Finance AI for everyone

Hello, everyone, and welcome. Welcome to Finance AI Academy by OneStream. I'm Janette Kosior, VP of Product Marketing, and I'm here with Tiffany Ma, Director of Product Marketing. Tiff, thanks so much for joining today.

Thanks, Jeanette. Happy to be here. Thanks for having me. So I'm really excited today to talk to you about demystifying machine learning, generative AI, and agentic AI for finance.

And what I'd like to do is let's first break down some of these concepts into digestible finance-relevant examples.

So finance is very precise on making data super accurate, right? I mean, when we think about data, if we're 80% accurate, then we're 100% wrong.

And the numbers need to be so precise. So talk to me about how finance teams can leverage AI in today's world and ensure that data is accurate.

Finance teams really need to understand the AI technology that they're using, and really ensure that they understand the contextual point of that data.

And that's really where, you know, these purpose built AI solutions come in play here. And that's also where transparency is critical because, one, with finance the number has to be accurate, but also, two, they also have to understand where that number is coming from.

As a finance professional, I think I'd be a bit worried just using any generic AI technology, because how do I know to trust the data?

I can ask ChatGPT the same question twice and get two different answers. As a finance professional, how do I know the results that I'm going to get back I can trust?

Transparency is key here because, again, finance has to trust the numbers and where it's coming from.

And so with generative AI, it has to be able to list out its sources and link back to the source, as well as show exactly how they pulled that financial number.

And that's how finance can trust the numbers as a result. What is agenetic AI, and how is this different from generative AI?

So ever since ChatGPT came out in 2022 with generative AI, the development of AI has accelerated at a lightning pace.

So what we've seen over the last few years is the development of agenetic AI, which is, basically, a form of generative AI, but it's more autonomous, it's more dynamic and adaptive, and it involves lots of different models that is able to plan, choose different tools, and iteratively solve very complex tasks.

It almost sounds like, with the three different AI capabilities, we have quantitative AI, and that does the math.

Then we have generative AI, and that explains the math. And then agenetic AI that applies the math.

Am I thinking about that correctly? That's a really good analogy. Yeah, I would say exactly that. Quantitative was machine learning.

Generative was non-quantitative. Explaining the math. And agenetic is the combination of the two, essentially.

And so it's the most powerful one. And that's where we're seeing agenetic AI everywhere today. I could see this being really helpful for finance teams to forecast more accurate, to automatically reconcile.

Just I see so many different use cases where this can be applicable and very, very valuable. Absolutely, yeah.

Not only finance, but also operational teams and bringing the two together because as we see, finance is now more involved with operations.

And they are the data stewards for all things within the organization. And so you think about narrative generation, report generation moving into contract analysis and how that ties into your financials, and public filings processings.

It's really exciting, though, to think about the fact that I could, within my finance organization, utilize artificial intelligence to help me be able to do more analysis on the data, rather than focusing on figuring out the data and keep having to remodel or reforecast.

I'm curious in your thoughts or your experience, how is this expected to evolve over the next couple of years?

With agentic AI, again, the most advanced form of it, it's going to start being more and more powerful to where, again, the autonomy of it is going to come into play here.

Agenetic AI, when they have specialized skill sets, are going to be able to talk to each other. And, really, you're going to have a digital teammate that's able to take a lot of the tedious, menial tasks that, you know, finance users don't want to do.

And, like you said, shift that over to the important value add activities that humans are so great at. Problem solving, being a strategic partner to the rest of the organization, making critical decisions, and really steering the business forward. Thanks, Tiff, so much for joining me today on this chat. It was really enlightening. Thanks so much, Jeanette. It was so great to be on to help demystify what AI means for finance.