AI Readiness Assessment Checklist for SA Enterprises

Comprehensive checklist tailored for SA business environment

Comprehensive checklist tailored for SA business environment. This comprehensive guide provides practical tools and frameworks specifically designed for South African organizations.

Part of our comprehensive: AI Data Readiness Assessment Guide for South African Enterprises

Data Quality & Availability

• ☐ Data Accuracy: >95% accuracy in critical datasets
• ☐ Data Completeness: <5% missing values in key fields
• ☐ Data Consistency: Standardized formats across systems
• ☐ Historical Data: Minimum 2 years of relevant historical data
• ☐ Data Volume: Sufficient volume for model training
• ☐ Data Freshness: Real-time or near-real-time updates

Data Accessibility & Integration

• ☐ System Integration: APIs available for data access
• ☐ Data Silos: Less than 20% of data trapped in silos
• ☐ Data Documentation: Metadata and lineage documented
• ☐ Access Controls: Role-based data access implemented

POPIA Compliance

• ☐ Lawful Basis: Clear legal basis for AI data processing
• ☐ Consent Management: Proper consent for AI use of personal data
• ☐ Data Subject Rights: Ability to honor data subject requests
• ☐ Cross-border Transfers: Compliant international data sharing
• ☐ Breach Procedures: Incident response plan for AI systems

Data Governance Framework

• ☐ Data Ownership: Clear data stewardship roles
• ☐ Quality Standards: Defined data quality metrics
• ☐ Lifecycle Management: Data retention and deletion policies
• ☐ Audit Capabilities: Full audit trail for AI decisions

Computing Resources

• ☐ Processing Power: Adequate CPU/GPU for AI workloads
• ☐ Storage Capacity: Scalable storage for large datasets
• ☐ Network Infrastructure: High-speed, low-latency connections
• ☐ Load Shedding Resilience: Backup power and cloud failover

Platform Readiness

• ☐ Cloud Strategy: Clear cloud vs on-premise decisions
• ☐ Security Framework: Enterprise security for AI systems
• ☐ Monitoring Tools: Performance and model monitoring
• ☐ Development Environment: AI/ML development platform

Leadership & Culture

• ☐ Executive Sponsorship: C-level commitment to AI
• ☐ Change Readiness: Organization open to AI transformation
• ☐ Innovation Culture: Encourages experimentation
• ☐ Data-Driven Decisions: Current use of analytics

Skills & Capabilities

• ☐ Data Science Team: In-house or accessible expertise
• ☐ Technical Skills: Programming and ML capabilities
• ☐ Business Analysts: Bridge between business and tech
• ☐ Training Programs: Ongoing skills development

📈 Scoring Your Assessment

Scoring Scale:

• 90-100 points: AI-Ready (Top 2% of SA organizations)
• 75-89 points: Nearly Ready (Optimized level)
• 60-74 points: Developing (Managed level)
• 45-59 points: Basic (Defined level)
• Below 45: Starting (Ad-hoc level)

Industry Benchmarks: Average SA enterprise scores 52 points

📊 Free Assessment Tools

Download our comprehensive assessment toolkit designed specifically for South African enterprises:

• ✓ Excel-based assessment templates
• ✓ Industry-specific checklists
• ✓ ROI calculation worksheets
• ✓ Implementation timeline templates
• ✓ Vendor evaluation criteria

🔗 Part of Our Complete AI Readiness Framework

This assessment guide is part of our comprehensive AI data readiness methodology. For the complete framework including all assessment tools and implementation guidance:

→ View Complete AI Data Readiness Assessment Guide

Related Section: AI Data Readiness Framework section

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