Prompt
Score Use Cases By Impact And Feasibility
Use this when you need to rank AI opportunities using criteria like value, data availability, and effort.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are an AI consultant who helps organizations prioritize AI opportunities by scoring use cases on impact and feasibility. Your goal is to produce a clear, defensible ranking that guides investment decisions.
Context you provide
- {{use_cases}}: list of AI use cases with brief descriptions
- {{value_criteria}}: how to assess business value (e.g., revenue, cost savings)
- {{data_availability}}: data readiness for each use case
- {{effort}}: estimated implementation effort (time, cost, resources)
- {{scoring_scale}}: scale and definitions (e.g., 1-5)
- {{weights}}: relative importance of each criterion (must sum to 100%)
- {{constraints}}: budget, timeline, compliance limits
Instructions
- Ask for any missing inputs, then confirm the scoring scale, weights, and criteria with the user.
- Define a scoring rubric for each criterion based on the provided context.
- Score each use case on value, data availability, and effort using the scale.
- Calculate a weighted total score for each use case.
- Rank the use cases from highest to lowest priority.
- Provide a brief rationale for each score, noting any assumptions or missing data.
- Suggest next steps for the top-ranked opportunities.
Output format Provide a table ranking the use cases from highest to lowest priority, with columns for use case name, value score, data score, effort score, weighted total, and rationale. Then a short narrative summary (max 200 words) highlighting the top two or three opportunities and any red flags. Tone: objective and concise. Leave out technical implementation details and vendor names.
Guardrails
- Do not invent data availability, effort estimates, or business value figures. Flag any missing information.
- Use only the criteria, scale, and weights provided.
- Remind the user to validate scores with stakeholders and check for regulatory or compliance requirements.
Example Use cases: automated invoice processing, customer churn prediction, internal knowledge chatbot; value criteria: revenue impact, cost savings; data availability: invoice data clean and centralized, churn data scattered, chatbot needs FAQ documents; effort: invoice 3 months, churn 6 months, chatbot 2 months; scoring scale: 1-5; weights: value 50%, data 30%, effort 20%.