AI drives surge in complex software pricing models
Usage-based charges have risen sevenfold since 2025 - putting pressure on finance teams and increasing the risk of invoicing errors.
Published on 17th April 2026
Solvimon says companies are adopting more complex pricing models as AI changes how software is billed. According to the billing platform, usage-based charges have risen sevenfold since 2025.
Its data points to a shift away from flat monthly fees and seat-based pricing towards combinations of subscriptions and consumption-based charges. The fastest-growing software and AI businesses now use nearly five pricing structures on average, up from three over the past year.
That shift is putting pressure on finance teams as AI products create value in ways that do not fit neatly into older billing systems. Businesses are trying to bill for credits, tokens, usage and outcome-based measures alongside standard subscriptions, increasing the risk of invoicing errors and missed revenue.
A Bain & Company analysis of more than 30 established SaaS vendors found that 65% have already introduced hybrid pricing, adding AI usage or outcome metrics to traditional seat-based models. Solvimon argues that the spread of these structures is making billing one of the more fragile parts of the revenue cycle for companies with expanding product lines and more tailored commercial contracts.
Research from MGI found that SaaS companies can lose between 1% and 5% of annual recurring revenue each year through billing leakage caused by errors that repeat in each billing cycle until detected. For chief financial officers, that is bringing greater scrutiny to systems once treated as back-office tools rather than strategic infrastructure.
Billing strain
The issue has become more visible as AI services move into mainstream commercial software. Charging by user made sense when software access was closely tied to headcount. AI tools, however, can be consumed based on compute use, transaction volume or the number of generated outputs.
Companies are responding by layering several charging methods into a single contract. That can help protect margins, but it also adds operational complexity as finance teams reconcile usage data, contract terms and invoices across multiple entities and product lines.
“At Adyen, we processed almost a trillion euros a year. Billing was the system that could break everything else. When we saw AI companies hitting the same wall with hybrid pricing, multiple entities, and enterprise contracts that limit pricing flexibility, we knew what needed to be built. Pricing models are more complex because of AI and you can no longer price on a per seat basis as the risk of revenue leakage grows from unbilled usage to misconfigured contracts. That’s why we’re building accurate, real-time billing infrastructure to ensure companies capture every euro or dollar of earned revenue,” said Kim Verkooij, co-founder and chief executive officer of Solvimon.
The remarks reflect a broader shift in software economics. AI features often introduce variable costs because providers must pay for infrastructure such as graphics processing, model inference and data processing, making it harder to absorb those charges within a fixed monthly subscription.
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Hasan As Ari via Vecteezy