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Build Your AI Leadership Strategy

IBM via Coursera

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 1 hour a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

Found in

Part of

IBM Lead AI Transformation: Strategy, Governance & Execution

Overview

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This IBM course teaches you to turn broad business goals into a focused, defensible AI strategy. Prioritize the right use cases, sequence them into a realistic roadmap, and build the business case that earns executive approval. You'll start by translating high-level ambition into a small set of high-conviction AI bets. Draw the line between genuine strategy and scattered experimentation. Using a framework to compare value and effort, rank competing investments by business impact against data availability, feasibility, and risk. Defend a short, prioritized shortlist. Sequence those choices into a phased roadmap with milestones, dependencies, and early quick wins that build momentum and stakeholder alignment. Finally, assemble a one-page business case—costs, expected value, key risks, and assumptions—clear enough for executives to say yes to. Methods are taught tool-agnostic, with IBM and other tools demonstrated by industry experts. You'll build your skills in the core of leadership strategy: the ability to tie AI decisions to measurable business outcomes.

Syllabus

Turn Business Goals into AI Priorities
- Turn a broad mandate to “use AI” into a focused, defensible AI strategy. This module shows leaders and managers how to translate business goals into a small set of high-value AI priorities, tying every AI initiative to a measurable business outcome, a KPI, and an owner. Learn to tell a genuine AI strategy from scattered experimentation, apply portfolio thinking to prioritize AI use cases, and align generative AI and enterprise AI investment with core business strategy instead of technology hype. Built for aspiring AI transformation leaders, product and operations managers, and executives developing AI leadership skills, it covers AI strategy alignment, use-case prioritization, value and ROI framing, and the reasoning behind the high-conviction AI bets that actually scale across the enterprise.
Prioritize AI Use Cases
- Prioritize AI use cases and turn scattered AI projects into a focused, funded AI strategy. This module builds the decision-making skill enterprise leaders need to rank competing AI investments, weighing business value against feasibility, implementation effort, and risk to produce a short, defensible priority list they can justify to a board, CFO, or risk committee. It covers AI use-case selection, weighted scoring, the value–feasibility–risk matrix, portfolio prioritization, sequencing and road mapping, and tying each AI initiative to a measurable KPI. Built for AI transformation leaders, AI program and product managers, and business-unit leaders driving AI adoption, it develops practical judgment for AI portfolio management, ROI, and governance — the skill that decides which AI opportunities enterprise funds first, and why. No prior AI or coding experience is required.
Build the AI Transformation Roadmap
- A prioritized list of AI use cases is not yet a plan. This module teaches AI and business leaders how to build an AI transformation roadmap — a phased, milestone-driven plan that sequences enterprise AI initiatives from pilot through production and scale. It covers mapping dependencies, placing early quick wins, and ordering initiatives by organizational readiness and momentum rather than by technical feasibility alone. Core topics include roadmap planning, use-case sequencing, phased execution, stakeholder alignment, governance, data readiness, change management, and adoption — the essential skills of enterprise AI strategy and digital transformation. Designed for aspiring and practicing AI transformation leaders, program and product managers, and business-unit leaders, the module connects strategy, execution, and measurable business outcomes into one defensible plan that executives can approve and fund.
Build the AI Business Case
- Turn approval-stopping AI proposals into a credible, fundable investment case. This beginner-friendly module teaches business leaders how to build an AI business case that executives, CFOs, and boards will actually approve — no finance or coding background required. Learn to write for the finance reader, lead with a quantified business problem rather than the technology and rest your numbers on a measured baseline instead of vendor estimates. You’ll model return on investment (ROI) across conservative, base, and optimistic scenarios; account for total cost of ownership (TCO), including data preparation, integration, and change management; build a risk register with named accountability; and quantify the cost of doing nothing. Core skills include AI strategy, financial modeling, cost-benefit analysis, business value measurement, stakeholder communication, and executive decision-making for enterprise AI transformation.