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IBM

Design AI Transformation Roadmaps

IBM via Coursera

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Overview

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Convert prioritized opportunities and an honest readiness picture into a phased, fundable plan. You learn to construct a transformation roadmap with milestones and dependencies, sequence an AI investment portfolio across near-, mid-, and longer-term horizons, decide what to centralize and what to federate as the plan scales, recognize where AI-enabled workflows and agents add value, and pressure-test a roadmap for feasibility and value. AI-enabled workflow framing references IBM watsonx Orchestrate, reflecting the field's shift toward agentic, multi-agent operations.

Syllabus

  • Roadmap Fundamentals
    • This module develops the core skills for designing an AI transformation roadmap that turns prioritized AI opportunities and organizational readiness into a phased enterprise plan. It covers phased AI roadmaps, roadmap milestones and dependencies, AI use-case sequencing, business value and readiness, horizon planning, AI phase gates, pilot-to-scale decisions, and enterprise AI planning. Learners examine centralized and federated AI operating-model choices, governance and standards ownership, shared-platform responsibilities, and local business execution. They practice sequencing AI initiatives with checkable preconditions rather than calendar dates, accounting for capacity and downstream work, and planning how demonstrated value can support responsible scaling. The result is a stronger foundation for AI transformation planning, roadmap design, and consulting.
  • Sequencing the Investment Portfolio Across Horizons
    • This module builds practical skill in AI investment portfolio management, investment horizon planning, phased AI funding, capital allocation, and transformation roadmap sequencing. Learners examine how to place enterprise AI initiatives across near-, mid-, and longer-term horizons using proof-maturity, dependencies, risk, and readiness rather than calendar dates alone. The module covers portfolio balance, pilot-to-scale funding gates, capacity constraints, dependency mapping, investment sequencing under uncertainty, and the conditions that allow early work to fund and de-risk later commitments. Learners also explore how finance, business-unit, portfolio, and AI leadership perspectives shape funding decisions, then practice classifying initiatives, testing portfolio balance, and stating observable conditions for defer, fund, or scale decisions.
  • AI-Enabled Workflow and Agent Opportunities
    • This module develops practical skills for identifying AI-enabled workflow opportunities and framing AI agent use cases for enterprise transformation roadmaps. Learners use process mapping and workflow redesign to distinguish ordinary automation, predictive or generative AI, assistants, and multi-step agentic workflows. They learn how to identify AI automation candidates, isolate the agentic surface where judgment justifies autonomy, and account for deployment layers, citizen developer governance, permissions, guardrails, system connections, ongoing upkeep, human escalation, and verification. The module also strengthens AI opportunity framing by showing how reach, reversibility, workflow ownership, and residual work shape cost, risk, and feasibility. The focus is opportunity identification and roadmap-ready framing, not technical build or deployment.
  • Pressure-Testing the Roadmap
    • Roadmap review and pressure-testing help organizations turn an approved transformation plan into a credible, fundable roadmap. This module develops practical skills in roadmap feasibility, plan validation, assumption testing, dependency mapping, sequencing risk, premortem analysis, red-team review, stage-gate review, and failure-mode identification. Learners distinguish planning from testing, separate incorrect assumptions from fragile dependencies, and use independent review to surface hidden weaknesses before execution. They practice stress-testing transformation plans, testing controls against operational load, identifying concrete consequences, and choosing dispositions such as correction, resequencing, fallback design, de-scoping, deferral, or removal. The module strengthens critical thinking for consultants who must evaluate roadmap value, feasibility, resilience, and execution risk.

Taught by

LearnQuest Network

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