Costa Rica
Last updated: 2026-03-04
| Category | Question to Ask | Example Response | Purpose |
|---|---|---|---|
| Business Objective | What problem are you trying to solve with AI? | We want to reduce manual ticket triage time. |
Understand the core use case and business value. |
| AI Use Case Type | Is this a predictive, generative, or classification use case? | We want to predict equipment failure before it happens. |
Helps determine the AI model type and architecture. |
| Data Availability | What kind of data do you have access to? | We have historical logs, sensor data, and incident reports. |
Assesses data readiness and integration needs. |
| Data Location | Where is your data stored (cloud, on-prem, hybrid)? | Most of our data is in Azure Data Lake. |
Determines data pipeline and access strategy. |
| Real-Time vs Batch | Do you need real-time insights or is batch processing sufficient? | Real-time alerts are critical for us. |
Influences infrastructure and model deployment strategy. |
| Integration Points | What systems will this AI solution need to integrate with? | ServiceNow, Jira, and our internal monitoring tools. |
Identifies APIs, connectors, and integration complexity. |
| User Interaction | Will end users interact with the AI directly (e.g., chatbot) or indirectly? | It will be embedded in our internal dashboard. |
Helps define UI/UX and delivery method. |
| Security & Compliance | Are there any compliance or data privacy requirements (e.g., HIPAA, GDPR)? | Yes, we must comply with SOC 2 and GDPR. |
Determines constraints on data handling and model training. |
| Preferred Cloud | Do you have a preferred cloud provider or existing cloud contracts? | We’re primarily an Azure shop. |
Guides service selection (e.g., Azure ML, AWS SageMaker, GCP Vertex AI). |
| AI Maturity | Have you used AI/ML in production before? | We’ve done some POCs but nothing in production. |
Assesses readiness and need for foundational support. |
| Model Ownership | Do you plan to build your own models or use prebuilt ones (e.g., OpenAI, Azure AI)? | We’d prefer to fine-tune a prebuilt model. |
Helps scope the project and choose between custom vs. managed services. |
| Monitoring Needs | How will you monitor and evaluate model performance? | We’ll need dashboards and alerts for drift and accuracy. |
Ensures observability and governance are planned. |
| Scalability | How many users or transactions do you expect the AI to handle? | We expect 10,000+ daily interactions. |
Determines infrastructure sizing and cost implications. |
| Budget & Timeline | What’s your budget and timeline for this initiative? | We have a 3-month window and a $50K budget. |
Helps prioritize scope and feasibility. |
| Success Metrics | How will you measure the success of this AI solution? | Reduction in ticket resolution time by 30%. |
Aligns technical goals with business KPIs. |
Refresh Date: 2026-03-04