Most ERP systems generate dashboards, alerts, and exception reports. However, they stop short of execution. As a result, organizations continue to face a persistent decision-execution gap. Signals exist, yet actions lag behind. Consequently, operational latency compounds across planning, approval, and execution cycles. In this webinar, we take a structured deep dive into how Taco, Inc. addressed this gap using data from Epicor ERP. More importantly, we analyze why traditional ERP workflows fail to close the loop—and what it truly takes to move from insight to action in modern supply chain environments.

Next, we shift focus to architecture and execution. Specifically, we examine how A2go deployed a Databricks-native AI agent layer on top of existing ERP and operational systems. This composable approach avoided disruption while enabling autonomous, yet governed, execution. In addition, we break down how supply chain AI agents operate within a modern enterprise stack. Key concepts include event-driven reads, governed writes, audit-ready data trails, identity propagation, and human-in-the-loop control mechanisms. As a result, you will gain clarity on how AI can integrate seamlessly without replacing your ERP—while still driving measurable operational outcomes.

Finally, we move from theory to execution. We present a realistic deployment roadmap grounded in actual implementations at Taco and JBS. Instead of hype, we provide a pragmatic lens. AI agents do not go live in weeks—but they also do not require multi-year transformations. Therefore, we outline a structured 90–180 day implementation model, including sequencing, governance checkpoints, and risk controls. In addition, we share critical lessons learned—what failed initially, what was recalibrated, and how outcomes improved. Ultimately, this session equips you with a practical, defensible framework to operationalize AI agents and systematically close the ERP decision-execution gap.

Register to save a spot today!