Building systems that hold up under pressure.
My approach to AI strategy is simple: disciplined execution, measurable outcomes, and applying the rigor regulated operations demand to a field that's mostly moving too fast to check its own work. The same operating principles that worked in twenty years of insurance operations — applied to AI systems instead of claims and policy workflows.
A long-form account of how operational discipline became a methodology for building AI systems that hold up in production.
The foundation.
Two decades in VP-level insurance operations taught me that success isn't about having the most resources — it's about process discipline, clear accountability, and the ability to adapt without losing control of the outcome. Every claim, every policy decision, every regulatory requirement demands the same thing: a system that works the same way every time, whether anyone is watching or not.
Those lessons became the foundation for everything I do today as an AI strategist.
The technical evolution.
I started building AI systems into business operations in 2018 — long before generative AI put the term "AI strategy" into everyday use. I pursued a Master's in Organizational Development at Southern Methodist University alongside deep technical study — 25+ certifications spanning AI/ML, generative AI, prompt engineering, data science, cloud infrastructure, cybersecurity, project management, and IP law. I became obsessed with one question:
How do you build AI systems that survive contact with how people and processes actually work?
The answer wasn't more technology. It was better implementation, grounded in organizational reality — not vendor demos.
The ZenAgentic mission.
I founded ZenAgentic to solve a problem I saw clearly from inside regulated operations: small and mid-market businesses were being left behind in the AI shift, caught between agencies selling shelfware and consultants selling frameworks nobody could operate.
We're the alternative — AI search optimization and automation built for businesses that need results, not theater. Our disciplined approach means solutions that are robust and built for real operations, not controlled demos.
The next evolution.
After two decades making high-consequence decisions in regulated environments, and years of hands-on AI system building, one pattern became impossible to ignore: the companies that succeed with AI have senior leadership owning the decisions. The ones that fail are buying tools without a strategy — reacting to vendor pitches instead of executing a roadmap.
Most growing companies need a Chief AI Officer but can't justify — or find — a full-time hire at $300K+. So I built the engagement model I wished existed: a Fractional Chief AI Officer who embeds directly into the leadership team, owns the AI roadmap, evaluates every vendor, and ensures every automation dollar drives measurable ROI.
JC Burrows
Fractional Chief AI Officer · Founder, ZenAgentic
How decisions are made.
Speed over perfection
Analysis paralysis kills more projects than bad execution. Rapid iteration, real-world testing, and a bias toward shipping.
Direct communication
No consultant-speak, no sugarcoating. You'll always know where you stand, what's working, and what needs to change.
Results over activity
Success is measured in outcomes, not hours billed. If it doesn't move the needle, it doesn't matter.
Process discipline
The same rigor regulated operations demand, applied to AI decisions — because the cost of getting it wrong is real in both worlds.
Education & Credentials
Areas of Expertise
AI Strategy & Roadmap Design · Vendor & Technology Evaluation · Process Optimization · Digital Transformation · AI ROI & Business Case Development · Organizational Change Management · Cross-Functional AI Integration
Beyond the Bio
When I'm not advising leadership teams on AI strategy, you'll find me reading investigative non-fiction, studying complex systems, and exploring the outdoors.
I believe in building things that hold up, working with people I respect, and leaving every engagement better than I found it. If that resonates, I'd love to connect.
Get In Touch
Have a question, an opportunity, or just want to say hello? I read every message.
Looking for something specific? Start with AI strategy & advisory, read the governance framework, or take the free readiness assessment.
Get in touchCommon questions.
What is your background?
Two decades in VP-level insurance operations, then AI systems building since 2018. MA in Organizational Development from SMU, plus 25+ technical certifications. The operations background matters more than the AI credential — most failed AI projects are process problems wearing a technology costume.
What kind of companies do you work with?
Growing businesses that have started spending on AI without anyone senior owning the decisions. Typically $1M–$30M in revenue.
Why fractional rather than full-time?
Most companies this size don't have enough AI decision volume to fill an executive week, but the decisions they do make are expensive to get wrong. Fractional matches the cost of the seat to the weight of the decisions.
Do you work with companies outside Texas?
Yes — the engagement is fully remote and location-agnostic. The work is decision-making and governance, which travels well regardless of where your team is based.
How do we start working together?
Usually a conversation, then either a strategy intensive or a retainer depending on whether you need one decision or a standing seat.