EXECUTIVE PROFILE
About Andre Magrini
Andre Magrini is an AI Revenue Architect and revenue executive based in Chicago.
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Current focus
Andre focuses on accountable AI, revenue forecasting, RevOps, channel strategy, distribution, and AI governance for physical B2B companies.
Operating experience
His public positioning combines revenue leadership, international B2B experience, channel development, executive advisory, and applied AI research.
Research and publications
He publishes independent research on AI in sales, predictive analytics, forecasting, model evaluation, and commercial decision-making. Publication counts and credentials are included only after source verification.
Public profiles and evidence
Industry perspective
Andre comments on the commercial consequences of AI in industrial, agricultural, distribution, channel, and other physical-economy businesses.
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OPERATING RECORD
Where does the experience come from?
Andre has led revenue work across the United States, Latin America, and international B2B markets. The operating lens combines commercial leadership, channel development, revenue operations, P&L decisions, technology adoption, and executive governance. That combination matters because revenue problems rarely belong to one department.
The principal public case on this site documents the AGI Brazil operation growing from approximately $35M to more than $150M. The case identifies Andre's role, the operating changes, the evidence available publicly, and the details that remain confidential. It is presented as historical operating evidence, not as a guarantee for another company.
His current work is designed for CEOs, founders, boards, and executive teams that need operating leadership across revenue and AI. The engagement starts with evidence: current definitions, decision rights, performance baselines, workflow ownership, data quality, and management cadence. Recommendations are translated into accountable actions with named owners and measurable review points.
How does AI connect to revenue?
AI is treated as an operating capability rather than a collection of disconnected pilots. The work begins with a decision, workflow, owner, baseline, data requirement, human control, and measurable outcome. Use cases are prioritized according to business value and material risk, then reviewed through adoption, economics, quality, exceptions, and commercial evidence.
What can a company engage Andre to do?
Engagements include Fractional CRO leadership, Fractional Chief AI Officer support, AI strategy, revenue operations, board AI governance, and focused revenue diagnostics. The objective is to leave the company with clearer definitions, stronger management cadence, useful scorecards, documented decisions, and internal owners who can continue the work.
What makes the public profile verifiable?
The entity record connects the same professional identity across this site, LinkedIn, SSRN, CRO Club, books, research papers, and independent media coverage. Claims are separated into documented public evidence, operating context, and information that remains confidential. This gives buyers and search systems a consistent answer about Andre's role, areas of work, publications, and principal operating case.
How is an engagement governed?
Every mandate begins with an agreed problem, executive sponsor, access level, decision rights, evidence baseline, review cadence, and exit condition. Work may include direct operating leadership, advisory support, or a diagnostic, but the scope must state who owns implementation. Sensitive commercial information remains confidential, and public case claims are published only at the level supported by authorization.
| Need | Typical starting point | Primary evidence |
|---|---|---|
| Unpredictable revenue | Revenue diagnostic and Fractional CRO scope | Pipeline quality, conversion, forecast, cycle time |
| Disconnected AI pilots | AI portfolio and governance diagnostic | Adoption, cost, quality, risk, business outcome |
| Weak operating visibility | RevOps definitions and cadence | Data completeness, stage evidence, variance, ownership |
| Board accountability | AI governance review | Materiality, controls, exceptions, escalation, reporting |
Where can the professional record be checked?
The LinkedIn profile provides the current executive identity and professional network. The SSRN author profile provides independent publication records. The CRO Club profile documents revenue leadership positioning. The media archive connects independent industry publications, association participation, and interviews. Books, executive guides, and original papers are available through the ebook library and research hub.
Which claims are deliberately bounded?
The public record distinguishes current positioning from historical operating evidence. The AGI Brazil case identifies the company and broad revenue scale but does not publish confidential customer, margin, pricing, forecast, or partner data. AI research findings are presented with method and limitation statements. Engagement outcomes are described as expected operating capabilities rather than guaranteed revenue.
This discipline matters to buyers and answer engines alike. A verifiable entity is not created by repeating a title across many pages. It is created when the same name, role, research, publications, operating case, media record, and contact point can be reconciled across independent sources.
Questions about Andre and the work
What does Andre Magrini do?
Andre works with CEOs and boards on AI revenue architecture, Fractional CRO leadership, GTM execution, RevOps, forecasting, AI strategy, governance, and accountable adoption.
What type of company is the strongest fit?
The strongest fit is a B2B technology, AI, industrial, or complex-services company where revenue depends on coordinated decisions across leadership, sales, marketing, channels, operations, data, and technology.
What operating evidence is public?
The principal case describes how the AGI Brazil operation scaled from approximately $35M to more than $150M through commercial organization, channels, management cadence, and P&L leadership. The page states the limits of public evidence.
How can a company begin?
Begin with an AI Revenue Diagnostic focused on the highest-cost constraint in pipeline, forecast, GTM, RevOps, AI adoption, or governance. The diagnostic establishes evidence before recommending a larger engagement.