Enterprise leaders know how to buy large transformations. They know to challenge the business case, test the solution, establish governance, negotiate accountability and manage risk.
Agentic AI does not make those disciplines obsolete. But it does change some of the assumptions underneath them. The technology is moving, systems integrators are changing how they deliver the work, and enterprises are still determining how autonomous agents will fit into their own operating models, all while investment decisions are being made.
That creates some uncomfortable new questions. What does a successful test actually prove when agent behavior can vary? Who benefits when an SI uses AI to reduce its delivery effort? And what happens when the agent itself becomes the cheap part of the equation, while the infrastructure required to trust it (identity, controls, monitoring, governance and human oversight) becomes the larger architectural commitment?
If enterprises do not make those choices deliberately, platform providers and integrators will naturally make them inside their own architectures, potentially creating duplicated control environments and dependencies that become difficult and expensive to unwind.
In this webinar, UpperEdge will examine 13 principles for buying agentic transformation and what experienced technology and sourcing leaders may need to recalibrate. We will explore:
- How to evaluate an SI when polished methodologies are becoming easier to produce
- How to preserve leverage across a growing network of providers
- How to plan optionality before options disappear
- Why the most important question may no longer be whether a proposal looks complete, but what consequential decisions remain unsettled underneath it
