10
Years in data & AI product leadership
About
AI operator with a decade of data and AI product leadership, shipping AI-enabled products and workflows at scale in regulated, high-complexity environments. I take initiatives from problem identification through deployment to measured ROI. Not building decks, building outcomes.
Today I lead the GenAI practice at Artisan Studios, a technology consultancy, where I build repeatable AI delivery frameworks and prototype hands-on with Claude Code, AWS Bedrock, and agentic workflows. Before that, I spent 14 years at Asurion growing from product marketing into leading AI/ML product, generative AI strategy, and enterprise AI transformation for a business serving 300M+ consumers.
"People thrive on purpose, not pressure."
10
Years in data & AI product leadership
$12M
Documented value from a secure on-prem AI platform
133%
Of AI adoption target via an embedded Champions network
600+
Employees in the internal GenAI community I built
My Journey
Mar 2026 to Present
Building and scaling the GenAI practice at a full-service technology consultancy, with client work across Government, Food Service, and Supply Chain. I architect repeatable AI delivery frameworks that compress time-to-pilot for non-technical operators, prototype directly with Claude Code, AWS Bedrock, AgentCore, and agentic workflows, and lead vendor evaluation for client AI initiatives, from scorecards and live-data pressure tests to AI-specific contract terms.
Nov 2024 to Mar 2026
Asurion
Led enterprise AI adoption and change management across a $10B+ subscription business serving 300M+ consumers through 50+ carrier partnerships. Scaled an AI Champions network to 133% of its adoption target, built a Responsible AI governance framework aligning 20+ stakeholders across security, legal, and operations, and shipped AI voice simulation for sales training (23% sales lift for the pilot team) and IVR AI interactions (43% increase in call containment).
Mar 2023 to Nov 2024
Asurion
Launched Asurion's first Expert Copilots, LLM-powered tools for technical support agents, and designed the LLM evaluation framework used to benchmark frontier models on latency, cost, accuracy, and task fit. Presented AI strategy and future-of-support prototypes to the Board of Directors, unlocking investment in GenAI infrastructure.
Sep 2019 to Mar 2023
Asurion
Led AI product managers, ML engineers, and data scientists to scale real-time speech-to-text from prototype to production with a 55% accuracy improvement, securing $2M+ in investment that became the foundation of Asurion's AI services. Championed a secure on-prem AI cluster that generated $12M in documented value over two years, and established Asurion's first Technical PM and ML Engineering career tracks.
Oct 2017 to Sep 2019
Asurion
Rebuilt knowledge base search across 30+ carrier partners, cutting call handling time by 27 seconds and saving $1M+ annually. Launched an internal data education platform with 150+ courses and 200 recurring users, and implemented same-day device delivery reaching 85% of the U.S. within a 50-minute drive.
Sep 2012 to Oct 2017
Asurion
Evangelized and commercialized a new messaging platform that delivered $58M in EBITDA, and drove 1.5M subscriber net adds, 20% app adoption, and a 15% churn reduction through partner marketing across retail, customer care, and digital.
Earlier career
Cincinnati Bell
Product and partner marketing in wireless, managing the prepaid business and helping launch early smartphones with OEM partners, which grew into a career-long focus on turning new technology into customer value.
What I Bring
Turning ambiguous AI mandates into prioritized roadmaps that product, technology, security, legal, and operations leaders sign off on.
Proof Board-level AI strategy presentations at Asurion
Bridging ideation and deployment by building working prototypes myself instead of waiting on engineering capacity.
Proof AI-native delivery pattern from idea to deployed app
Read: From Bench to Building: My AI Delivery PatternBenchmarking frontier models on latency, cost, accuracy, and task fit so investment decisions rest on evidence.
Proof Built the evaluation framework behind Asurion's GenAI investment decisions
Designing principles, risk standards, and guardrails that let risk and compliance teams say yes.
Proof Aligned 20+ stakeholders across security, legal, and operations
Read: The Next Real Differentiator in Agentic AI Isn't Capability. It's Refusal.Separating demos from durable value with scorecards, live-data pressure tests, and AI-specific contract terms.
Proof Vendor evaluations at Asurion and for Artisan clients
Building AI fluency through embedded operators and purpose-led change, not mandates.
Proof 133% of adoption target; 600+ member internal GenAI community
Read: Purpose Over Pressure: Why Most AI Adoption FailsFocus
AI isn't failing because of the technology. It's failing because of how we introduce it to people. Three principles shape how I lead, build, and write.
HUMAN
Mandates and fear narratives produce shallow adoption. People engage deeply when they understand why AI matters to their work and are trusted to grow into it. Fluency is built through repeated use on real problems, not completed training modules.
How I relate to this
At Asurion I scaled an embedded AI Champions network to 133% of target and grew an internal GenAI community from a handful of people to 600+ employees, by bringing people along rather than pushing them.
Read: When it comes to AI transformation, people thrive on purpose, not pressure.TRUSTED
Agents are built for completion, but enterprises need judgment. The tools that win will be the ones risk and compliance teams can approve: agents that understand the constraint layer around a user's intent and know when to stop and ask.
How I relate to this
I built Asurion's Responsible AI governance framework, aligning 20+ stakeholders on principles, risk standards, and deployment guardrails before AI reached production.
Read: The Next Real Differentiator in Agentic AI Isn't Capability. It's Refusal.PRACTICAL
The barrier to building isn't knowledge anymore. It's willingness to stay in the problem. Leaders who prototype make better calls about timelines, risk, and what's actually possible.
How I relate to this
I use a repeatable chain: chat to frame the problem, a work agent to produce the plan, and Claude Code to ship it. It's how I go from idea to deployed software, and how I set realistic expectations with clients.
Read: From Bench to BuildingSpeaking
The New Customer Service Playbook: AI-led with Human Oversight & Governance Systems
Photos by Kevin Mei
Hands On
A Claude Code plugin that gives a delivery team one shared engineering method: 5 skills, 3 review subagents, 5 guardrails, and data schema reference SOPs. Engineers install it with two commands, and updates ship as reviewed, versioned PRs from a single owner.
A ten-page library covering the full AI delivery path, from spec-driven development through pre-deployment evals to production observability, giving engineering teams one shared standard for building AI systems.
A family-and-friends prediction game with group-stage picks, a two-phase knockout bracket, a Golden Boot podium, match simulation, an admin panel, and automatic leaderboard scoring. Went from a walk to a deployed site in about a day.
Build storyFrom Bench to Building, Part 2
Built from a written spec with an AI coding agent, sourcing articles from Substack automatically.
Testimonials
Insights

