Your AI vendor just quoted you “industry-leading 94% accuracy.” Your team is excited. The board is ready to sign off. But here’s what nobody’s asking: accuracy at what, exactly? Using whose data? Under which conditions?
AI Vendor Due Diligence Checklist
The Essential Guide to big money AI Decisions
When AI implementations run 40% over budget and takes twice as long as promised, systematic due diligence is a must.
Technical Validation
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Real Data Testing: Vendor tested with 30+ days of your actual data, not demos
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Performance Under Load: System tested at 2x your peak usage volumes
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Integration Plan: Detailed technical roadmap (add 50% buffer to timeline)
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Security Audit: Independent assessment within last 12 months
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SLA Guarantees: Performance benchmarks with financial penalties
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Exit Strategy: Complete data export in standard formats within 30 days
Business Protection
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Staged Payments: Tied to delivery milestones, not calendar dates
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Total Cost Transparency: All costs including training, support, scaling defined
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Pilot Period: 60-90 days with clear success criteria and exit rights
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Data Ownership: You retain full ownership of data and derived insights
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Competitive Protection: Clear policies on serving direct competitors
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Performance Benchmarking: Annual right to compare against alternatives
Vendor Viability
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Financial Stability: Recent financials or verified investor backing
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Customer References: 3+ similar companies willing to speak with you
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Support Structure: Local team with guaranteed response times
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Regulatory Compliance: Current certifications for your industry
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Business Continuity: Service protection if vendor acquired/pivots
Universal Red Flags to Avoid
- "One-size-fits-all" solutions for all industries
- Reluctance to provide references or case studies
- Pressure to sign quickly without adequate testing
- Vague answers about security or compliance
E-commerce
Can't handle seasonal/promotional variations
Healthcare
Limited regulatory understanding beyond basics
Finance
Insufficient market volatility stress testing
Energy
Ignores weather patterns or grid infrastructure
Implementation Success Factors
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Project Teams Defined: Clear roles and communication protocols
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Success Metrics Agreed: Baseline established and targets defined
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Risk Mitigation: Backup plans for critical processes
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Performance Monitoring: Regular vendor vs. promise reviews scheduled