VIDEO TRANSCRIPT
I do think it was worthwhile spending a a few minutes talking about why we think the recent evolution of generative AI is particularly meaningful for financial services institutions.
Namely, it's kinda two things. You know? Now with the advent of LLMs, computers can understand written human language, which means that people who are not technical, people who are not developers are able to interact with computers in new ways and get them to do things that previously they couldn't do, such as asking ChatGPT to help you create a marketing campaign or explain a complex contract or take a look at customer data and find customers who are underserved or potentially could be better sources of revenue.
In addition to that, and this has always been true, but it adds a new dimension now that computers can understand written language. Computers can reason based on the instructions that you're giving it. So it can help teams optimize whatever metric is most important to them, such as increasing revenue, saving time. Time is money, so that could mean saving money. It can improve the quality of the employee experience. So if somebody's got a very cumbersome process that's really annoying them, they can use, AI to help them streamline it or perhaps get rid of it entirely. And then, you know, we can just generally improve the way that customers are interacting with with your organization and the way that employees view themselves with their jobs.
So what does all that mean? That means that computers, because they're able to now do work that is hard to define and instruct, so it they're able to do things that are a little bit more nebulous and not necessarily confined to ones and zeros. That means that this technology offers teams the opportunity to scale up without increasing cost or sacrificing quality. So, basically, you can take the same team that you have today and two x, three x, four x, or even ten x productivity without adding without adding headcount or additional cost.