What If It Doesn't Work? Exit Strategy and Risk Mitigation

The "What If" Question 

Every implementation carries failure risk. What if AI agents don't achieve promised results? What if customer acceptance is lower than expected? What if staff resistance prevents adoption? 

Understanding exit options, pilot approach, and risk limitation prevents paralysis while enabling informed decisions. 

The Pilot Approach 

What a Pilot Means 

Scope: Single exception process, limited customer segment, defined timeline 

Investment: $16,000-$27,000 (versus $35,000 full implementation) 

Timeline: 90 days from kickoff to decision point 

Purpose: Prove value with limited risk before full commitment 

Pilot Parameters 

Process scope: 

• Single exception type (AR collections OR vendor bills, not both) 

• Excludes VIP accounts 

• 30-50 exceptions minimum monthly for meaningful test 

Customer segment: 

• Standard business relationships 

• Exclude relationship-critical accounts 

• Typical payment patterns 

Success criteria defined upfront: 

• 60-70% complete handling rate 

• 20-30% appropriate escalation rate 

• Zero customer relationship damage 

• Staff acceptance (not resistance) 

• Measurable time savings 

Exit Decision Timeline 

Month 1: Implementation and Learning 

Activities: 

• Rule definition and testing 

• Script development 

• Staff training 

• Limited production deployment 

Exit consideration: Too early. Learning curve expected. 

Month 2: Active Operation 

Activities: 

• Expanding exception volume 

• Staff reviewing results 

• Script refinement 

• Pattern identification 

Exit evaluation: Review preliminary results. Identify issues requiring resolution. 

Month 3: Decision Point 

Activities: 

• Comprehensive results review 

• Success criteria assessment 

• Staff feedback collection 

• Cost-benefit analysis 

Exit decision: Based on data, not emotion. Three outcomes possible. 

Three Possible Outcomes 

Outcome 1: Success - Expand (60-70% of pilots) 

Indicators: 

• Complete handling rate 65%+ 

• Escalation rate 20-30% 

• No customer complaints 

• Staff positive or neutral 

• Measurable time savings evident 

Decision: Expand to full customer base and/or additional processes 

Investment: $5,000-$15,000 incremental for expansion 

Timeline: 4-6 weeks to full deployment 

Outcome 2: Refine - Continue Pilot (20-30% of pilots) 

Indicators: 

• Complete handling rate 50-60% 

• Issues identified but fixable 

• Customer acceptance mixed 

• Staff see potential but want improvements 

Decision: Extend pilot 60 days with targeted improvements 

Additional investment: $3,000-$8,000 for refinement 

Timeline: 2-3 months continued pilot 

Outcome 3: Exit - Discontinue (5-10% of pilots) 

Indicators: 

• Complete handling rate below 50% 

• Customer complaints significant 

• Staff strongly resistant 

• Process complexity exceeds AI capability 

Decision: Return to manual handling 

Sunk cost: $16,000-$27,000 pilot investment 

Learning value: Process documentation, rule clarity, what doesn't work 

What You Keep If You Exit 

Process Documentation 

Value: Documented decision criteria, exception handling rules, prioritization logic 

Use: Improves manual handling even without AI. Onboarding new staff easier. Consistency improves. 

Rule Clarity 

Value: Understanding of decision-making process that was previously implicit knowledge 

Use: Training material, process improvement, future automation attempts 

Staff Capability 

Value: Team learned to articulate how they handle exceptions 

Use: Process optimization, cross-training, identifying inefficiencies 

Technical Knowledge 

Value: Understanding of API capabilities, integration possibilities, automation potential 

Use: Future automation initiatives, vendor evaluation skills 

The Reality 

Pilot approach limits risk to $16,000-$27,000 investment. Clear success criteria enable data-driven decisions at 90 days. Exit is clean with no long-term commitments. 

60-70% of pilots succeed and expand. 20-30% refine and continue. 5-10% exit. Even failed pilots provide process documentation and learning value reducing effective sunk cost to $0-$6,000. 

The risk of not trying while exception volume grows and costs compound is higher than pilot risk. 

About the Author 

This content is published by ERP AI Agent, a consulting practice specializing in AI agents for mid-market ERP exception processes. 

Published: January 2025 Last Updated: January 2025 Reading Time: 7 minutes