Chris Carter is a product and design leader in Leander, Texas — VP Technical Product Owner, AI at JPMorgan Chase, where he leads the design function for machine learning in operations. Over 17 years at Fortune 500 companies including Microsoft, The Home Depot, and Audi, he has shipped AI, voice, and design-system work at scale, and he writes about what AI product work actually takes.
$0M+
Acquisitions influenced
$0B+
Platform sales supported
0.0M+
Active users on platforms designed
0%
Usability on voice banking
VP-level design leader
Experience Design Vice President, Consumer & Community Banking, JPMorgan Chase. Previously Lead Product Designer for AI at Microsoft. 17 years leading design at Fortune 500 companies and startups — not a senior IC, an executive who ships.
AI is the current edge, not the whole story
LLM UX, RAG, agentic workflows, conversational AI, voice and IVR systems, NLU — that's the current edge. Underneath it: design systems at enterprise scale, design engineering, UX research, growth and experimentation, service design, and 0-to-1 product.
Quantified impact
$248M+ in acquisitions influenced. $20B+ in platform sales supported. 2.4M+ active users on platforms designed. 92% usability on voice banking. 70% fewer support inquiries through AI. The numbers are in the timeline below.
How he works
Bring him the business problem. He diagnoses what is blocking customers, then ships the fix — one issue in flight at a time. A queue, not a calendar.
The full skill set
More than three buckets.
“AI systems, web, and product” is the surface. Here is everything underneath it — the complete range from 17 years across Fortune 500 companies, startups, and independent practice.
AI systems, web, and product are the surface. Below is the full range — every role, the impact it shipped, and the skills it used. Filter by what you care about.
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Impact
92% usability score on NLU Phase 2 IVR systems
15% reduction in operational costs through IVR optimization
75% reduction in peer review time through LLM/AI adoption
Led design for 7 micro front ends, breaking the EV monolith into componentized architecture
Delivered future prototype to MLIO leaders driving agentic AI adoption