AI Applications Earn Their Premium

Lower inference costs can improve margins for AI application companies, but more capable models and easier development tools can also make parts of an application easier to replace, so the commercial question is what customers will keep paying for as their alternatives improve. The piece argues that applications must outperform the customer's best credible alternative across the full workflow, make context cheaper to rent than to rebuild, and prove value before pricing to capture it, citing Repsol's blind evaluation of Harvey against Microsoft Copilot and its internal Lexia prototype and Decagon's Notion case study.