Agentic Commerce Is Here: Agent Payments and Real-World AI Workflows
Session Overview
AI agents are moving beyond chat and content generation into economic activity. This session explores how agent payments can become the foundation for agentic commerce β drawing on Stripe's work on agent payments as one practical reference point.
Richard will show how agents can request, approve, execute, and reconcile transactions while keeping humans in control of the right decisions β then connect that same pattern to broader workflows: booking travel, following up on invoices, preparing finance reports, checking procurement options, and coordinating tasks across multiple business systems.
What you'll take away
- How agentic commerce differs from chatbots, copilots, and traditional automation.
- Where agents can safely act β and where humans should stay in control.
- How enterprises can design workflows that are observable, auditable, and useful in production.
The goal is to give business and technology leaders a practical way to think about agentic commerce: what should be automated, what should be reviewed, and what infrastructure is needed before agents can safely operate in real economic workflows.
Speaker
Richard Lee is the Chief Architect of IntelWave AI, a family office portfolio, where he leads a team of engineers to architect, design, and build agentic systems for organizations of all sizes and domains β both internally and externally. He has presented practical applications of AI agents at Amazon, Tencent, Stripe, Surperteam, Lorong AI, the Association of Chartered Certified Accountants (ACCA), the Institute of Singapore Chartered Accountants (ISCA), Singapore Management University (SMU), Network School, SCAPE, Preface, Legal Benchmarks, and ClawCon.
His background spans software, hardware, medical devices, payments, ecommerce, localization platforms, data infrastructure, and venture lab R&D. He has worked across Shopee, Rakuten Viki, Enterprise Singapore, Photobook Worldwide, and TeleMedC, among others. That career history shapes how he approaches agents: not as isolated demos, but as systems that must work inside real business constraints β approvals, operations, and accountability.