Executive Profile
Matt Phillips
AI strategy and product leader with a decade in data and AI product leadership, most recently leading enterprise AI transformation at a $10B+ consumer services company and building a GenAI consulting practice. Known for taking AI from pilot to production in regulated environments, and for bringing people along with it.
- Director of Intelligent Engineering & AI Strategy
- Artisan Studios
- Franklin, TN
Executive biography
Matt Phillips is an AI strategy and product leader who has spent his career turning emerging technology into measurable business outcomes. He currently leads the GenAI practice at Artisan Studios, a full-service technology consultancy, where he builds repeatable AI delivery frameworks and prototypes agentic solutions hands-on for clients in government, food service, and supply chain.
Before Artisan, Matt spent 14 years at Asurion, the device protection and tech support company serving 300M+ consumers through 50+ carrier partnerships. He grew from product marketing into AI/ML product leadership, scaling real-time speech-to-text into the foundation of Asurion's AI services, championing a secure on-prem AI platform that generated $12M in documented value, and launching the company's first LLM-powered Expert Copilots. As Director of AI Transformation & Strategy, he built the Responsible AI governance framework, scaled an AI Champions network past its adoption target, and presented AI strategy to the Board of Directors.
Matt writes about human-centered AI on Substack and speaks on AI at scale and AI with human oversight. His leadership philosophy is simple: people thrive on purpose, not pressure.
Elevator pitch
I help organizations get real value from AI by pairing strategy with hands-on building and purpose-led change. I've taken AI from prototype to production inside a regulated, 300M-consumer business, built the governance that let it scale, and now prototype agentic solutions myself so the roadmap matches what's actually possible.
Leadership philosophy
Purpose over pressure.
Clear purpose reduces AI anxiety; fear-driven mandates produce shallow adoption.
Outcomes over output.
Every initiative traces to a measured result, not a deck.
Build to learn.
Leaders who prototype make better calls on timelines and risk.
Bring people along.
Embedded champions and open communities scale fluency faster than training programs.
Career milestones
Mar 2026 to Present
Director of Intelligent Engineering & AI Strategy
Nov 2024 to Mar 2026
Director of AI Transformation & Strategy
Asurion
Mar 2023 to Nov 2024
Director of Generative AI Product Strategy
Asurion
Sep 2019 to Mar 2023
Director of AI/ML Product Management
Asurion
Oct 2017 to Sep 2019
Senior Product Manager, Analytics
Asurion
Sep 2012 to Oct 2017
Senior Product & Marketing Manager, Client Solutions
Asurion
Earlier career
Earlier career
Cincinnati Bell
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"
Signature topics
- Purpose over pressure: leading AI adoption without fear
- Constraint-aware agents: governance as a product feature
- From pilot to production: making AI pay off in regulated operations
- The builder-leader: why AI strategists should prototype
Curated thought leadership

The Next Real Differentiator in Agentic AI Isn't Capability. It's Refusal.
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.
- Agentic AI
- Governance
- Trust

From Bench to Building: My AI Delivery Pattern (Part 2)
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.
- AI-Native Delivery
- Claude Code
- Building

From Bench to Building (Part 1)
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.
- Career
- Builders
- Mindset

Purpose Over Pressure: Why Most AI Adoption Fails (And What Actually Works)
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.
- Adoption
- Research
- Leadership