The 90-Day Pilot: How to Validate AI Agents Before Full Deployment

The Validation Need 

Implementing AI agents without proof creates risk. A structured 90-day pilot validates capability, builds confidence, and provides data for informed expansion decisions. 

Understanding the complete pilot framework - setup, testing, production, evaluation - enables successful validation. 

The 90-Day Framework 

Weeks 1-2: Setup and Configuration 

Activities: 

• Discovery workshops with staff (8-10 hours) 

• Document current exception handling process 

• Define decision rules and escalation criteria 

• Develop conversation scripts 

• Configure AI platform and integrations 

• Set up test environment 

Staff time required: 12-15 hours 

Deliverables: 

• Documented process flows 

• Decision rule matrix 

• Draft conversation scripts 

• Configured test environment 

Success criteria: Rules documented, scripts approved, test environment functional 

Weeks 3-4: Testing and Refinement 

Activities: 

• Test with historical exceptions (20-30 scenarios) 

• Staff listen to AI handling and provide feedback 

• Refine scripts based on feedback 

• Adjust decision logic 

• Test edge cases 

• Prepare for limited production 

Staff time required: 10-12 hours 

Deliverables: 

• Refined conversation scripts 

• Updated decision rules 

• Test results documentation 

• Production readiness checklist 

Success criteria: AI handles 60%+ of test scenarios successfully, staff approve script quality 

Weeks 5-8: Limited Production 

Activities: 

• Deploy to 30-40% of exception volume 

• Exclude VIP accounts 

• Staff review all AI interactions initially 

• Daily monitoring first week 

• Weekly refinement sessions 

• Gradually expand volume 

Staff time required: 15-20 hours 

Key metrics tracked: 

• Complete handling rate 

• Escalation rate 

• Customer complaints 

• Staff feedback 

• Time savings 

Success criteria: 

• 60-70% complete handling rate 

• 20-30% appropriate escalation 

• Zero VIP account issues 

• No customer complaints 

• Staff comfortable with quality 

Weeks 9-12: Evaluation and Decision 

Activities: 

• Comprehensive results analysis 

• Staff feedback collection 

• Customer satisfaction assessment 

• ROI calculation 

• Decision point meeting 

• Expansion planning (if successful) 

Staff time required: 8-10 hours 

Decision framework: 

1. Review against success criteria 

2. Calculate actual vs projected ROI 

3. Assess staff acceptance 

4. Evaluate customer impact 

5. Determine next steps 

Three outcomes: 

• Expand: Success criteria met → Full deployment 

• Refine: Partial success → Extend pilot 60 days 

• Exit: Significant issues → Return to manual 

Success Criteria Definition 

Quantitative Metrics 

Complete handling rate: 60-70% 

• AI handles exception from identification through resolution 

• No human intervention required 

• Documented outcome 

Escalation rate: 20-30% 

• Situations requiring human judgment 

• Appropriate escalation triggers 

• Complete context provided 

Time savings: 40-60% 

• Reduction in staff hours 

• Measured against baseline 

• Sustainable over pilot period 

Customer satisfaction: Maintained or improved 

• No increase in complaints 

• VIP accounts unaffected 

• Relationship quality preserved 

Qualitative Indicators 

Staff acceptance: 

• Team sees value 

• Comfortable with quality 

• Willing to expand scope 

• Contributes improvement ideas 

Process clarity: 

• Decision rules well-defined 

• Escalation criteria appropriate 

• Documentation comprehensive 

• Continuous improvement evident 

Pilot Scope Definition 

Process Selection 

Best candidates: 

• AR collections (proven use case) 

• Vendor bill matching (structured process) 

• Back order management (systematic workflow) 

Avoid for first pilot: 

• Customer quotations (complex, varied) 

• Quality issue resolution (requires judgment) 

• New process categories (limited precedent) 

Customer Segmentation 

Include: 

• Standard business relationships 

• Typical payment patterns 

• Regular communication preferences 

• Mid-tier account values 

Exclude: 

• VIP or strategic accounts 

• Relationship-critical customers 

• Accounts with special handling requirements 

• Problem accounts with ongoing disputes 

Volume Requirements 

Minimum viable: 30-50 exceptions monthly 

• Sufficient data for evaluation 

• Meaningful time savings measurable 

• Representative sample size 

Too small (<30): Insufficient data, high per-exception cost  

Too large (>100): Excessive risk for first pilot 

Data Collection 

Required Tracking 

Every AI interaction: 

• Exception details (account, amount, age) 

• AI actions taken 

• Customer responses 

• Outcome (resolved, escalated, pending) 

• Time to resolution 

• Staff intervention (if any) 

Aggregated weekly: 

• Total exceptions handled 

• Complete resolution count 

• Escalation count with reasons 

• Average handling time 

• Staff hours saved 

Monthly summary: 

• Success rate trends 

• Escalation pattern analysis 

• Customer feedback compilation 

• ROI calculation update 

Common Pilot Challenges 

Challenge 1: Insufficient Volume 

Symptom: Only 15-20 exceptions monthly during pilot 

Impact: Cannot determine meaningful success rate 

Solution: Expand scope slightly (include additional customer segment) or extend timeline to gather sufficient data 

Challenge 2: Staff Skepticism 

Symptom: Team resists AI approach, focuses on failures 

Impact: Negative bias affects evaluation 

Solution: 

• Focus on data not opinions 

• Show comparison to manual handling errors 

• Involve staff in improvement process 

• Celebrate successes 

Challenge 3: Unrealistic Expectations 

Symptom: Expecting 90%+ automation rate 

Impact: Disappointment with 65-70% success 

Solution: Set realistic expectations upfront (60-70% target), explain why 100% is wrong goal 

Challenge 4: VIP Account Contact 

Symptom: AI accidentally contacts strategic account 

Impact: Relationship friction, staff confidence drops 

Solution: Pause pilot, verify VIP flags, apologize personally, strengthen safeguards, resume carefully 

Cost Structure 

Pilot Investment: $16,000-$27,000 

Breakdown: 

• Consulting and configuration: $12,000-$18,000 

• Platform setup: $1,500-$3,000 

• Staff time (50 hours): $2,500 

• Contingency: $2,000-$3,500 

Lower than full implementation ($35,000) by: 

• Limited scope (single process) 

• Shorter timeline (90 days vs full year) 

• Staged platform costs 

Expansion Path 

If Pilot Succeeds 

Week 13-14: Planning 

• Define full deployment scope 

• Update budget estimate 

• Plan timeline 

• Prepare communication 

Week 15-18: Expansion 

• Add remaining customer segments 

• Deploy to full exception volume 

• Maintain monitoring 

• Continue refinement 

Incremental cost: $5,000-$15,000 

Total investment: $21,000-$42,000 (vs $35,000 direct full deployment) 

Trade-off: $0-$7,000 premium for risk reduction 

The Reality 

90-day pilot validates AI agents with limited risk. Structured approach: Weeks 1-2 setup, Weeks 3-4 testing, Weeks 5-8 limited production, Weeks 9-12 evaluation. 

Success criteria: 60-70% complete handling, 20-30% escalation, 40-60% time savings, maintained customer satisfaction, staff acceptance. 

Pilot investment $16K-$27K. 60-70% expand successfully. 20-30% refine. 5-10% exit. 

Data-driven decision at Day 90 enables informed expansion or clean exit. 

About the Author: This content is published by ERP AI Agent. 

Published: January 2025 | Reading Time: 8 minutes