Led an enterprise-wide transformation to stabilize operations, modernize delivery practices, and embed practical AI capabilities into high-volume workflows. The initiative improved reliability, accelerated delivery, and eliminated tens of thousands of recurring support and warranty-related cases annually, while maintaining strong governance and risk controls.
A large, multi-site enterprise operating across manufacturing, engineering, and service environments was experiencing rapid growth through both organic expansion and acquisitions. Technology teams were under pressure to improve reliability, accelerate delivery, and scale operations without increasing risk or operational cost.
Without intervention, continued growth risked compounding operational issues and eroding stakeholder confidence.
Established a disciplined, outcome-driven operating model focused on reliability, delivery predictability, and measurable value. Aligned architecture, engineering, operations, and business leadership around shared KPIs and phased execution. AI enablement was positioned as a productivity and scale lever—governed, measurable, and embedded into existing workflows rather than treated as experimental technology.
AI was applied to high-volume, repeatable workflows where it could create immediate leverage, including quality detection, support analysis, and knowledge discovery. Adoption was governed through data classification, approved tools, logging, human-in-the-loop decisioning, and architectural oversight to ensure security, compliance, and trust.
The organization shifted from reactive operations to predictable, scalable delivery. Leadership gained improved visibility into performance and investment impact, teams operated with greater confidence and speed, and AI became a trusted capability embedded within governed enterprise workflows rather than a standalone experiment.
Success was driven by disciplined governance, outcome-based measurement, and phased adoption. AI and automation were treated as platform capabilities with clear ownership, risk controls, and ROI expectations—aligned to business outcomes rather than novelty.
Accountable for enterprise technology strategy, operating model design, AI enablement governance, cross-functional delivery alignment, and executive stakeholder engagement across architecture, engineering, and operations.