AI Idea Validation Checklist for Product Managers

Use this checklist to evaluate the feasibility, impact, and scalability of your AI idea before moving to development.

[ ] User Pain Point Identified: Is there a clear problem the AI solution is addressing?
[ ] Target Audience: Have you defined the primary users (e.g., students, teachers, administrators)?
[ ] Value Proposition: Can you articulate how the AI will improve the user experience or solve the problem better than existing solutions?

[ ] Data Availability: Do you have access to high-quality, relevant, and sufficient data for training the model?
[ ] Data Privacy: Are there any legal or ethical concerns with using the required data (e.g., GDPR, FERPA)?
[ ] Technical Complexity: Is the AI approach realistic given your resources (time, team expertise, budget)?
[ ] Pre-trained Models: Are there pre-existing models or APIs you can fine-tune or leverage? (See this list for exhaustive list)
[ ] Infrastructure: Do you have the infrastructure (e.g., compute power, storage) needed to train and deploy the model?

[ ] Competitor Analysis: Have you analyzed similar AI products in the market to identify differentiation opportunities?
[ ] User Demand: Is there evidence (e.g., surveys, interviews, analytics) showing users want this feature?
[ ] Adoption Feasibility: Will the target audience easily adopt the solution, or is there a steep learning curve?