Title of the Talk:
Beyond Go-Live: Building an AI-Augmented Operating Model for Large-Scale ERP Transformation
Abstract:
Enterprise transformation is often framed around one defining moment: go-live. But for large-scale ERP programs, the real challenge begins after that milestone, when organizations must prove stability, maintain trust in their data, and operate with confidence in a live business environment.
In this keynote, Rahul Juvvadi shares a practical vision for an AI-augmented operating model for ERP transformation. Based on lessons from SAP S/4HANA and broader enterprise modernization programs, the session explores how AI can help organizations improve transformation quality, strengthen validation and assurance, and create a more resilient path from implementation to sustained operations.
The talk argues that AI should not be treated as a peripheral experiment, but as a core capability woven into the way modern transformation programs are executed and managed. Although grounded in ERP and finance transformation, the ideas presented will be applicable to any organization navigating the complexity of large-scale enterprise change.
Profile:
Rahul Juvvadi, FCPA, CGMA, is a Principal Software Engineer at Microsoft and a finance systems architect with 18+ years of experience at the intersection of enterprise finance, SAP S/4HANA transformation, and software engineering. He specializes in building resilient, audit-ready finance platforms, with deep expertise across SAP S/4HANA Finance, Central Finance, Group Reporting, intercompany, financial close orchestration, and Azure-based enterprise architecture. Over the course of his career at Microsoft, Dupont, and other global organizations, Rahul has led large-scale ERP modernization programs, pioneered finance transformation patterns, and designed governance and observability solutions that improve reliability, reduce risk, and accelerate insight. Rahul brings a rare combination of finance depth, engineering rigor, and practical AI thinking to enterprise transformation, with a focus on making mission-critical systems more intelligent, transparent, and trustworthy.
