WEX CDO Advocates Redesigning Work Around AI

WEX Chief Digital Officer Karen Stroup advocated redesigning work around agentic AI, emphasizing its ability to reason, make decisions, and take action. The approach aims to reshape workflows in payments and logistics, with potential efficiency gains in fuel cards and benefits administration.

What happened Reporting by PYMNTS and a WEX blog post covered comments from Karen Stroup, chief digital officer at WEX , about how businesses should apply agentic AI . Per the WEX blog post, Stroup describes agentic AI as having two core capabilities: the ability to reason and make decisions, and the ability to take action. The WEX blog includes Stroup saying, "There are two key things to agentic AI solutions. The first is the ability to reason and make decisions... The second is it can take action." PYMNTS frames the interview by noting that "AI produces greater returns when it reshapes workflows instead of adding isolated features" and cites concrete payments use cases including fuel cards , benefits administration, and service design. Editorial analysis - technical context Industry-pattern observations: Agentic systems combine decision making and action execution, which increases the engineering scope from model training to end-to-end orchestration. For practitioners, that typically means integrating models with workflow engines, business logic, and monitoring to ensure actions remain auditable and reversible. Common technical demands include robust state management, fine-grained permissions, and high-confidence validation steps before automated actions execute in production. Context and significance Reporting by PYMNTS and the WEX blog places this discussion in payments and logistics, sectors where routine decision-action loops are common and where incremental automation can yield clear efficiency gains. The emphasis on measuring customer outcomes rather than model-centric metrics echoes broader shifts in ML engineering toward outcome-driven KPIs such as error reduction, cost per transaction, and end-to-end latency. What to watch Industry observers will monitor three indicators: adoption of agentic AI connectors in payment platforms, emergence of audit and rollback tooling for actioning agents, and shifts in SLAs tied to automated decision outcomes. Reporting does not include company roadmap details or announced product launches from WEX beyond the quoted commentary. Direct quotes "For me, the key is that agentic AI solutions are not about taking the human out of the loop - it's about enabling them," Stroup is quoted in the WEX blog. PYMNTS describes the broader thesis as AI delivering greater returns when it prompts workflow redesign rather than feature additions. Bottom line Editorial analysis: For practitioners building production ML systems, the move from advisory models to agentic workflows raises integration, observability, and safety engineering priorities. Organizations adopting such patterns will likely need clearer action gating and outcome-based measurements to balance automation gains with operational risk. Scoring Rationale The piece highlights a practical shift toward agentic AI in payments, which is notable for practitioners integrating models into workflows; it is not a frontier model release, so importance is moderate. Practice with real Payments data 90 SQL & Python problems · 15 industry datasets 250 free problems · No credit card See all Payments problems /problems/datasets/payments