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Learning Roadmap

How to Become a AI Roadmap Designer

A step-by-step, phase-based learning path from beginner to job-ready AI Roadmap Designer. Estimated completion: 6 months across 6 phases.

6 Phases
22 Weeks Total
Medium Entry Barrier
Advanced Difficulty
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  1. Foundations of AI Strategy & Business Alignment

    4 weeks
    Goals
    • Understand core AI/ML concepts well enough to evaluate feasibility of use cases
    • Learn business strategy frameworks (Porter's Five Forces, value chain analysis) as applied to AI
    • Develop data literacy: understand data quality, pipelines, feature engineering at a conceptual level
    Resources
    • Andrew Ng's 'AI for Everyone' (Coursera)
    • Hugging Face NLP Course (free)
    • Harvard Business Review: 'The AI-Powered Enterprise' articles
    • Book: 'Prediction Machines' by Agrawal, Gans, and Goldfarb
    Milestone

    You can articulate how AI creates business value and assess whether a proposed use case is technically plausible

  2. Use Case Design & Prioritization Mastery

    4 weeks
    Goals
    • Master use case identification techniques across industries
    • Learn and apply prioritization frameworks (ICE, RICE, WSJF) to AI initiatives
    • Build ROI and business case models for AI projects using spreadsheets and Python
    Resources
    • Google Cloud 'AI Adoption Framework' whitepaper
    • McKinsey 'The State of AI' annual reports
    • Book: 'Competing in the Age of AI' by Iansiti and Lakhani
    • Practice: Build an ICE scoring model in a spreadsheet for 20+ hypothetical AI use cases
    Milestone

    You can independently build a prioritized AI use case portfolio for a mid-size company with ROI estimates

  3. Technical Roadmapping & Dependency Planning

    4 weeks
    Goals
    • Learn phased roadmap design: sequencing by data readiness, dependencies, and organizational capacity
    • Understand MLOps maturity models and how they constrain roadmap timelines
    • Practice building roadmaps in professional tools (Notion, Airtable, Jira)
    Resources
    • Google 'MLOps Maturity Model' documentation
    • AWS Well-Architected Machine Learning Lens
    • DVC (Data Version Control) documentation for understanding ML workflows
    • Practice: Design a 4-quarter roadmap for a fictional e-commerce company
    Milestone

    You can create a detailed, phased AI roadmap with clear milestones, dependencies, and resource requirements

  4. Advanced Strategy: Governance, Ethics & Vendor Evaluation

    4 weeks
    Goals
    • Design AI governance and responsible AI frameworks integrated into roadmaps
    • Master vendor evaluation methodologies for LLM APIs, MLOps platforms, and AI tooling
    • Understand regulatory landscape (EU AI Act, NIST AI RMF) and its impact on roadmap design
    Resources
    • NIST AI Risk Management Framework (AI RMF 1.0)
    • EU AI Act summary and compliance guides
    • LangChain and LlamaIndex documentation for RAG/agent architectures
    • Practice: Build a vendor comparison matrix for LLM providers (OpenAI, Anthropic, Google, open-source)
    Milestone

    You can design governance-integrated roadmaps and make defensible build-vs-buy recommendations

  5. Portfolio Management & Organizational Change

    4 weeks
    Goals
    • Learn AI portfolio management: tracking multiple initiatives, rebalancing, and sunsetting
    • Develop change management skills for AI adoption (Kotter's framework, ADKAR)
    • Practice executive communication: board decks, strategy memos, and progress narratives
    Resources
    • Book: 'Leading Change' by John Kotter
    • Prosci ADKAR certification materials
    • Lenny's Newsletter and Stratechery for product strategy patterns
    • Practice: Create a quarterly AI roadmap update presentation for a fictional board
    Milestone

    You can manage a portfolio of 10+ AI initiatives with executive-level reporting and change management plans

  6. Capstone & Professional Positioning

    2 weeks
    Goals
    • Complete a comprehensive capstone: design a full AI roadmap for a real or realistic organization
    • Build a portfolio of roadmap artifacts (use case matrices, roadmaps, business cases)
    • Prepare for interviews and begin networking in the AI strategy community
    Resources
    • Your completed artifacts from Phases 1-5
    • LinkedIn and X (Twitter) AI strategy communities
    • Industry conferences: AI Summit, NeurIPS Applied track, ODSC
    • Practice: Conduct a mock AI roadmap engagement for a local business or non-profit
    Milestone

    You have a professional portfolio demonstrating end-to-end AI roadmap design capability and are ready to interview or freelance

Practice Projects

Apply your skills with hands-on projects. Ordered by difficulty.

AI Readiness Assessment Report

Beginner

Create a comprehensive AI readiness assessment for a fictional mid-size company across dimensions of data maturity, technical infrastructure, talent, culture, and strategy. Deliver a scored report with improvement recommendations.

~15h
AI maturity assessmentData literacyStructured analysis

AI Use Case Prioritization Matrix

Beginner

Identify 20+ potential AI use cases for a retail company, score them using ICE/RICE framework, and create a prioritized portfolio with business case estimates for the top 5.

~20h
Use case identificationPrioritization frameworksROI estimation

Multi-Department AI Roadmap for E-Commerce

Intermediate

Design a 4-quarter phased AI roadmap for an e-commerce company spanning marketing (personalization), operations (demand forecasting), and customer service (LLM-powered support). Include dependencies, milestones, resource estimates, and KPIs.

~30h
Phased roadmap designDependency planningCross-functional coordination

AI Vendor Evaluation & Selection Framework

Intermediate

Build a reusable vendor evaluation framework and apply it to compare LLM providers (OpenAI, Anthropic, Google, open-source alternatives) across dimensions of capability, cost, privacy, latency, and ecosystem maturity for 3 distinct use cases.

~25h
Vendor evaluationBuild vs. buy analysisTechnical assessment

3-Year Enterprise AI Transformation Roadmap

Advanced

Design a comprehensive 3-year AI roadmap for a Fortune 500 financial institution, including governance frameworks, MLOps maturity progression, regulatory compliance planning, talent development tracks, and board-ready executive presentation.

~45h
Multi-year strategic planningAI governance designRegulatory compliance

AI Portfolio Optimization Engine

Advanced

Build a Python-based tool that takes a list of AI initiatives with attributes (impact, cost, data readiness, strategic alignment, risk) and uses optimization algorithms to recommend the optimal portfolio given budget and capacity constraints. Include visualization dashboards.

~40h
Portfolio optimizationPython developmentData visualization

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