AI is compressing the cadence of strategy itself. Portfolios that once refreshed strategic themes annually now face capability shifts every quarter, and Lean Portfolio Management teams are discovering that last year’s investment thesis may already be stale. This session gives SAFe practitioners a structured approach to building an AI Investment Strategy that survives contact with reality and delivers ROI leaders can defend in the boardroom.

We will start by examining how AI accelerates strategy cycles, shortening the distance between insight, investment, and impact, and why traditional annual planning horizons no longer fit. From there, we will walk through a practical approach to AI Investment Strategy: how to frame AI initiatives as a portfolio of outcomes and govern them with the same rigor as any other Lean Portfolio investment.

A significant part of the session addresses a challenge many portfolios are only beginning to confront: the shift from mostly fixed technology costs to a blend of fixed and variable costs driven by token consumption, compute, and model licensing. We will show how to model these costs so they inform, rather than derail, investment decisions.

Finally, we will tackle measurement directly. Attendees will learn a practical framework for defining measurable ROI for AI investments, and understand how the definition of ROI itself is changing when speed, quality, and capacity gains occur simultaneously. Participants will leave with a repeatable method for building, funding, and measuring an AI Investment Strategy they can defend with data.

For more information and to register for the Summit, visit the SAFe Summit website.  Sign up for Summit updates directly from Luke Hohmann here.