How to Maximize ROI with Outcome-Based Scoring

There’s a lot of noise around AI agents these days. But when I talk to executives, it’s clear that most companies are just starting to dip their toes in AI waters. They’re eager to explore the potential but uncertain about how to get from their current state to a fully realized, AI-agent-led future. And there’s a paradox: while leaders are feeling the pressure to cut costs and do more with less, they’re simultaneously asked to drive higher revenue performance. As a result, we see ambitious plans built on assumed productivity gains from AI—but often without a realistic blueprint to capture those gains and no clear plan to fund it.  For those companies that aim to reap real, outsized benefits sooner and more predictably, achieving an AI-agent-driven future won’t happen by chance. It’ll require a targeted approach, grounded in strategic execution, data, and iterative learning. And where near-term revenue gains can fund this investment in AI, those opportunities should be prioritized.