AI Transformation PM
Turns AI opportunities into governed roadmaps, rollout plans, adoption metrics, and executive-ready decisions.

Strategic sales planning leader at AT&T with an MBA, 10+ years across enterprise operations, forecasting, transformation, and a growing portfolio of AI systems that connect governance, adoption, automation, and executive decision support.
years enterprise ops, planning, and execution
AI systems and proof-of-work assets shipped
proof lanes across transformation, automation, product, and strategy
The strongest AI roles are screening for governance, adoption, ROI, and cross-functional execution. This portfolio is built around that exact signal.
Turns AI opportunities into governed roadmaps, rollout plans, adoption metrics, and executive-ready decisions.
Builds automations across n8n, Claude, Notion, Airtable, Gmail, Supabase, Vercel, and modern AI tooling.
Frames AI work through use-case intake, risk tiers, benefits realization, adoption scorecards, and operating cadence.
Adoption, stakeholder alignment, operational readiness
AI-assisted sales planning and operating-rhythm modernization for enterprise teams using Microsoft Copilot, workflow redesign, and executive reporting discipline.
Forecasting, scenario planning, finance narrative
A practical MVP path for improving planning responsiveness, decision quality, and leadership visibility across sales and operating teams.
Claude, n8n, Notion, Airtable, Gmail, operating briefs
A market-intelligence automation engine that turns AI trend signals into concise briefs, content ideas, portfolio actions, and operating priorities.
Next.js, TypeScript, Supabase, Vercel, Claude
A consumer AI product concept built with an AI-assisted software workflow, showing product sense, rapid prototyping, and shipping muscle.
Career Compound Engine researches enterprise AI adoption, role language, governance patterns, tooling shifts, and operator-builder proof, then converts that signal into concise briefs and next actions.
Tracks enterprise AI adoption patterns, governance themes, market shifts, and workflow automation signals.
Translates research into concise executive briefs, content ideas, project priorities, and proof-of-work actions.
Keeps the operating narrative focused on AI transformation, measurable adoption, and business decision support.
The dashboard model connects market signal, adoption metrics, governance checkpoints, workflow automation, and executive reporting into one operating view.
Reusable enterprise AI operating model
Measures behavior change and usage quality
Turns signal into repeatable action
Makes AI progress visible to leadership
Prince combines enterprise operating experience with shipped AI systems, automation workflows, and product builds that show how AI can move from idea to governed execution.
Career Compound Engine: Claude, n8n, Notion, Airtable, Gmail, and weekly AI hiring-market signal automation.
TYS Table: AI-assisted product development using Next.js, TypeScript, Supabase, Claude, and Vercel.
Enterprise AI transformation artifacts: PMO, governance, adoption, forecasting, and executive decision-support systems.
Public portfolio layer: curated proof that connects AI tooling to business outcomes and operating rhythm.