Start here
Why I started writing: an internal GenAI community that grew to 600+ people, and a belief that AI succeeds when we bring people along with us.

Reading the Amazon and Perplexity court fight as an early AI governance signal: user permission is not the same as the full set of constraints an agent should honor. Enterprise winners will be agents that know when to stop and ask.

The build story behind a World Cup pick'em app, and the repeatable pattern behind it: frame in chat, produce in a work agent, ship in Claude Code.

A career spent adjacent to building, and the moment that changed. The barrier to shipping software is no longer knowledge, it's the willingness to stay in the problem.

What a Microsoft field experiment with Gap Inc. employees suggests: mindset and repeated use beat rigid protocols and access alone. Leaders have to design for learning, not mandate it.

Can anyone keep up?
Credentials
Anthropic
Jul 2026
ID x44ray26it2v
Anthropic
Apr 2026
ID gzsdrd9spq7m
DeepLearning.AI
Aug 2025
Perplexity
2025
Maven (Allie K. Miller)
Aug 2024
ID WgpFMyoW
Udacity
Speaking & Media
Nashville AI Week
"AI at Scale"
GenAI Summit, Santa Clara
"AI Led with Human Oversight"
Microsoft Silicon Valley HQ
Voice of the Customer, Copilot launch
Asurion AI Storylines (LinkedIn and YouTube)
"Turning Data Into Faster, Smarter, More Personal Tech Care"