Get your free personalized podcast brief

We scan new podcasts and send you the top 5 insights daily.

Marketing leaders are re-evaluating their tech stacks, actively churning legacy tools that feel outdated. The freed-up budget is being reallocated to cover AI platform usage costs, like tokens or credits, and to invest in new, more capable "AI-forward" applications.

Related Insights

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.

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.

As more companies integrate AI, their costs are tied to variable usage (e.g., tokens, inference). This is causing a profound, economy-wide transformation away from predictable seat-based subscriptions towards more dynamic usage-based models to align costs with revenue.

The dominant per-user-per-month SaaS business model is becoming obsolete for AI-native companies. The new standard is consumption or outcome-based pricing. Customers will pay for the specific task an AI completes or the value it generates, not for a seat license, fundamentally changing how software is sold.

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.

The business model for AI is pivoting away from SaaS-style subscriptions. Enterprise-focused labs like Anthropic see massive revenue not from adding users, but from the immense token consumption of API power users. A single developer can be 100x more valuable than a subscriber, forcing a shift to consumption-based pricing.

The initial explosion in AI spending was largely additive, not a replacement for existing budgets. Going forward, this will change. Companies will start substituting AI spend for traditional SaaS licenses and human capital as they rationalize operating expenses and seek higher ROI.

Many marketing tools are simple UI wrappers over data sets for minimally complex tasks. CMO Amanda Cole argues that conversational AI can now perform these functions, eliminating the need for paid, single-purpose software. Marketers should cut these 'lightweight' tools to save budget.

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.

SaaS companies like HubSpot are shifting to credit-based pricing for AI features where costs are variable and opaque. This makes it nearly impossible for business leaders to budget for AI usage and operationalize new intelligent workflows effectively.

Marketing Budgets Are Shifting From Traditional SaaS Licenses to AI Credits and Tokens | RiffOn