In this episode of the AI Agent & Copilot Podcast, Tom Smith speaks with Jorgen Bach, Senior Vice President, Commerce, Truvio, live from the AI Agent & Copilot Summit in San Diego. Bach discusses the company’s recent formation, its strategy of unifying commerce, banking, automation, and ERP extensions, and why enterprises are shifting from AI experimentation toward measurable business value. The conversation explores how organizations can close what Truvio calls the “ERP value gap” while operationalizing AI across finance, operations, and commerce workflows.
Key Takeaways
- Closing the ERP Value Gap: Bach explains that while modern ERP platforms provide strong standardized foundations, real-world organizations operate with highly specialized manufacturing, distribution, and financial processes. These unique requirements often fall outside out-of-the-box ERP functionality, creating what Truvio calls the ERP value gap. Rather than adding dozens of disconnected ISV solutions, enterprises are increasingly looking for consolidated platforms that extend ERP systems while simplifying governance, integrations, and vendor management.
- AI Is Moving From Playtime to Production: One of Bach’s strongest themes is maturity in enterprise AI adoption. A year ago, many companies were experimenting with AI tools and encouraging bottom-up innovation. Today, organizations are demanding governance, ROI, and production-grade outcomes. AI is now being embedded into real workflows — automating invoice validation, detecting anomalies, enabling agent-to-agent ordering, and accelerating software delivery cycles. According to Bach, the industry is transitioning from experimentation to operational execution.
- Agentic AI Enables Business-to-Business Automation: Truvio is investing heavily in agent-based architectures where AI agents transact directly with other agents, supported by human oversight loops. Instead of employees manually placing recurring orders or managing repetitive financial processes, intelligent agents can execute transactions autonomously while maintaining control and auditability. This shift signals a broader transformation: AI is evolving from an assistant into an operational participant inside enterprise systems.
