In October, Box unveiled a new pricing approach for the company’s AI manufacturing capabilities. Instead of a fixed rate, the company designed a unique consumption-based model.
Each user receives 20 credits per month, perfect for any number of AI tasks that add up to 20 events, with each task charged a single credit. After that, people can dive into a corporate pool of 2,000 additional credits. If the customer exceeds this, it would be time to talk to a salesperson about purchasing additional credits.
Box CEO Aaron Levie explained that this approach provides a way to charge based on usage, with the understanding that some users will take advantage of AI capabilities more than others, while also factoring in the cost of using the OpenAI API, which company uses for its underlying large language model.
Meanwhile, Microsoft opted for a more traditional pricing model, announcing in November that it would charge $30 per user per month to use the features of Copilot, in addition to the cost of a regular monthly subscription to Office 365, which varies by customer.
While it became clear over the past year that enterprise software companies would be building AI production capabilities, in a panel on the impact of genetic AI on SaaS companies at Web Summit in November, Christine Spang, co-founder and CTO at Nylas , a communication API startup. and Manny Medina, CEO at sales enablement platform Outreach, discussed the challenges facing SaaS companies as they implement these capabilities.
Spang says, for starters, that despite the hype, genetic AI is clearly a big leap forward, and software companies should be looking for ways to incorporate it into their products. “I’m not going to say it’s like 10 out of 10 where the hype meets it [current] reality, but I think there’s real value there and what’s really going to make the difference is how people take the technology and connect it to other systems, other applications, and what kind of real value in different use cases with it.” , he said. .
