AI is changing how organizations execute work, make decisions, and manage business processes. But faster automation does not automatically create better outcomes. In fact, AI can amplify inefficient workflows, weak controls, and poor data if organizations automate before fixing the underlying process. As human, ERP, automation, and AI responsibilities increasingly overlap, leaders need a new approach to business process auditing. They must evaluate operational efficiency and financial effectiveness together.

In this webinar, we explore how to audit end-to-end business processes in AI-enabled environments. We start by mapping how work actually flows across people, systems, decisions, handoffs, transactions, and financial outcomes. Next, we examine operational measures such as cycle time, throughput, manual touches, bottlenecks, exceptions, rework, and process variability. We then connect these issues to financial outcomes such as working capital, margins, cost-to-serve, and cash conversion. This approach helps organizations distinguish productivity improvements from improvements that materially change business economics.

Finally, we examine where AI belongs within business processes and how AI changes process governance. You will learn how to classify activities across standardization, automation, augmentation, prediction, and autonomy. We will also explore data quality, AI decision authority, confidence thresholds, human approvals, transaction permissions, exception handling, and auditability. Most importantly, we follow AI decisions through workflows, ERP transactions, operational outcomes, and financial statements. The goal is to move beyond asking, “Where can we use AI?” and instead determine whether AI can materially improve process economics while maintaining appropriate controls.

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