Gen AI is forcing a reckoning in how software companies charge for their products, according to Metronome’s CEO, Scott Woody. Traditional seat-based subscription pricing, once the standard for enterprise SaaS, is breaking down under the weight of AI systems that do work rather than simply provide access. In a recent AI + a16z podcast, Woody described the shift as an industry-wide reset, and one that most companies are unprepared for.
“You just inserted an insanely expensive line item into your bottom line in the form of AI,” Woody said. “You have to be engaging with it now.”
Metronome, which Woody co-founded in 2019, sells billing infrastructure meant to help software companies transition to usage-based and hybrid pricing models. While such models aren’t new: AWS and other infrastructure providers have used them for years, the complexity increases when applied to enterprise software layered with AI capabilities. “The value is now the work the software is doing on my behalf,” Woody said. “That doesn’t monetize in the ‘scaling with users’ way.”
Billing for AI Usage, Not Access
Woody’s perspective is informed by years working on monetization at Dropbox, where engineering teams struggled to run basic pricing experiments. Billing changes often took months to implement, and users were frequently confused by delayed or opaque charges. “Billing was really honestly more of a product surface than a once-a-month workflow,” he said.
As AI reshapes how companies define and deliver value, Woody argues that billing infrastructure must keep pace. In AI-heavy products, usage can spike unpredictably, and the cost of computation can be significant. “You can spend a million dollars on OpenAI in like three hours if you want to,” Woody said. That volatility demands real-time billing systems, spend controls, and immediate visibility for both the vendor and the customer.
Woody also warns that billing is not just a technical concern. Shifting to usage-based pricing requires organizational change across product, sales, finance, and customer success. “If I can’t talk to the CEO of that company, it’s not a real deal,” he said. “The CEO has to be like, ‘I’m going to take the hard path.’”
Despite that, most enterprise software companies are still built around models where access and not output drives revenue. “In a seat subscription business, you could kind of run your revenue org lazily,” Woody said. “In a usage-based model, every team has to be tightly aligned to value delivery, or the revenue doesn’t show up.”
Capitalizing on a Pricing Reset
Metronome’s bet is that AI will accelerate demand for more flexible billing systems. The company recently raised a $50 million Series C round led by NEA, bringing its total funding to $128 million. Customers include AI-native and cloud infrastructure firms like OpenAI, Anthropic, Databricks, Confluent, and NVIDIA, companies whose products don’t make sense under fixed, seat-based pricing.
In a blog post announcing the funding, Woody said Metronome’s platform now supports billing for more than 150 million end users and processed billions in usage-based revenue in the past year. The company claims its tools let teams experiment with new pricing models, adjust rates by customer cohort, and integrate real-time billing data into sales, product, and finance operations.
Still, many of the challenges Woody describes are broader than billing and may be difficult for Metronome, or any vendor, to fully solve. For example, large enterprises often manage bespoke contracts with different pricing terms, discounts, and data rules. Woody said he spoke to a public company handling $1 billion in usage-based spend, all of it reconciled manually. “Every single enterprise contract is different,” he said. “Creating the general rules engine that can handle all that complexity is very hard.”
The company’s framing of its product as infrastructure, rather than software, suggests its ambitions are long-term. Woody compared Metronome’s architecture to “Datadog plus a billing engine,” aimed at technical teams looking for control and adaptability. But it also underscores a key tension: the more critical billing becomes to product value and revenue recognition, the harder it is to move fast without introducing financial risk.
Whether Metronome can scale as quickly as its AI-native customers remains an open question. But Woody is clear on one point: the old ways of pricing software no longer fit. “Agility is the only thing that’s rewarded in this environment,” he said. “You can’t sit on a pricing change for nine months anymore. By the time you go live, your model is already outdated.”
