AI Strategy
Before Building an AI Solution: Five Questions Businesses Should Ask
Five practical questions that reveal whether an AI idea is valuable, feasible and ready for responsible delivery.
AI projects become clearer when the conversation starts with the business workflow. Five questions can expose the most important assumptions before significant implementation begins.
1. What outcome should change?
Define the user, decision, task or operating measure the solution should improve. “Use AI” is not an outcome.
2. What information does the task require?
Identify data sources, ownership, permissions, quality and update frequency. This often determines feasibility more than model choice.
3. How will we evaluate quality?
Create representative examples and acceptance criteria before optimizing prompts. Evaluation needs to reflect the real workflow and its failure modes.
4. What happens when the system is uncertain or wrong?
Decide when to cite, decline, escalate or request human approval. Controls should match the consequence of the action.
5. How will this fit existing work?
A technically impressive tool still fails if it adds friction. Plan the integrations, ownership, training and feedback loop needed for adoption.