Companies like Notion and Datadog are re-accelerating by targeting new, dedicated AI budgets. This is separate from shrinking 'efficiency tool' budgets. Growth comes from solving problems that unlock this specific new spending category, not just adding a minor AI feature.

An IBM study reveals a significant performance gap in AI adoption. The top 20% of companies achieve over 60% ROI from their product engineering efforts, while the median return for the rest is only 36%. This highlights the value of mastering key team behaviors.

Data from RAMP indicates enterprise AI adoption has stalled at 45%, with 55% of businesses not paying for AI. This suggests that simply making models smarter isn't driving growth. The next adoption wave requires AI to become more practically useful and demonstrate clear business value, rather than just offering incremental intelligence gains.

While employee surveys show significant skepticism about AI's productivity benefits, actual spending data from Ramp tells a different story. The data shows companies are not only adopting AI tools but are renewing, expanding, and extending their contracts, indicating that revealed preference (actual spending) is a stronger signal than stated preference (survey answers).

A massive budget shift is underway where companies spend exponentially more on AI agents than on foundational software like CRM. One small team spends $500k annually on AI agents versus just $10k on Salesforce, signaling a tectonic shift in software value and spending priorities.

According to Ramp's AI index, Anthropic has become the default choice for businesses adopting AI for the first time, capturing 70% of this segment. This marks a complete reversal from 2023 when OpenAI led, suggesting Anthropic's enterprise-focused strategy is successfully capturing the lucrative business market.

New data from Ramp provides the first concrete business-level evidence of AI displacing labor. Businesses are reallocating budgets directly from freelancers to AI tools, with over half of companies using freelancers in 2022 having stopped entirely. The highest-spending freelance users shifted fastest, realizing 97% savings.

Ramp's AI index shows paid AI adoption among businesses has stalled. This indicates the initial wave of adoption driven by model capability leaps has passed. Future growth will depend less on raw model improvements and more on clear, high-ROI use cases for the mainstream market.

The trend is shifting from simply adopting AI to proving its ROI with specific metrics. As industry leaders publicly share their AI-driven gains, it creates a competitive necessity for all other companies to follow suit and quantify their own benefits, making it 'table stakes' for all.