The Chief Outcome Officer
Every organization is investing in AI. Most are getting incremental returns. The difference between incremental and transformational is not the technology. It is the human directing it.
The Chief Outcome Officer is the professional who brings deep enough knowledge across the commercial engine to ask AI the right questions, broad enough connections across functions to see how the answers interact, and enough organizational influence to translate cross-functional insight into coordinated action.
It is not a job title. It is a capability. And it is the single highest-leverage investment any commercial organization can make in the age of AI.
Leverage = AI × Knowledge × Connections
AI is the multiplier. It is powerful, accelerating, and available to everyone. The differentiator is what the human brings to it.
Knowledge is depth across the five pillars of the Growth Excellence Model (GEM): Strategy, Marketing, Sales, Commercial Operations, and People. It is the domain expertise that allows a professional to direct AI with precision and evaluate its output against operational reality.
Connections is fluency across the six GEM foundations: AI & Advanced Analytics, Business Transformation, Communication & Alignment, Data & Systems Architecture, Financial Planning, and Measurement & Continuous Improvement. Connections are the cross-functional capabilities that link the pillars into an integrated system.
When Knowledge is deep but Connections are weak, AI produces strong functional output that breaks down at the seams between functions. When Connections are broad but Knowledge is shallow, AI produces cross-functional analysis that lacks the depth to be actionable. When both are strong, AI produces integrated intelligence that drives commercial outcomes across the full go-to-market engine.
Consider a common scenario: a PE-backed B2B company is shifting from SMB velocity sales to enterprise. The board has set aggressive revenue targets and a timeline. Most organizations approach this as a series of functional projects: marketing builds an enterprise campaign, sales hires enterprise reps, operations reconfigures the CRM, HR designs a new comp plan.
Each project is well-executed within its function. And the transformation still underperforms, because nobody connected the marketing budget allocation to the enterprise pipeline timeline, or traced how the new comp plan would interact with the territory redesign, or identified that the CRM data model couldn't support the enterprise deal structure the sales process required.
The Chief Outcome Officer sees those connections before they become problems. They direct AI across functional boundaries to surface implications that no single function would catch on its own. They don't replace functional leaders. They ensure that functional excellence translates into commercial outcomes by maintaining visibility across the full system.
This is the capability RevEng's Growth Excellence Model was built to develop: not just strong pillars, but the connections between them that determine whether a strategy executes as designed or breaks down in implementation.
The Chief Outcome Officer model applies to every role in the commercial engine. The way it shows up in daily work is what we call the AI-Augmented Operator: a professional at any level who directs AI with cross-functional Knowledge and Connections.
The AI-Augmented Seller
An enterprise seller with cross-functional fluency doesn't just ask AI to build a generic business case. They direct AI to build a prospect-specific financial model in the CFO's language, map the product to the prospect's M&A integration challenges, and proactively address adoption risk with a change management plan. The AI is the same tool available to every seller. The Knowledge and Connections determine the quality of the output.
The GTM Engineer
The GTM Engineer operates across all five GEM pillars simultaneously, orchestrating multiple AI agents across connected data to produce intelligence no single function could generate alone. It is an operational role that creates disproportionate leverage because it combines domain depth with cross-functional breadth and technical capability.
The AI-Augmented RevOps Leader
RevOps is the role most naturally positioned for the Chief Outcome Officer model because it already sits at the intersection of multiple functions. The AI-Augmented RevOps leader connects pipeline data to marketing source quality, customer success outcomes, financial projections, and rep capability readiness in a single integrated analysis, not as four separate reports
AI agents are becoming more capable and more numerous. The bottleneck is no longer the technology. It is the human capability to direct AI across the full commercial system with enough Knowledge to ask precise questions and enough Connections to integrate the answers into actionable recommendations.
Organizations that build this capability at scale don't just perform better on any single initiative. They get better at getting better. Each transformation is faster than the last because the cross-functional foundations are in place. Each AI deployment is more valuable because the data connections already exist. Each strategic shift executes more cleanly because cross-functional coordination is an organizational capability rather than an individual effort.
That compounding advantage is the thesis of the Chief Outcome Officer model: not better tools, but better-equipped humans directing the tools they already have. The go-to-market strategy framework, the brand congruence model, the sales compensation growth model, and the career architecture framework are all expressions of this principle: commercial transformation requires integrated thinking across the full engine, not point solutions applied in isolation.
The Chief Outcome Officer: How Cross-Functional Fluency Creates the Leverage That Makes AI Transformational is the definitive guide to building the Knowledge and Connections that turn AI investment into commercial outcomes.
Across 13 chapters, the book introduces the Leverage Equation, walks through the complete Growth Excellence Model with a running transformation scenario, and provides self-assessment and development frameworks so every reader can identify where to build their own leverage.
Written by Carmen Olmetti, Partner and Founder at RevEng Consulting, drawing on direct M&A practitioner experience and years of commercial transformation work with PE portfolio companies and mid-market B2B organizations.
Build your Leverage
Whether you are leading a transformation, evaluating your commercial engine, or developing the cross-functional fluency that makes AI transformational, RevEng can help.