Use a scorecard to rank AI use cases

What this solves

The business has a list of AI ideas, but no shared way to decide which one should come first, so tool enthusiasm and personal preference drive priority.

• Each person has a different favorite use case and a different definition of value.
• The team debates tools before agreeing on the workflow, owner, success metric, or risk boundary.
• No one can explain why one workflow beats another in commercial, operational, and readiness terms.

What AI is good at here

• Normalizing messy ideas into comparable workflow descriptions with trigger, input, output, owner, volume, and risk.
• Applying consistent scoring criteria across value, repetition, source quality, review risk, system complexity, and adoption effort.
• Summarizing tradeoffs between upside, clarity, risk, implementation effort, and speed to first proof.

What AI should not own

• Humans choose the weights and make the final decision based on business strategy, owner capacity, and risk appetite.
• AI should not treat every scorecard point as equally important or hide a high-risk workflow behind a high value score.

Best first implementation

• Score each candidate on owner-time return, revenue recovery or protection, customer impact, repetition, input clarity, source quality, review risk, system complexity, and owner readiness.
• Discuss only the top 3 after scoring and write down why the highest-scoring idea might still be deferred.
• Pick one workflow for a contained test with a named owner, success metric, source set, and review rule.

What good looks like

• The first use case has a defensible business reason instead of being the loudest idea.
• Internal debate becomes concrete because people are arguing over scores, evidence, and weights.
• The next few workflow candidates remain visible for later rather than disappearing into a notes document.

Common mistakes

• Scoring too many ideas with no commitment to choose and test one.
• Letting the loudest stakeholder set the weights implicitly or ignoring risk because the upside looks attractive.