Scaling Industrial AI from Pilot to Enterprise Value
My AI work focuses on moving beyond experimentation and into real operational adoption. I have led and supported initiatives across AI knowledge assistants, generative AI for developer productivity, predictive maintenance, and industrial workflow intelligence — always grounded in trusted data, responsible design, and measurable business outcomes.
- 55%
- Developer productivity improvement from generative AI pilot
- 4.5 / 5
- User satisfaction for AI-assisted development
- 50 furnaces
- AI/ML predictive maintenance scale
- 2026
- ACC Responsible Care® AI & Digitalization Award recognition for Dow AI Assistants
- Led AI-powered Knowledge Assistant initiatives using engineering, process safety, and personal safety standards to improve access to critical guidance and support safer, more consistent decision-making.
- Contributed to Dow's AI Assistants work, answering hundreds of questions weekly and recognized by the 2026 ACC Responsible Care® AI & Digitalization Award, highlighting the role of AI in advancing safety, sustainability, and responsible chemical-industry performance.
- Co-innovated with Microsoft on an Industrial AI Assistant integrated with maintenance workflows, piloting and scaling the solution globally while helping field workers retrieve contextual equipment history and improve work-order quality.
- Led a cross-functional GitHub Copilot generative AI pilot across R&D, Manufacturing & Engineering, Integrated Supply Chain, Information Systems, and EHS.
- Delivered a scalable framework for AI-assisted development adoption, increasing developer productivity by 55% with 4.5/5 user satisfaction.
- Accelerated AI/ML predictive maintenance for furnace reliability by providing the equipment context necessary for scale and helping reduce unplanned shutdown risk.
- Applied Responsible AI principles to balance innovation speed with transparency, reliability, governance, and sustainable adoption.