A Checklist for Getting Started with Responsible AI

It can be challenging to know where to get started, so here is our checklist for getting started:

1. Foundation: Define Your Responsible AI Vision

✅ Clarify what "responsible AI" means in your organizational context.

✅ Align AI strategy with business ethics, compliance, and cultural values.

✅ Establish a cross-functional leadership team that includes risk, HR, tech, and operations.

2. Governance: Build Strong Ethical and Operational Frameworks

✅ Create AI governance policies that define data handling, bias mitigation, and transparency.

✅ Set up review boards for high-impact AI initiatives.

✅ Use AI Ethics Impact Assessments to evaluate project alignment before deployment.

3. Upskill and Align Talent

✅ Identify current AI knowledge gaps across departments.

✅ Launch upskilling programs focused on AI fluency, ethical awareness, and cyber risk.

✅ Encourage adaptive learning cultures where AI literacy is part of every role.

4. Integrate AI into Core Strategy

✅ Apply AI where ROI is measurable: operations, forecasting, customer insights, and automation.

✅ Combine AI initiatives with cultural readiness to reduce resistance.

✅ Use pilots with clear KPIs before full-scale rollouts.

5. Secure AI with Cyber and Compliance Layers

✅ Conduct AI-specific threat modeling and penetration testing.

✅ Monitor third-party models and APIs for security weaknesses.

✅ Ensure AI deployment aligns with global compliance and industry regulations.