In October, Box unveiled a new pricing approach for the company's generative AI features. Instead of a flat rate, the company designed a unique consumption-based model.
Each user receives 20 credits per month, valid for any number of AI tasks totaling 20 events, with each task worth a single credit. After that, the people can draw on a business fund of 2000 additional credits. If the customer exceeds that figure, 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 would take advantage of AI features more than others, while also taking into account the cost of using the technology. OpenAI API, which the company is using for its underlying large language model.
Meanwhile, Microsoft has chosen a more traditional pricing model and announced in November that it would charge $30 per user per month to use its Copilot features, in addition to the cost of a regular monthly Office 365 subscription, which varies by customer.
While it became clear over the past year that enterprise software companies would be building generative AI capabilities, a panel on the impact of generative AI on SaaS companies At the Web Summit in November, Christine Spang, co-founder and CTO of Nylas, a communications API startup, and Manny Medina, CEO of sales enablement platform Outreach, talked about the challenges SaaS companies face when implementing these functions.
Spang says, for starters, that despite the hype, generative AI is clearly a big step forward, and software companies should look for ways to incorporate it into their products. "I'm not going to say it's like 10 out of 10 where hype meets reality, but I think there is real value and what will really make a difference is how people take the technology and connect it to other systems, other applications." and, in a way, they generate real value in different use cases with it,” he said.
It's also about finding a balance between offering the kind of features that customers are suddenly demanding and finding a way to price it in a way that provides real value to the customer while still allowing the company to make money. “In reality, those of us who bundle generative AI functions need to repeatedly consult with our large language model vendor, and that will get expensive quickly. So until we create experiences that are ten times more differentiated and that someone wants to pay for, it will be a challenge,” Medina said.
It's worth noting that model makers like OpenAI are already announcing price cuts as they find ways to run models more efficiently, or reducing prices on older products as new ones are announced. For example, in June, the company announced some new features that increase processing power, providing more benefit while reducing the cost of previous versions for developers who don't require all the new features.
Spang says his company is already using a consumption model based on the number of connected email or calendar apps, and hopes to follow a similar approach as they add generative AI features.
"We already have the case where some people send a lot more messages, or receive a lot more messages, and I think it's important to map to a similar pricing model that people understand, and then hopefully we can find a price that" “This works for the average,” he said.
But Medina says it's harder for an app to use a consumption model than an API provider like Nylas. “I just don't know if that's an acceptable model in apps. “When you are a Legos supplier (like Nylas), it is a different story, but for app suppliers it is more difficult.”
But it's also not clear that businesses are willing to pay a flat fee like Microsoft's $30 per month per user for Office 365, unless they can see the real value of that additional cost. “There is still no consensus until someone lowers the price and makes it very affordable for the rest of us, or we find a way to monetize it,” Medina said.
A big unknown is also the compliance costs that could be related to the use of this technology, which remains a big open question for companies and their customers. "So if you start incorporating some of these applications and the United States or another government passes a law that requires you to disclose the ingredient list of your AI, you won't get that from OpenAI, so it will be difficult," he added.
CIOs who control the company's technology budget are taking a close look at this technology, but are still trying to determine whether the additional cost passed on to them will pay for themselves in terms of increased employee productivity.
Sharon Mandell, CIO of Juniper Networks, says she is closely looking at the return on investment (ROI) of these features. "In 2024, we're going to put the GenAI hype to the test, because if those tools can produce the types of benefits they say, then the ROI on them is high and can help us eliminate other things," she said. So she and other CIOs are running pilots, moving cautiously and trying to find ways to measure whether there really is a productivity gain that justifies the increased investment.
Regardless, companies will continue to experiment with pricing models while their customers conduct pilot and concept testing. It seems like there's something to be gained from both, but until we start seeing more of these tools in production, it's hard to know the real benefits for everyone involved.
