As enterprise AI adoption accelerates, procurement leaders are being asked to support a fundamentally different buying cycle. Traditional fixed-price, time-and-materials, and long evaluation models are struggling to keep pace with AI initiatives that move from concept to deployment in days or weeks, not months. At the same time, emerging cost structures — particularly usage-based infrastructure, model access, and token consumption — are making spend less predictable and harder to govern through conventional controls.

The discussion will explore how procurement, IT, and business teams can work together to shift from input-based purchasing toward outcome-based commercial models. Participants will consider how to define value, manage risk, and create governance mechanisms that enable experimentation without allowing fragmented or unmanaged “shadow AI” adoption. A central question is how procurement can become an enabler of AI scale rather than a bottleneck, while still maintaining accountability for cost, security, compliance, and supplier performance.

The roundtable will also examine the longer-term implications of AI for technology sourcing. As AI capabilities become embedded in existing platforms and custom AI-enabled workflows begin to replace some point solutions, organizations may need to rethink how budgets are allocated across software, services, infrastructure, and usage-based AI consumption. The objective is to surface practical procurement levers, operating models, and commercial structures in an AI-driven technology landscape.