SaaS & AI Pricing Rethought –
Benchmarks from 4,400 Software Profiles

The four drivers of AI transformation: Artificial intelligence is fundamentally changing the software economy by transforming the product (from rigid functions to autonomous agents), the cost structure (real marginal costs per AI interaction due to expensive compute), value creation (delivered work results rather than mere software access), and the role of software.

The massive jump in valuations (multiples): VC investors are paying significant premiums for true AI architectures. While traditional legacy SaaS platforms are valued at a revenue multiple of 5.5x, AI-enabled products are already fetching 8.5x, and purely AI-native architectures are commanding 21.2x, nearly four times as much.

Urgent need for pricing action: The urgency to adjust monetization strategies is extremely high. An overwhelming majority of 80% of all surveyed software and AI companies are planning or actively evaluating a change to their pricing model within the next 12 months.

A two-tiered market for AI monetization: So far, AI has been packaged primarily as a defensive measure within product portfolios. 50% of providers simply integrate AI features as a free standard component into their core product, and 22% do not monetize them at all. Differentiated monetization strategies (such as paid add-ons at 15% or credit models at 5%) are still the exception.

The shift in billing models: Pure subscriptions remain the most common primary model in 2026 at 40%, followed by hybrid models at 34%. Looking two years ahead, 63% of respondents expect hybrid models to be the most relevant for their business, while only 22% see pure subscriptions leading.

“Per-seat” pricing is facing serious competition: Billing based on users (seats) is rapidly losing its relevance. The market anticipates a shift toward outcome-based and credit-based pricing metrics. Nevertheless, there is also uncertainty: approximately 25% of participants have not yet established a target metric for the future

Pragmatism prevails, agent-based pricing over outcome-based pricing: Billing for autonomous AI agents is establishing itself on the market much faster than purely outcome-based pricing. Work can already be precisely defined and priced today based on tasks and workflows, while pure outcome-based compensation remains limited for the time being to niches with extremely clear, undisputed measurability and attribution.

The new bottleneck in product discovery: The software purchasing process is undergoing a fundamental shift, as one in four searches (25%) now begins in AI systems (such as ChatGPT, Claude, and Perplexity). Since 92% of all B2B buyers ultimately choose a product that was already on their initial shortlist, the machine-readability of prices and content becomes a decisive competitive advantage for even appearing in AI recommendations.