Smarter. Faster. Bolder: Real-World AI for Finance Teams

Overview

This is a rebroadcast from AICPA ENGAGE 2026.

Artificial intelligence (AI) is no longer a future concept for finance organizations — it’s here now. Leading teams are already using AI to streamline processes, generate insights faster, and support more informed business decisions. The challenge is knowing where to start and how to implement these technologies responsibly.

In this session, you’ll examine real-world examples of AI applications across finance and controllership functions. Learn how AI can improve reporting, forecasting, process automation, and financial analysis while maintaining strong governance and oversight.

The webcast also explores key data security, access control, and risk management considerations that organizations must address when scaling AI initiatives.

Key features and benefits:

Review practical AI use cases across reporting, forecasting, and finance operations

Learn how AI can improve the speed and quality of financial insights

Assess governance, risk, and security considerations for AI adoption

Explore methods for integrating AI into existing finance workflows
Identify actionable next steps for implementing or expanding AI capabilities while maintaining effective controls

Highlights

· Artificial Intelligence (AI) · Generative AI · Financial reporting and forecasting · Process automation · AI governance and risk management

Prerequisites

None

Designed For

Corporate finance professionals and controllers

Objectives

Identify real-world applications of artificial intelligence being used across corporate finance and controllership functions, including reporting, forecasting, revenue recognition, and process automation.
Recognize how AI-enabled capabilities can enhance the timeliness and quality of financial insights to support more agile and informed decision-making.
Estimate governance, access control, and data security considerations that finance leaders must address when adopting generative AI and advanced analytics.
Identify practical next steps for adopting or scaling AI within existing finance workflows while maintaining effective controls and oversight