Ethan Sulpizio Estrada

Ethan Sulpizio Estrada

I lead AI programs from the first idea to company-wide adoption.

AI Process Engineer running a company-wide AI program across every department: 70+ projects, the agents and automations behind them, and the training that gets people using them. I’m completing a Master of Science in Artificial Intelligence in Business at Arizona State University’s W. P. Carey School of Business, graduating in December 2026, and hold a BA in Digital Computational Studies and Sociology from Bowdoin College.

What I stand for

Three principles behind every project

Start with the people who own the work

Every project begins with the team’s real problem, a named owner and an executive stakeholder, not with the technology.

Ship small, prove it, then scale

A minimum viable product in front of a test group beats a perfect plan, and adoption is earned one team at a time.

Govern it and make it visible

Governance comes first, every project is documented and reviewed, and everyone can see what AI is doing and what it costs.

My workflow

How I take an AI idea from a conversation to something people use every day

Five steps joined by one thin line: listen, spec, build, pilot, roll out LISTEN SPEC BUILD PILOT ROLL OUT
  1. Listen

    Start with the team’s problem and the people who own it: who uses the work, who signs off, and what good looks like.

  2. Spec

    Define the project as deeply as I can. I write the project spec and the instruction set an AI agent will work from, with milestones toward a minimum viable product.

  3. Build

    Build the agent, skill, automation or app. Depending on the team, I’m the primary builder, a collaborator, or dedicated support.

  4. Pilot

    Put the first working version in front of a small test group, the project owner and an executive sponsor, and refine it from what they find.

  5. Roll out

    Release it to the people it was built for, and train them until it’s part of how they work.

Across every project, I keep watch over the whole set so no two teams build the same thing twice, and overlapping work gets merged.
70+

AI projects overseen

~150

employees supported as their AI resource

40

Claude skills and automations shared company-wide

50+

employees trained hands-on

Recognized by
  • ASU NewsFeatured in “For these ASU business students, AI is a family affair”
  • C10 LabsSelected for the AI Biotech Cohort
  • Bowdoin CollegeAcademic award for applied machine learning research at Neoclease
Selected work

Inside the AI program I run

How I take AI from one team’s idea to company-wide use, plus the machine learning and governance case studies from my master’s program.

See the case studies