AI Business Cases and ROI Models

IBM focuses on the evidence and assumptions behind an AI investment proposal. Cost modeling connects with baselines, value metrics and a decision-ready case. It suits learners who want a proposal to support a decision either way, including situations where the expected benefits do not justify the full cost.

What you will learn

• Structure an evidence-based AI business case.
• Build an ROI model with explicit costs and assumptions.
• Define baselines and measurable value indicators.

Who this suits

Beginners evaluating AI investments; the provider requires neither coding nor spreadsheet expertise.

Before you enroll

Use fictional or approved data when testing business tools. Check account, subscription and usage conditions before starting an automation. Compare results with a baseline and include review, failure and maintenance costs. Course examples describe possibilities; they do not establish a return on investment for a particular organization.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Provider access terms can change; review them before paying.

Put it into practice

Build a fictional adoption case with optimistic and conservative scenarios, including review, rework and ongoing operating costs.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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