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.

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Many B2B companies failed by launching AI "co-pilots" that were too expensive for the minimal value they provided. The winning strategy, exemplified by Notion, is to create an AI add-on so valuable that users willingly pay a 50-100% premium, which in turn re-accelerates the company's growth.

Selling an efficiency-focused SaaS tool is harder than ever. CIOs are cutting classic SaaS tools while expanding their AI budget. Any remaining efficiency spend is being consumed by price hikes from giants like Salesforce, leaving no room for new, non-AI vendors.

Unlike the slow denial of SaaS by client-server companies, today's SaaS leaders (e.g., HubSpot, Notion) are rapidly integrating AI. They have an advantage due to vast proprietary data and existing distribution channels, making it harder for new AI-native startups to displace them. The old playbook of a slow incumbent may no longer apply.

A fundamental shift is occurring where startups allocate limited budgets toward specialized AI models and developer tools, rather than defaulting to AWS for all infrastructure. This signals a de-bundling of the traditional cloud stack and a change in platform priorities.

For established software companies with sluggish growth, the path forward is clear: find a way to become relevant in the age of AI. While they may not become the next Harvey, attaching to AI spend can boost growth from 15% to 25%, the difference between a viable public company and a sale to a private equity firm.

Focusing on AI for cost savings yields incremental gains. The transformative value comes from rethinking entire workflows to drive top-line growth. This is achieved by either delivering a service much faster or by expanding a high-touch service to a vastly larger audience ("do more").

The massive TAM expansion for AI relies on shifting spend from labor to technology budgets. This shift won't happen because of top-down CIO mandates. It must be driven by bottom-up product pull, where the value proposition is so overwhelmingly clear that customers are compelled to adopt it.

In the current market, AI companies see explosive growth through two primary vectors: attaching to the massive AI compute spend or directly replacing human labor. Companies merely using AI to improve an existing product without hitting one of these drivers risk being discounted as they lack a clear, exponential growth narrative.

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.

A 'tale of two cities' exists in SaaS. Traditional software budgets are frozen, with spending eaten by price hikes from incumbents. Simultaneously, new, separate AI budgets are creating massive opportunities, making the market feel dead for classic SaaS but booming for AI-native solutions.

Tapping Into Dedicated AI Budgets Is Key to Re-Accelerating SaaS Growth | RiffOn