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Return on investment

As explained in The Art of AI Product Development

Return on investment is the financial or economic gain produced by an investment relative to its cost.

Return on investment (ROI) compares the financial or economic gain from an investment with its cost. In AI product work, it turns a proposed capability into an outcome-based case: expected revenue, cost reduction, efficiency, retention, or other measurable value. section 12.2.1 section 2.3.1

A credible ROI case connects the investment to decisions and assumptions:

  • Define the business problem and identify the KPIs it should affect. section 12.2.1
  • Estimate benefits using explicit assumptions about adoption, pricing, efficiency, or cost reduction. section 12.2.1 section 12.4
  • Validate user impact, technical feasibility, market demand, and regulatory constraints before committing substantial resources. section 2.3.1

Inventory optimization

An inventory optimization feature could reduce waste and support a premium pricing tier. If 20% of top-tier clients adopt it in the first year and each produces a $50,000 upsell, the projected result is $2 million in additional annual recurring revenue—provided the launch stays on schedule. The estimate gives executives a basis for deciding whether to fund a pilot. section 12.2.1

How The Art of AI Product Development covers it

How deep it goes
Estimates value through KPIs, adoption, revenue, efficiency, and risk, but does not specify a calculation method.
Examples
Illustrates ROI through inventory optimization, client upsell projections, and healthcare-feature validation.
What it assumes
Requires a defined business challenge, relevant KPIs, user-impact evidence, feasibility assessment, and market or regulatory validation.
What you can do after
Evaluate AI opportunities and pitch them to executives with projected benefits, assumptions, and next steps.
How it connects
Connects ROI with KPIs, adoption rates, operational efficiency, market positioning, feasibility, and regulatory compliance.

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This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.