Loading your experience...
Preparing something amazing for you

8.3
@jropenshaw
Enterprise AI Governance Executive | Turning Unsanctioned AI Risk into Managed Value
AI Fluency Score
8.3/10
Assessed 3/27/2026
Velocity
Technology has never been just a career for me. It's been a lifelong pursuit. It started in the late 1980s when it was still possible to build your own PC from parts and genuinely understand every component inside it. That hands-on obsession turned into a consulting practice supporting dozens of small businesses, keeping their networks, desktops, and printers running while helping them navigate whatever came next. When the internet exploded in the early 1990s, I was there connecting users and small businesses to something none of us fully understood yet but knew was going to change everything, and it did! The cloud transition in the 2010s was the next wave, and when my employer at the time shied away from adoption, that was the signal I needed to take a huge leap to another company with the vision to embrace the technology early. That bet paid off, eventually leading to the hospitality industry's first complete migration of its entire datacenter footprint into the cloud. Now AI is the wave, and the pattern is the same: learn it deeply, build with it, and figure out how to govern it before the risk outruns the value. My wife has graciously tolerated decades of late nights studying for certifications and the particular brand of restlessness that comes with chasing emerging technology. We're also avid hikers with a deep passion for national parks, and our family has served for the past 5 years as stewards with the McDowell Sonoran Preserve in Scottsdale. These days I'm supporting my wife's growing passion for teaching mahjong, which has become a wonderful way to build community. My current AI work spans open-source tooling, structured governance protocols, and active pursuit of the IAPP AIGP certification targeting mid-2026. The goal is the same one that's driven every chapter: understand how it actually works, then make it useful for the people who need it.
Generated 3/27/2026
Owned the infrastructure and vendor integration for the hospitality industry's first complete all-in cloud migration: 3,729 servers, 1,000+ applications, and 7,500+ global properties transitioned to AWS. This wasn't a technology project. It was a governance project at scale: vendor accountability, risk management, compliance continuity, and financial discipline applied to the first full cloud transition in the hospitality sector. The same architectural discipline required to govern a migration of this complexity, phased adoption, risk tiering, stakeholder alignment, measurable outcomes, is the discipline I now apply to enterprise AI adoption. Eight consecutive years of zero audit findings across PCI-DSS and SOX. The infrastructure held because the governance held.
Built the FinOps and IT Vendor Management practices at Choice Hotels from the ground up, establishing the financial discipline and vendor accountability frameworks that governed a $34M+ combined portfolio. 92% forecast accuracy sustained across multiple budget cycles. That kind of precision doesn't happen by accident. It reflects governance infrastructure built correctly from the start rather than retrofitted after something breaks. Owned infrastructure and vendor integration across the $675M Radisson acquisition lifecycle, delivering $2.1M in annual run-rate savings. Managed a vendor portfolio spanning cloud, SaaS, and managed services: negotiating contracts, enforcing accountability, and connecting spend to measurable business outcomes. The practice I built: forecast accuracy, vendor governance, spend tied to outcomes, is the foundational model enterprises will need as AI investment scales. Most haven't started building it yet.
Independent research and open-source development focused on applied AI governance, multi-AI orchestration, and the infrastructure enterprises will need to adopt AI responsibly. LENS (Layered Exposure of Nascent Structure) is a metacognitive AI interaction governance protocol I authored and published under Apache 2.0. It defines six named constraints that govern how AI systems communicate, reason, and execute: prioritizing accuracy, substance, and accountability over fluency. It is the behavioral governance layer for every AI interaction I run. AegisRelay is a multi-provider AI ingress and governance platform that connects AI agents across session boundaries, enforces data sovereignty policies, and creates a structured relay between AI providers and enterprise workflows. It is the architectural answer to the question most enterprises haven't asked yet: how do you govern AI systems that don't share memory, context, or accountability? PipelinePilot is an open-source job search infrastructure platform that demonstrates AI orchestration in practice: multi-agent fit analysis, document generation, and pipeline tracking, all governed by the same principles I apply to enterprise AI adoption. Actively pursuing the IAPP AIGP (AI Governance Professional) certification, targeting mid-2026. Passed ITIL 4 Foundation in March 2026