Amit Ghag

About Amit Ghag

Product quality and velocity rarely fail for lack of effort - they fail when teams lack a sharp strategy for what to test, why it matters, and how to apply AI efficiently. Passion for the product too easily eclipses disciplined focus on the customer problem.Current Role: Build the enterprise AI capability for Product Engineering teams: operating model & roadmap, unified toolchain, faster idea→pilot flow, responsible governance, talent pathways, adoption & outcome instrumentation.My Impact- 47% OPEX reduction (elimination / standardization / automation / self‑service)- 30.3% CAGR from $3.89M with 15% YoY productivity gains (3 years)- Global portfolios: 150+ FTE;$10M+ annual revenue impact- Restructured IT operating model improving agility & decision speed- High‑trust, high‑retention leadership bench built.Philosophy: Staying calm brings clarity; clarity builds trust; trust creates results. I coach emerging leaders so the momentum outlives any one individual.Differentiators: Calm, structured leadership; diligent execution standards; trusted reliability; followership cultivation; customer‑centric strategy translating capabilities into adoption & measurable outcomes.Advisory & Speaking: Advisory Board Member (quality/AI platform) influencing adoption criteria, AI capability priorities, customer‑centric roadmap validation, value metrics; regular Quality Engineering event speaker.2026 Focus: Product Strategy | Autonomous Testing Agents | AI Capability Maturity & Operating Model | Outcome & Adoption Instrumentation.Parallel passion for personal financial planning strengthens my structured, analytical approach to strategic decisions and value realization.Happy to exchange perspectives with product & platform executives on scaling AI‑enabled quality and adoption.

Experience

1. Capability Leader Ai for Engineering Transformation

   Eaton

   Jul 2025 — Present · Pune, IN

   Mandated to build AI capability for Eaton’s Product Engineering groups—defining the operating model & roadmap, unifying toolchains, embedding responsible governance, standing up talent pathways, and instrumenting adoption/outcome metrics across Electrical, Aerospace, and Vehicle/Mobility businesses.Targeting a 50% reduction in idea→pilot lead time by standardizing playbooks, streamlining approvals, and removing tooling fragmentation.Driving a unified platform ecosystem to simplify and consolidate operations, boost reuse, and accelerate AI adoption across engineering teams.“Simplicity with Structure, Value over Volume”: standardized toolchains and decision checklists that keep teams focused on customer value and quality signals.Embedding learn‑fast loops - short, blame‑free retros and pattern sharing - to turn mistakes into reusable assets.Aligning cross-functional stakeholders (AI Council, Enterprise Architecture, Security, Data Governance, Product Owners) around a common governance and value framework.

Education

• University of Mumbai

  Bachelor of Engineering

  1995 — 1999

• Institute of Product Leadership

  Executive MBA (Pursuing)

  2023 — 2025

• Indian Institute of Technology, Bombay

  PG professional course

• C-DAC

  Diploma in Advanced Computing

  2000 — 2000

Skills

• Process Improvement
• Agile Methodologies
• Management
• People Management
• System Integration Testing
• Digital Strategy
• System Testing
• Project Governance
• Global Delivery
• Regression Testing
• Software Development Life Cycle (Sdlc)
• Qtp
• Automation
• Defect Tracking
• Hp Quality Center
• Software Project Management
• Technological Innovation
• Test Automation
• Test Cases
• Hp Quicktest Professional (Qtp)
• Test Planning
• Point of Sale (Pos) Systems
• Program Delivery Management
• Testing
• Test Strategy
• Integration Testing
• Test Management
• Manual Testing
• User Acceptance Testing
• Mobile Testing
• Engagement Management
• Hp Qtp
• Sdlc
• Quality Center