AIStrategyGuide

AI Pricing Framework

Tier-based guidance for realistic proposals and cost estimates

Why Realistic Pricing Matters

Under-quoting to win deals creates a lose-lose situation. Customers face scope creep and budget overruns, while vendors struggle with unprofitable projects and damaged relationships.

❌ Consequences of Under-Pricing

  • Scope creep and change orders
  • Customer dissatisfaction
  • Project delays and failures
  • Unprofitable delivery

✅ Benefits of Realistic Pricing

  • Aligned expectations from day one
  • Proper resource allocation
  • Higher project success rates
  • Better customer relationships

This framework provides tier-based cost ranges based on actual implementation complexity.

Pro Tips for Maximum Value

🎯 When to Use This Tool

Use this before creating proposals and during internal proposal reviews. Reference this framework when sales pushes for discounts - these cost ranges represent what success actually requires. Cutting price means cutting scope or quality.

✅ Best Practices

  • Print and share with sales team - Educate your sales team on why Tier 3 can't be delivered for Tier 1 pricing
  • Include hidden costs explicitly - Break out data prep, infrastructure, and change management separately in proposals
  • Use ranges, not point estimates - "$150K-$500K" is honest. "$325K" is false precision and invites negotiation.
  • Explain TCO (Total Cost of Ownership) - Show year 1 + ongoing costs together so customer budgets accurately

🚨 Common Mistakes to Avoid

  • Matching competitor pricing without understanding their tier or quality (race to the bottom)
  • Under-pricing to "land and expand" (unprofitable projects kill your margin and reputation)
  • Forgetting Year 2+ maintenance costs (customer feels blindsided by renewal pricing)

🔗 Combine with Other Tools

Use Qualification Scorecard to ensure customer has budget → Reference this framework when creating SOW pricing → Use ROI Calculator to justify the investment to customer's CFO.

Cost Ranges by Tier

Tier 0

Rules-Based

2-4 months
POC/Pilot:$10K - $30K
Production (Year 1):$50K - $150K

Tier 1

Statistical

3-6 months
POC/Pilot:$20K - $75K
Production (Year 1):$100K - $300K

Tier 2

Machine Learning

6-12 months
POC/Pilot:$30K - $100K
Production (Year 1):$150K - $500K

Tier 3

Deep Learning

9-18 months
POC/Pilot:$75K - $250K
Production (Year 1):$300K - $1M+

Tier 4

Generative AI

6-12 months
POC/Pilot:$50K - $200K
Production (Year 1):$200K - $800K

Tier 5

Research

12-36+ months
POC/Pilot:$100K - $500K
Production (Year 1):$500K - $5M+

💡 Important Notes:

  • • Ranges assume customer has appropriate data readiness and team capabilities
  • • Production costs include implementation, training, integration, and first year support
  • • Ongoing costs (years 2+) typically 15-25% of year 1 for maintenance and support
  • • Custom development, integration complexity, and scale can significantly impact costs

What's Included in These Costs?

POC/Pilot Phase

Technical discovery and scoping
Data assessment and preparation
Model development or configuration
Limited testing with sample data
Results presentation and recommendations

Production Implementation

Full model training and optimization
Enterprise system integration
User interface development
Security and compliance implementation
User training and documentation
First year technical support

⚠️ Hidden Costs to Discuss

Make sure your proposal accounts for these often-overlooked costs:

Data Preparation

Cleaning, labeling, and structuring data can add 20-40% to project costs if customer data isn't ready.

Infrastructure

Cloud costs, GPU instances, or on-prem hardware can significantly impact TCO, especially for Tier 3+.

Change Management

User adoption, training, and process changes require dedicated resources that are often underestimated.

Ongoing Maintenance

Model retraining, performance monitoring, and support typically cost 15-25% annually after year 1.

Recommended Proposal Structure

Structure your proposals to set clear expectations and reduce risk:

Phase 1: Discovery & Planning (10-15% of budget)

Data assessment, technical architecture design, success criteria definition, and detailed project plan.

Phase 2: POC/Pilot (20-30% of budget)

Build and test with limited scope to validate technical approach and business value before full commitment.

Phase 3: Production Build (40-50% of budget)

Full-scale development, integration with enterprise systems, security hardening, and performance optimization.

Phase 4: Deployment & Training (15-20% of budget)

User training, documentation, change management, and production rollout with monitoring.

Phase 5: Support & Optimization (Ongoing)

Typically 15-25% of year 1 cost annually for maintenance, model retraining, and technical support.

💡 Pro Tip: Include clear exit criteria for each phase so customers can pause or adjust if expectations aren't met.

Use This Framework

Reference this framework when creating proposals to ensure realistic pricing: