20+ years leading marketing, sales, and revenue operations — now designing and running the agentic AI infrastructure behind ABM, demand generation, and RevOps for a global Fortune-500 semiconductor company.
Curated from a portfolio of 56 AI use cases — each one a working system, not a slide. Production means live in an enterprise environment today.
Converts named-account inputs into coordinated research and personalized outreach assets. The system behind a ~90% cut in campaign time-to-launch for a full campaign category.
Turns sparse, unmarketable contacts into governed, routable records ready for ABM activation — with data-quality rules and human review built into the pipeline.
Converts anonymous web visitors into named accounts, scored buying groups, and sales-ready signals — closing the gap between traffic and pipeline.
Shared AI context infrastructure so every team member's AI session starts informed. Adoption engineering, not tool rollout — the difference between licenses and lift.
Designs a complete AI adoption architecture for any team — capability map, governance model, sequencing — and scopes the first deliverable to proof-of-concept in week one.
Models demand generation scenarios and their likely outcomes before resources are committed — turning budget debates into structured, testable comparisons.
A governed pathway that closes the gap between a working AI prototype and enterprise deployment: security audit, IT handoff documentation, porting kit, and approval gates.
Detects competitor design-in momentum at target OEMs using hiring and public signals — early warning for account teams months before revenue impact shows up.
An installable context and memory architecture that turns a team's scattered AI usage into one compounding system — every session smarter than the last.
Lead AI enablement across the GTM organization: enterprise-approved AI use case library, end-to-end pilot development, reusable skill and prompt libraries, weekly AI Lab for cross-functional upskilling, and primary AI liaison to IT.
Built an AI-driven lead-gen and cold-email system that generated $500K in 60 days, achieved 70% open rates at scale, and cut list-building costs 50% with in-house enrichment infrastructure.
Increased sales-qualified leads 400–950% through omni-channel campaigns, attribution modeling, and marketing automation and CRM implementations.
One of four executive team members. Co-built seven departments from the ground up, grew marketing-attributed revenue 250%, launched an e-commerce platform managing 500,000 SKUs, and drove a 450% lift in organic traffic.
One-off AI wins don't compound. I build skill libraries, SOPs, and templates that make the second deployment 10x cheaper than the first.
Human-in-the-loop, evaluation gates, and security review are designed in from day one — because enterprise AI that can't pass IT review doesn't ship.
Tools don't change outcomes; teams do. Weekly labs, enablement materials, and upskilling programs turn AI capability into everyday behavior.
Every system ships with a success metric: time-to-launch, pipeline velocity, cost per record, engagement lift. No vanity deployments.
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