AI Implementation Checklist

Establish clear goals for AI adoption aligned with business strategy

Create cross-functional team to oversee AI initiatives

Document principles for responsible AI use

Identify and assess potential AI-related risks

Define measurable outcomes for AI projects

Inventory and assess quality of available data

Define data ownership, access, and quality standards

Ensure GDPR/privacy compliance for AI training data

Build systems for data collection and processing

Establish workflows for training data annotation

Evaluate GPU/cloud resources needed for AI workloads

Choose appropriate tools and frameworks

Configure staging and production environments

Establish CI/CD for model deployment

Set up tools for tracking model performance

Evaluate existing team skills and gaps

Create learning paths for different roles

Clarify who does what in AI projects

Hire specialists or upskill existing staff

Identify advocates across business units

Understand AI regulations in your industry/region

Evaluate potential harms and mitigations

Set up processes to detect and mitigate bias

Prepare for AI-related issues and failures

Maintain records for compliance reporting