AI & Insights Practice Leader · Big 4 Consulting
AI Strategist. Architect. Practitioner.
I operate where boardroom strategy meets production systems — helping enterprises navigate the shift from AI experiments to AI-native operations.
As the AI & Insights Practice Leader at a Big 4 consulting firm, I lead AI strategy, architecture, and delivery across some of the world's most complex organizations — spanning financial services, healthcare, technology, consumer, and the public sector. My work covers the full altitude: from advising C-suites and boards on AI transformation, to designing the architectures that make agentic systems production-real.
Across 20+ years, I've built my career at every layer of the AI and data stack — from hands-on implementation and data engineering, through large-scale cloud and data operations, to enterprise-wide AI transformation strategy. I've led and delivered AI, machine learning, and data programs for Fortune 500 organizations, always at the intersection of what the technology makes possible and what the business actually needs.
Today, I oversee sustainable AI and machine learning initiatives at enterprise scale — deploying intelligent AI agents, GenAI capabilities, and data engineering solutions that enhance decision-making and operational efficiency. My deepest focus areas are AI transformation and agentic AI: how organizations redesign their operations, architectures, and governance for a world where AI systems act with increasing autonomy.
I write and speak because I believe the gap between AI's potential and enterprise reality is the most important problem in technology today.
Selected publications in Deloitte Insights, the Wall Street Journal, and other outlets — on agentic AI, enterprise architecture, data integrity, and the future of AI-driven organizations.
Weekly writing on strategy, architecture, and the real challenges of making AI work at scale.
The industry is predicting that nearly half of agentic AI projects will be cancelled by 2027. Having seen what works and what doesn't across dozens of enterprise deployments, here's what separates the projects that deliver from the ones that don't.
When every team is building their own agents in silos with different frameworks, you don't have an AI strategy — you have technical debt with a chatbot interface.
Everyone wants to talk about models. Nobody wants to talk about the data feeding them. After 20 years in the trenches, here's why data integrity is still the make-or-break factor.
I regularly speak at industry conferences, executive forums, and AI summits on the themes that sit at the intersection of strategy and systems.
How to build an AI strategy that survives contact with organizational reality. Moving beyond pilots to enterprise-wide transformation.
The shift from tools to agents — what it means for enterprise architecture, governance, and the future of work.
Building trust frameworks, safety guardrails, and accountability structures for AI systems that make real decisions.
Why bolting AI onto legacy architectures fails, and how to design systems that are built from the ground up for intelligence.
Translating AI complexity into strategic clarity for directors and executives who need to make consequential decisions about AI.
Interested in having me speak at your event? Get in touch.
These are the questions I get asked most often by executives, boards, and technology leaders. If any of them resonate, I'd enjoy the conversation.
How do you move from AI experiments to enterprise-wide transformation? What does it actually take to redesign operations, governance, and culture for an AI-native future?
How should organizations think about deploying autonomous AI agents? What governance frameworks, architectural patterns, and risk models are needed to scale responsibly?
What does a production-grade AI architecture look like — one that's built for intelligence from the ground up, not bolted onto legacy infrastructure?
Have a question or want to exchange ideas? I'm always happy to connect.
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