How to Evaluate an AI Use Case Before Spending on Development

The operational problem

AI proposals are difficult to compare because the value is described in capability terms rather than operational terms.

Why it happens

Capability is easy to demonstrate. Operational value requires measuring the current process first.

What leaders usually miss

If the current process cannot be described and measured, the AI project has no baseline and no way to prove success.

What technology can and cannot solve

AI can change the cost or speed of a defined task. It cannot rescue a project with no owner, no baseline, or no data.

Example solution patterns

Example solution pattern - not a packaged YOTT product.

• A bounded pilot on one measurable task
• A human-in-the-loop workflow that keeps judgement with a person
• An evaluation period with agreed success criteria

Questions to ask internally

Run every AI proposal through these before funding development.

• What is the current cost of doing this task manually?
• What data does the system need, and is it accessible?
• What is the failure mode, and who catches it?
• What measurable change would justify continuing?