Questions we didn't get to: Expectations vs. reality for the modern finance professional in 2024

On January 30th, we caught up with Benjamin Gammell, CFO at Brex and Antonio Reza, Head of Finance at Google to understand what their priorities are as 2024 gets rolling.

We managed to cover some of your questions live, but unfortunately there wasn't enough time to get to all of them. We managed to catch up with Benjamin post-event afterward though, and put the following questions to him:

How do you foresee balancing AI automation with the need for human judgment in finance, especially for complex decision-making scenarios?

A: I think the key is to start with the lowest hanging fruit and “work your way up”. In my view you can get pretty far, and save a lot of time and money, by just attacking the less complex tasks.

Finance is a good example of an area where human judgment and a lot of pattern recognition are crucial, so fully replacing complicated tasks is probably still a little ways away. 

Q: I like the perspective on the hype around AI, and solutions are appearing in the market in a very decentralized way. Any advice on use cases which are worth experimenting/pioneering vs waiting?

A: My answer to this question is similar to the one above. I think the world of AI is changing & improving with each passing day. The good thing is that there’s plenty to do to keep us busy already.

We are already seeing countless areas across the finance & accounting org where AI functionality can be utilized to improve processes and save time. 

Q: How do you think about helping technology teams prioritize resources between fixing the basics and creating new capabilities?

A: The key here is laying the right foundation and doing it right the first time. This will minimize the amount of time you have to spend patching/fixing basic functionality. This always feels like low ROI work and should be minimized.

At Brex, for instance, we set out to build a strong payments and banking core infrastructure from the beginning. Over the years this has allowed us to be nimbler and add new capabilities faster than if we would not have done so, and our teams spend less time rebuilding or fixing already existing systems. 

Q: What would you say are the top 3 to 5 skills that a finance manager needs for the future?

A: I'd say to remain relevant and thrive as a finance manager I’d highlight two skills:

1: The ability to adjust course and think on your feet. The finance function is changing faster and faster for each passing year so being nimble and, when needed, changing up how things are done is important.

2: Experience working with and manipulating large data sets in tools like Pigment, Looker, Hex, etc. I’m seeing most strong folks on finance teams being pretty sophisticated with tools that historically have been thought of as “data science tools”. 

Q: Markets seem to be optimistically positioned and betting on the success of AI. Are you aware of any actual success stories in the realm of finance outside of AP and machine learning utilizing AI?

A: Between those two, particularly the latter, you can think of a lot of use cases in the finance world, so I’m not sure there needs to be success stories outside of these areas for AI to be a success in the world of finance.

By applying machine learning you can improve more or less all key finance workstreams, including forecasting, cost budgeting, closing the books each month / quarter, etc. I think the right question is “how do we best leverage machine learning for maximum mileage?” vs. “what should we be doing outside of machine learning?”   

(Want to learn more about AI in finance? Read this blog post).

Catch up on the webinar

That's all for our follow up questions. If you'd like to watch the full webinar again on demand, it's available at this link.