifted from writing simple prompts to building complex, multi-step workflows that can spot anomalies, perform deep variance analysis, and automate testing protocols. This course moves beyond the basics, showing you how to treat tools like ChatGPT, Claude, and Microsoft Copilot as “agents” that can handle sequential tasks while you maintain the professional skepticism and oversight required to ensure accuracy and compliance. Success in an AI-integrated firm requires more than just technical skill; it requires a robust framework for data security and risk management. We will explore how to protect sensitive client information through a tiered approach to security, ranging from standard privacy settings to “closed-loop” enterprise systems. Participants will learn how to integrate these advanced analytical capabilities into their existing work in Excel and Power BI without disrupting established operations. By the end of this session, you will be able to move up the value chain of analytics, transforming the “hallucination risk” into a structured “AI audit” process that keeps the practitioner firmly in control.
Financial professionals and CPAs seeking to integrate advanced AI workflows into practice.
No, this is an intermediate session. You should already have a foundational understanding of how tools like ChatGPT or Claude operate before you join us.
Yes, we focus heavily on data security. You'll learn to implement a tiered approach that ranges from basic privacy settings to enterprise-level closed-loop systems.
You won't need to learn coding. We focus on integrating these AI capabilities into the tools you already use every day, specifically Excel and Power BI.
We address this directly through a process called the AI audit. You'll learn how to compare outcomes from different tools to validate narratives and spot potential hallucinations.
The course covers high-volume variance analysis, anomaly detection, and identifying hidden fraud indicators. We move beyond simple questions to build sequential workflows for these complex accounting tasks.
I watched many of my colleagues treat AI like a simple search engine before realizing it could actually function as a junior analyst. I wrote this course because the real value isn't in the chat box, but in the systems we build around it. It's for the professional who needs to move past basic questions and start building reliable, multi-step workflows that actually respect the sensitivity of financial data.
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