AI Readiness Assessment

A short and very basic assessment guide for those wanting to get started on their own.

1. Strategic Alignment

• Clearly define the objectives and outcomes you expect from AI.

• Identify how AI aligns with your strategic goals and business processes.

2. Data Capability

• Assess data completeness, accuracy, consistency, and timeliness.

• Evaluate ease of data access across teams and departments.

• Confirm data governance frameworks for compliance and ethical use.

3. Technical Infrastructure

• Review if current infrastructure supports scalability.

• Determine ease of integration with existing systems.

• Check robustness of cybersecurity practices specific to AI systems.

4. Talent and Culture

• Evaluate internal technical capabilities and identify skill gaps.

• Gauge organisational openness to innovation and iterative experimentation.

• Confirm senior leadership commitment to AI initiatives.

5. Financial and Operational Readiness

• Ensure sufficient funding and resources for initial adoption and scaling.

• Evaluate readiness for adapting workflows, roles, and responsibilities.

6. Regulatory and Ethical Considerations

• Identify relevant industry-specific and regional regulations.

• Develop ethical guidelines for AI application, transparency, and accountability.

7. Pilot and Scaling Plan

• Plan manageable AI pilots with clear metrics.

• Outline processes and criteria for scaling successful AI projects.

Scoring and Action Planning

Rate each section on a scale (1-low, 5-high). Total your scores:

• 28-35: High readiness—Proceed aggressively.

• 21-27: Moderate readiness—Address gaps before large investments.

• 14-20: Low readiness—Focus on fundamentals and targeted pilots.

• Below 14: Significant improvement needed—Prioritise foundational work first.

Use this assessment to create targeted action plans and strategic roadmaps for successful AI adoption.