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Responsible AI UseFramework

AI Integration Evaluation Framework

How to evaluate when AI is appropriate for your organization and when it's not.

01

AI Integration Evaluation Framework

Before implementing any AI solution, use this framework to evaluate whether it's appropriate for your context.


02

Part 1: Prerequisites Check

Before any AI evaluation, confirm these prerequisites are in place:

Process Prerequisites

Data Prerequisites

Organizational Prerequisites

If any prerequisites are missing, address them before proceeding.


03

Part 2: Use Case Evaluation

Suitability Assessment

Rate each factor 1-5 (1 = Poor fit for AI, 5 = Excellent fit for AI):

FactorRatingNotes
Task is repetitive and consistent  
Inputs are structured and predictable  
Rules/criteria are clear and documentable  
Volume justifies automation investment  
Error tolerance is reasonable  
Speed improvement would be valuable  
Human judgment is minimal  

Scoring:

  • 28-35: Strong candidate for AI
  • 21-27: Possible candidate, proceed carefully
  • Below 21: AI likely not appropriate

Risk Assessment

Evaluate potential downsides:

Risk FactorImpact (L/M/H)Likelihood (L/M/H)Mitigation
AI makes incorrect decisions   
Data privacy concerns   
Bias in AI outputs   
Dependency on AI vendor   
Cost exceeds value   
Team can't maintain it   
Stakeholders don't trust it   

04

Part 3: Implementation Planning

If evaluation is positive, plan implementation:

Scope Definition

What specifically will AI do?

  • Input: _______________
  • Process: _______________
  • Output: _______________
  • Boundaries: _______________

Human Oversight

How will humans stay in the loop?

  • Review frequency: _______________
  • Override capability: _______________
  • Escalation triggers: _______________
  • Accountability: _______________

Success Metrics

How will you measure success?

MetricCurrent BaselineTargetMeasurement Method
    
    

Monitoring Plan

How will you monitor AI performance?

  • Error detection method: _______________
  • Performance dashboards: _______________
  • Alert thresholds: _______________
  • Review cadence: _______________

Rollback Plan

If this fails, how do you revert?

  • Rollback trigger: _______________
  • Rollback process: _______________
  • Data preservation: _______________
  • Communication plan: _______________

05

Part 4: Ethical Considerations

Impact Assessment

Who is affected by this AI?

  • Direct users: _______________
  • Indirect stakeholders: _______________
  • Vulnerable populations: _______________

What are the potential harms?

Mitigation measures: _______________

Transparency Requirements


06

Part 5: Decision Matrix

Summarize your evaluation:

CriteriaAssessmentWeightScore
Prerequisites metYes/Partial/No25% 
Use case suitabilityHigh/Med/Low25% 
Risks acceptableYes/Partial/No20% 
Implementation feasibleYes/Partial/No15% 
Ethics clearYes/Partial/No15% 

Recommendation

Based on this evaluation:


07

Part 6: Post-Implementation Review

Schedule reviews at:

Review Questions

  1. Is AI performing as expected?
  2. What errors have occurred?
  3. How have users responded?
  4. Are there unintended consequences?
  5. Should we expand, maintain, or discontinue?

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