An Enterprise Transformation Leader building AI-native ways of working.
20+ years at the intersection of operations, technology, and transformation.
I lead digital transformation inside global enterprises. My work spans enterprise financial systems, business process transformation, and system and process architecture, redesigning how core operations are structured, automated, and run at scale.
Today I own AI and automation strategy and delivery, moving AI from experimentation into production by architecting intelligent workflows, embedding agentic AI into operational systems and decision-making, and scaling automation across Finance and enterprise functions.
Map the end-to-end process as it actually runs: systems of record, handoffs, exceptions, controls, and where cycle time and manual effort really accumulate. Baseline it with data before proposing a solution.
Score use cases on business value, feasibility, data readiness, and risk. Decide deliberately where AI, agents, traditional automation, data, or process redesign is the right answer, rather than applying AI to every problem.
Re-architect the process first: eliminate steps, standardize inputs, and remove upstream defects. Automating a broken process only makes it fail faster.
Design the target-state architecture across ERP, CRM, billing, and reporting layers: integration patterns, data contracts, master data, and a reliable data layer that AI and analytics can actually depend on.
Design intelligent workflows end-to-end: orchestration, tool use, retrieval, human-in-the-loop checkpoints, exception routing, and clear boundaries between deterministic automation and model-driven reasoning.
Build accuracy tracking, evaluations, guardrails, audit trails, and reconciliation into the design so automated decisions stay explainable and defensible to Finance, audit, and compliance.
Treat it as a system, not a prototype: schema validation, idempotency, retries, failover, monitoring, and telemetry so workflows survive API failures, degraded data, and silent errors without manual intervention.
Embed solutions into how teams already work, with training, ownership, and executive sponsorship. Adoption is the deliverable; a deployed tool nobody uses is not transformation.
Instrument outcomes: cycle time, effort removed, quality, and decision speed. Then productize the patterns into reusable components so each next use case ships faster than the last.
I treat every system as a question waiting to be cross-examined. Curiosity is a posture, not a phase.
Hypotheses ship in days, not quarters. The cheapest model that disproves the idea wins.
Optimize the loop, not the line. Most 'problems' are downstream artifacts of upstream choices.
Discipline compounds. The bar isn't 'it works,' it's 'it keeps working when no one is watching.'
Intelligent automation is decision plumbing. Frameworks beat intuition at scale.
I'd rather ship a small thing this week than draft a perfect thing next quarter.
Technology creates potential. Adoption creates value. Transformation happens when people change how they work.
Technology is the means, not the mission. Every initiative should trace back to measurable business value.
Sustainable transformation happens when capability becomes distributed. Success isn't what I build, it's what others can run without me.