SaaStr AI App of the Week: Willingness to Pay. The Pricing Firm B2B + AI Companies Call When Per-Seat Stops Working

2026-07-11 · Source: SaaStrAI · Field: Business & Management — Corporate Strategy & Leadership, Project & Product Management, Sales & Commercial Development · Depth: Intermediate, medium

Summary

Willingness to Pay is a pricing consultancy led by Ulrik Lehrskov-Schmidt, specializing in B2B and AI companies struggling with outdated pricing models. With over 200 pricing redesigns and an average of 125 days from contract to live implementation, the firm boasts zero pricing blow-ups across clients including Microsoft, SAP, Samsung, Intel, and Bosch. Traditional per-seat pricing has become problematic for AI products due to variable token/inference costs and AI's ability to reduce headcount, making power users unprofitable and pricing directly against value delivered. Willingness to Pay addresses this by focusing on customer value and pricing structure, not just product features or internal costs. They implement new models through a risk-first, end-to-end rollout, starting with new logos and low-risk accounts before strategic ones.

Key takeaway

For AI Product Managers or Directors of AI/ML evaluating monetization strategies, your current per-seat pricing model is likely eroding profitability and value. You should prioritize a comprehensive pricing redesign, focusing on customer value and structural changes rather than simple price hikes. Ignoring this critical aspect risks significant revenue loss and competitive disadvantage. Consider utilizing resources like "The Pricing Roadmap" or engaging specialized consultancies to implement a risk-managed transition to usage or credit-based models.

Key insights

AI's variable costs and seat collapse invalidate traditional B2B pricing, demanding customer-centric, structural approaches.

Principles

• Price the customer, not the product.
• The money is in the structure.

Method

Design, validate with stakeholders, then roll out risk-first: new logos, then low-risk existing accounts, finally strategic accounts.

In practice

• Adopt usage-based or credit-based pricing.
• Validate new models with customers.
• Implement pricing changes incrementally.

Topics

• B2B Pricing
• AI Monetization
• Usage-Based Pricing
• Pricing Strategy
• Customer Value
• Willingness to Pay

Best for: Product Manager, Entrepreneur, AI Product Manager, Director of AI/ML, Consultant

Related on AIssential

• PagerDuty CIO on the shift from seat-based to usage-based pricing for AI — AI integration is driving a shift from seat-based to usage-based SaaS pricing for better value alignment and cost reflection.
• SaaStr AI App of the Week: Nue. The Revenue Platform Built for How B2B + AI Actually Prices Now — B2B + AI pricing demands flexible, integrated revenue infrastructure to support consumption and outcome-based models.
• The SaaS Destruction Map — The SaaS market is repricing due to AI agents breaking the per-seat pricing model.
• Build Smarter B2B Pricing For Long-Term Growth And Profitability — B2B AI pricing must align with customer outcomes and enable growth, moving beyond traditional seat-based models.
• The Right Way To Price An AI Product In 2026 — Flat-rate SaaS pricing models are unsustainable for AI products due to variable, usage-based underlying costs.
• If enough other companies report the same, the bubble pops. 🫧 — Major companies are reporting poor AI return on investment and reliability issues, suggesting a potential market correction for overvalued AI ventures.

See Counsel's argued verdicts on the open AI decisions leaders are weighing →

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by SaaStrAI.