About Julien

Enterprise AI leader with 25+ years taking customers from executive vision to production deployment by bridging business strategy and hands-on technical delivery across regulated, high-stakes environments.

The Arc

I started at SAP Labs (2001–2007) as an ERP developer on the Finance and Controlling module, building ABAP code that touched millions of transactions daily. That foundation shaped everything: deep understanding of how enterprise systems work, the constraints they operate under, and how hard it is to move data reliably at scale.

I then spent 15 years in consulting (Alta Via, Mindtree, TruQua) advising enterprises on SAP S/4HANA transformations— Disney, Unilever, AbbVie, others—at finance leaders directly: controllers, CFOs, COOs. That's where I learned the other half: business impact, stakeholder alignment, the difference between a technically elegant solution and one that actually ships.

At Google/Alphabet (2019–2023), I owned the ERP transformation program—Oracle to SAP S/4HANA on GCP—delivering to 135k direct and 130k indirect employees across Finance, Assets, AP, AR, and Reporting. Delivered on time through COVID as the company scaled from $780B to $1.8T market cap. That's where I learned enterprise scale: how to think about roadmaps, trade-offs, and program governance when "small mistakes" touch 250k people.

At MSCI (2023–2025), I led the AI adoption for Finance—250 use cases, prioritization framework, make-vs-buy analysis. Built working solutions: a Run Rate Review agent, a Dispute Management workflow. And learned the gap: moving from POC to production, from demos to live business users, requires entirely different thinking about governance, ops, and organizational readiness.

Today, at SMX (cBEYONData), I build applied agentic AI for U.S. federal agencies—mission-critical systems, audited workflows, governance requirements that would break a startup. I lead strategic discovery, design reusable patterns, ship high-impact agents hands-on. That experience is the lens for everything I write and advise on.

The Pattern

Over those decades, I've seen the same pattern repeat: organizations have real problems, they want to solve them, but they're stuck between what the latest technology promises and what their actual environment can support. The vendors say "AI will solve it!" The CIO says "We can't upgrade for 3 years." The CFO says "I need this to work in SOX-controlled processes." Reality is messy.

That gap—between what's possible and what's practical—is where I work. It's why I write about the last-mile problem in agentic AI. It's why I advise enterprises to meet organizations where they are, not where they should be. It's why I built the Central Finance book—a guide for program managers navigating real transformations with real constraints.

What I Do

• Strategy & Advisory: Enterprise AI deployment, governance, build-vs-buy decisions, organization readiness
• Architecture & Hands-On: MCP servers, semantic models, RAG, agentic AI patterns that ship in regulated environments
• Teaching & Mentorship: FSU Law (program management), MIT (agentic AI), Stanford LEAD (leadership)
• Thought Leadership: Articles on the real problems in enterprise AI, finance transformation, and leadership

Credentials & Recognition

• Education: M.S. in Management, SKEMA Business School; Stanford LEAD program; MIT Applied Agentic AI
• Patents: 3+ granted patents (SAP, 2012–2013) on status schema modeling, audit trails, and data integration
• Published: Central Finance and SAP S/4HANA (SAP PRESS, 606 pp); numerous whitepapers and industry research
• Speaking: SAP Sapphire, ASUG, VC BootCamp, Controlling conference, SAPPHIRE NOW; SAP Mentor & Lighthouse Partner
• Languages: English (bilingual), French (native)