Most enterprises are lost in AI hype. You need someone who thinks differently.
“Cut the noise. Execute with discipline.”
I help AI Transformation leaders move from endless pilots to production systems that deliver measurable business outcomes — backed by research, not hype.
The Real Problem
Your organization has invested in AI. You have pilots. You have dashboards. What you don’t have is production systems tied to measurable outcomes. The bottleneck isn’t the model — it’s fragmented data, unclear ownership, and work that hasn’t been redesigned around AI. The gap between ambition and execution is organizational — and that’s exactly where I work.
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10%
of organizations have scaled AI agents in any function (McKinsey, 2025)
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84%
haven’t redesigned jobs or workflows around AI (Deloitte, 2026)
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70%
of AI value comes from people & process — not the model (BCG)
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How I Lead AI Transformation
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01
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Strategic AI Roadmapping Multi-year AI roadmaps tied to fiscal constraints, delivery capacity, and board-level business outcomes — not technology wish lists. So your AI investments have a sequence, not just a backlog. |
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02
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Portfolio Prioritization & Capital Allocation Evaluation frameworks that weigh value, risk, scalability, and interdependencies — so capital flows to the highest-return AI bets, not the loudest voices. So your AI budget is a strategic decision, not a political one. |
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03
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Architecture & Data Readiness AI, data modernization, and enterprise systems integrated under defined standards — closing the data governance gaps that stall most deployments. So your data is actually ready when your AI initiative is. |
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04
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Pilot-to-Production Deployment Discipline Clear milestones, governance controls, and accountability structures that move AI from experimentation to operational systems with defined performance targets. So pilots stop being the destination and start being the beginning. |
What This Enables
| ▶ Clear Direction AI and data initiatives sequenced with explicit priorities, dependencies, and executive alignment. |
▶ Stronger ROI Capital allocated with structured visibility into value and risk — not just cost and timeline. |
▶ Measurable Outcomes AI tied to performance targets that boards and CFOs can read — not just pilot metrics. |
How I Think — and What I Bring
Twenty years inside global enterprises — Cisco, Chevron, Pure Storage — teaches you to read past the noise. AI headlines swing between transformation overnight and mass disruption by Tuesday. The data tells a more measured story: capability is spreading faster than enterprises can absorb it, and the organizations pulling ahead are the ones doing the hard organizational work, not just running more pilots.
That grounded, research-backed perspective shapes every engagement. It’s reflected in the NC Tech article on enterprise AI in 2026 — and in a playlist of short, direct takes on execution that cut through the hype without replacing it with another layer of jargon.
Ready to Move from Pilot to Production?
Whether you’re building your AI transformation roadmap, stuck between experimentation and execution, or need a rigorous outside perspective — let’s talk.