ElaMereanu

Legacy System AI Readiness Assessment

Use this template to evaluate whether your legacy systems are ready for AI integration using the Legacy-AI Bridge framework.

System Information

System Name: _____ **Business Function**: _______ **Technology Stack**: _______ **Age**: ___ years Critical to Operations: [ ] Yes [ ] No

Technical Assessment

Data Access (Score: ___/20)

• Data Export Capability (5 points)
  • Can export data in standard formats (CSV, XML, JSON)
  • Regular export processes already exist
  • Export doesn’t impact system performance
• API Availability (5 points)
  • REST or SOAP APIs available
  • File-based integration possible
  • Message queue integration supported
• Database Access (5 points)
  • Read-only database access available
  • ODBC/JDBC connectivity supported
  • Query performance acceptable
• Documentation Quality (5 points)
  • Data schemas documented
  • Business rules documented
  • Integration points mapped

Integration Readiness (Score: ___/20)

• Performance Tolerance (5 points)
  • System can handle additional read operations
  • Off-peak processing windows available
  • Performance monitoring in place
• Security Compliance (5 points)
  • Security protocols documented
  • Access controls in place
  • Audit requirements understood
• Change Management (5 points)
  • Change approval process defined
  • Testing procedures established
  • Rollback procedures documented
• Stakeholder Support (5 points)
  • Business sponsors identified
  • Technical team buy-in secured
  • End user champions available

Business Assessment

Value Opportunity (Score: ___/20)

• Process Pain Points (5 points)
  • Manual processes that could be automated
  • Decision delays due to data analysis time
  • Error-prone manual data entry
• Data Value (5 points)
  • Rich historical data available
  • Data quality is acceptable
  • Business insights possible from data
• ROI Potential (5 points)
  • Clear cost savings opportunities
  • Efficiency improvements measurable
  • Competitive advantage possible
• Success Metrics (5 points)
  • KPIs defined and measurable
  • Baseline metrics available
  • Success criteria agreed upon

Risk Assessment (Score: ___/20)

• Business Risk Tolerance (5 points)
  • Low risk appetite for system changes
  • Gradual implementation acceptable
  • Parallel processing possible
• Technical Risk Management (5 points)
  • Experienced technical team available
  • Testing environments exist
  • Disaster recovery procedures in place
• Compliance Requirements (5 points)
  • Regulatory requirements understood
  • Audit trail requirements documented
  • Data privacy requirements clear
• Organizational Readiness (5 points)
  • Change management processes mature
  • Training resources available
  • Communication channels established

Implementation Feasibility (Score: ___/20)

• Resource Availability (5 points)
  • Development team capacity available
  • Budget allocated for project
  • Timeline realistic and agreed upon
• Technical Skills (5 points)
  • Legacy system expertise available
  • AI/ML skills present or acquirable
  • Integration experience in team
• Infrastructure (5 points)
  • Development/testing environments available
  • Monitoring and logging capabilities
  • Backup and recovery systems in place
• Vendor Support (5 points)
  • Legacy system vendor support available
  • Third-party integration support possible
  • Cloud services accessible if needed

Scoring Guide

Total Score: ___/100

Readiness Levels

90-100: Excellent Readiness

• Proceed with full implementation
• All phases can be implemented
• Low risk, high success probability

75-89: Good Readiness

• Proceed with pilot implementation
• Address gaps before full deployment
• Medium risk, good success probability

60-74: Moderate Readiness

• Implement Phase 1 only initially
• Significant preparation needed
• Medium to high risk

45-59: Poor Readiness

• Extensive preparation required
• Consider alternative approaches
• High risk of failure

Below 45: Not Ready

• Significant infrastructure investment needed
• Alternative solutions recommended
• Very high risk

Recommended Next Steps

For Excellent/Good Readiness (75+):

1. Week 1-2: Detailed technical planning
2. Week 3-4: Proof of concept development
3. Week 5-8: Pilot implementation
4. Week 9-12: Full deployment

For Moderate Readiness (60-74):

1. Month 1: Address critical gaps
2. Month 2: Infrastructure improvements
3. Month 3: Phase 1 pilot
4. Month 4-6: Gradual expansion

For Poor/Not Ready (Below 60):

1. Quarter 1: Infrastructure modernization
2. Quarter 2: Skill development and training
3. Quarter 3: Re-assessment
4. Quarter 4: Pilot if ready

Risk Mitigation Strategies

High-Risk Areas Identified:

• Data access limitations
• Performance concerns
• Security restrictions
• Stakeholder resistance
• Technical skill gaps

Mitigation Plans:

1. Data Access: _______
2. Performance: _______
3. Security: _______
4. Stakeholders: _______
5. Skills: _______

Success Criteria

Phase 1 (Analytics):

• AI insights generated from legacy data
• No performance impact on legacy systems
• Stakeholder satisfaction with results

Phase 2 (Recommendations):

• AI recommendations integrated into workflows
• User adoption rate >70%
• Decision accuracy improved by >20%

Phase 3 (Automation):

• Automated processes operational
• Error rates reduced by >50%
• ROI targets achieved

Assessment Summary

Assessor: _____ **Date**: _______ **Overall Recommendation**: _________

Key Strengths:

1. ---

2. ---

3. ---

Critical Gaps:

1. ---

2. ---

3. ---

Immediate Actions Required:

1. ---

2. ---

3. ---

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This assessment should be reviewed quarterly and updated as system capabilities and business needs evolve.

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