AI can help customers, but can it help the bottom line?
A growing number of fintechs claim to use artificial intelligence to get ahead. However, how many of them are actually using technology to improve the experience for their customers is less clear.
In the spend management space in particular, two of the biggest players, Ramp and Brex, have talked about how they believe AI will transform the way they operate and serve their customers.
Ramp on Wednesday announced a new integration with Copilot, Microsoft’s brand of artificial intelligence technologies. Ramp says its addition with Copilot for Microsoft 365 means businesses don’t have to bounce between multiple tools and apps to gather spend information or set up advanced controls. Microsoft 365 is Redmond’s subscription productivity suite.
“Now they can use natural language to access Ramp’s smart AI assistant from their workplace and get the most advanced work done faster,” said Ramp CEO and co-founder Eric Glyman.
Users will be able to do things like issue new cards directly in Teams or set up and receive real-time notifications for employee transactions.
The company also announced a number of new features to expand Ramp’s capabilities to not only read queries, but also compose responses and take appropriate action, in context, based on customer data.
This includes interacting with Ramp as a conversationalist. For example, according to Glyman, if a manager is talking to a finance manager about raising the spending limit for their employee’s upcoming travel, the finance manager can point to the Ramp agent in the conversation and ask the bot to increase the spending limit to the specified amount.
Invest more in artificial intelligence
Both Brex and Ramp claim to have used AI in various ways for some time.
Brex specifically said it has been using artificial intelligence since its inception in underwriting, fraud, receipt matching and merchant categorization, among other product areas. However, it has concentrated its investments in AI over the past year, particularly in customer-facing scenarios.
