AI Literacy for Business Leaders

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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Before you can lead AI, you need to understand it in business terms. This IBM course builds the AI literacy every modern leader needs. In plain language, you'll learn what today's AI can and cannot do, including generative AI and agentic systems that plan and take actions on their own. You’ll analyze where each AI system creates measurable value across business functions. You'll practice spotting high-value opportunities before budget is committed. You’ll learn to read the maturity signals that separate a genuine opportunity from a costly distraction. You’ll practice assessing whether your organization's data, talent, and infrastructure are ready. You'll also apply a responsible-AI lens—fairness, transparency, and accountability—to use cases from a sample enterprise. IBM tools and principles are optional; the skills stay tool-agnostic. By the end, you'll speak about AI credibly with both technical teams and the board, and tell a real opportunity from hype.

Syllabus

Demystify AI for Leaders
- Every business leader now needs to understand artificial intelligence in business terms, not technical ones. This beginner-friendly module builds core AI literacy for leaders and managers. We’ll explore the big categories you hear about every day in this field: AI, machine learning, deep learning, generative AI, and agentic AI. With video lectures, reading, interactions and exercises, you’ll learn to tell these categories apart, understand what each type of AI can and cannot do, and explain in plain language where AI creates value across business functions. This course and module are for professionals with no coding or data-science background. Wherever you are in your company’s org chart, AI adoption creates opportunities for you to be a leader and communicator. The module is ideal for anyone leading AI adoption who wants to cut through the hype, speak credibly about AI with technical teams and executives, and make confident AI decisions rather than defer to specialists.
Spot High-Value AI Opportunities
- Every business leader faces the same question: of all the places AI could go, where does it actually create value? This module builds a practical, in-demand skill for AI strategy and enterprise AI transformation — identifying and prioritizing high-value AI use cases before budget is committed. Learners gain a repeatable, tool-agnostic approach to AI opportunity mapping: scanning business functions for candidate use cases, scoring each for AI fit and feasibility, weighing business value and ROI, and ranking opportunities into a focused, defensible portfolio. Built for business leaders, managers, and aspiring AI and digital transformation leaders with no coding background, the module turns scattered AI activity and hype into disciplined, evidence-based decision-making — the front end of any credible AI strategy. It suits anyone leading AI adoption, opportunity assessment, or use-case prioritization across an organization.
Assess AI Readiness
- Most AI initiatives stall between pilot and scale — not because the technology fails, but because the organization was never ready. This beginner-friendly module teaches business leaders and managers how to assess AI readiness across the dimensions that decide whether enterprise AI succeeds: strategy, data, infrastructure, talent, governance, and culture. Using a structured AI readiness assessment framework and maturity model, learners distinguish AI-ready data from ordinary business-intelligence data, benchmark readiness against clear criteria, find the binding constraint that limits the whole initiative, and turn a maturity score into a prioritized gap analysis and action roadmap. Designed for professionals with no coding or data-science background, the module builds the AI strategy, AI governance, and change-readiness skills leaders need to guide AI adoption, scaling, and digital transformation with evidence rather than enthusiasm — producing a clear-eyed readiness snapshot instead of a wish list.
Responsible AI Fundamentals for Leaders
- Responsible AI has become a core leadership discipline, not a compliance afterthought. This beginner-friendly module builds practical foundations in responsible AI, AI ethics, and AI governance for business leaders and managers. Learners explore the recurring principles of fairness, transparency, accountability, privacy, and security; learn how algorithmic bias enters AI systems and what fairness testing and explainability mean in practice; and come to understand the AI regulatory landscape, including high-risk use cases, bias audits, and accountability for third-party AI tools. The module shows how to apply an ethical lens to any AI use case early — screening for AI risk before deployment — and how to turn ethical commitments into AI policy, oversight, and trustworthy, well-governed AI with real decision rights. Designed for professionals with no coding background who lead AI adoption, AI strategy, risk, compliance, or transformation.