MIT · Module 6 Unit 2 · Final Assignment
AI Roadmap for Strategic Competitive Advantage: Ford Motor Company Customer Service Division
Julie St. John · 2026 · MIT AI: Implications for Business Strategy
AI Strategy
Enterprise Transformation
Ford FCSD
Google Cloud
Vertex AI
Porter's Strategies
Parts Pricing
Predictive Analytics
Agentic AI
Abstract
This paper presents a strategic AI roadmap for Ford Motor Company's Customer Service Division (FCSD), a business unit responsible for post-purchase experiences across a $30–40B annual parts and services ecosystem. The roadmap addresses Ford's fragmented data platform landscape and proposes a consolidated, semantic-enriched, AI-ready data platform to enable scalable AI experiences across customers, dealers, and technicians. The initiative focuses on three primary AI capabilities: predictive vehicle health monitoring, dynamic parts pricing powered by elasticity and competitive intelligence, and agentic analytics delivered via chatbot and semantic layer access. Built on a Google Cloud-first stack with Vertex AI, BigQuery, Neo4j graph databases, and Terraform infrastructure-as-code, the platform is designed for API-first interoperability and third-party dealer CRM integration. The roadmap maps AI investment to Porter's competitive strategies — primarily differentiation through enhanced experience, secondarily cost leadership through automation and demand forecasting, with a focus strategy applied to high-value commercial fleet segments.
⚠ This paper was submitted as academic coursework for MIT Executive Education. The views, analysis, and strategic recommendations expressed are solely my own and do not represent the official positions, plans, or strategies of Ford Motor Company or any of its affiliates.
SECTION 01
Executive Summary
Vision for a consolidated, enterprise-grade data platform enabling AI-driven experiences across FCSD. Maps initiative to differentiation, cost leadership, and focus strategies using Porter's framework.
500 words
SECTION 02
Current State Analysis
Assessment of Ford's siloed operating model, fragmented data maturity across 8+ divisions, and inconsistent Google Cloud adoption. Identifies competitive positioning across differentiation, cost leadership, and focus strategies.
500 words
SECTION 03
Proposed AI Initiative
Parts pricing optimization via ML and price elasticity modeling. Dealer CRM API integrations. Semantic data platform on Google Cloud with RAG, vector embeddings, and graph databases (Neo4j). Agentic AI via grounded chatbot experiences.
800 words
SECTION 04
Plan of Action & Success Criteria
Kanban-governed delivery across discovery (complete April), initial release (through June), and full implementation (July–December 2026). Dual-track roadmap: platform operations and continuous innovation through 2029.
800 words